diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..ec4a626fbb7799f6a25b45fb86344b2bf7b37e64
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1 @@
+*.pth filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..aaefd8b1b828039ad8760e4f99bb9c15af59f45e
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+.ipynb_checkpoints/
+__pycache__/
+pretrained_models/
\ No newline at end of file
diff --git a/ConvertBitrate.ipynb b/ConvertBitrate.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..13eb9f299972c314b2db9bf4b9f3a39f7edc8683
--- /dev/null
+++ b/ConvertBitrate.ipynb
@@ -0,0 +1,165 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8775d691",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import librosa\n",
+    "import os\n",
+    "import soundfile\n",
+    "from tqdm import tqdm, tqdm_notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bcd1f6dc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 26%|█████████████████████████████████████████████▊                                                                                                                                  | 2606/10000 [01:01<02:54, 42.35it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total audio file written : 2606\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "base_dir = \"../data/amitaro\"\n",
+    "output_dir = \"../data/amitaro_22050hz\"\n",
+    "all_dir = [f for f in os.listdir(base_dir) if not os.path.isfile(os.path.join(base_dir, f))]\n",
+    "\n",
+    "file_list = []\n",
+    "\n",
+    "skip_dir = [\"301_dousa\",\n",
+    "            \"801_eng_suuji\",\n",
+    "            \"801_eng_jikan\",\n",
+    "            \"803_eng_others\",\n",
+    "            \"912_alphabet\",\n",
+    "            \"912_alphabet2\",\n",
+    "            \"913_web\",\n",
+    "            \"sample\"]\n",
+    "\n",
+    "total_file_write = 0\n",
+    "\n",
+    "def recursive_til_audio_file_found(path):\n",
+    "    listed_dir = [f for f in os.listdir(path)]\n",
+    "    if len(listed_dir) == 0:\n",
+    "        return\n",
+    "    test_path_first = os.path.join(path, listed_dir[0])\n",
+    "    \n",
+    "    # continue through the directory if not a file\n",
+    "    if not os.path.isfile(test_path_first):\n",
+    "        for next_dir in listed_dir:\n",
+    "            next_path = os.path.join(path, next_dir)\n",
+    "            # skip any directory specify in skip_dir\n",
+    "            for skip in skip_dir:\n",
+    "                if next_path.find(skip) != -1:\n",
+    "                    break\n",
+    "            else:\n",
+    "                recursive_til_audio_file_found(next_path)\n",
+    "        return\n",
+    "\n",
+    "    #for new_dir in tqdm_notebook(listed_dir, desc=f\"Processing : {path}\"):\n",
+    "    for new_dir in listed_dir:\n",
+    "        new_path = os.path.join(path, new_dir)\n",
+    "        \n",
+    "        #if it is file, convert the audio to 16k and write to output directory\n",
+    "#        output_path_base = path.replace(base_dir, output_dir)\n",
+    "#        if not os.path.exists(output_path_base):\n",
+    "#            os.makedirs(output_path_base, exist_ok=True)\n",
+    "\n",
+    "        # not an audio file\n",
+    "        if new_path.find(\".wav\") == -1 and new_path.find(\".mp3\") == -1:\n",
+    "            continue\n",
+    "\n",
+    "        global total_file_write\n",
+    "#        audio, rate = librosa.load(new_path, sr=16000)\n",
+    "        audio, rate = librosa.load(new_path, sr=22050)\n",
+    "#        output_path = os.path.join(output_path_base, new_dir)\n",
+    "        output_path = os.path.join(output_dir, new_dir)\n",
+    "#        output_path = os.path.join(output_dir, \"sakuramiko_\" + str(total_file_write) + \".wav\")\n",
+    "#        output_path = os.path.join(output_dir, new_dir[0:-4] + \".wav\")\n",
+    "        soundfile.write(output_path, audio, rate, format='wav', subtype=\"PCM_16\")\n",
+    "        file_list.append(new_dir)\n",
+    "        \n",
+    "        total_file_write += 1\n",
+    "        pbar.update(1)\n",
+    "        #print(f\"\\rWrite file{output_path}\", end=\"\")\n",
+    "        \n",
+    "with tqdm(total=10000) as pbar:\n",
+    "    recursive_til_audio_file_found(base_dir)\n",
+    "print(f\"Total audio file written : {total_file_write}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "7efe2fec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "base_dir = \"../data/amitaro_22050hz\"\n",
+    "output_dir = \"./custom_character_voice/amitaro\"\n",
+    "listed_dir = [f for f in os.listdir(base_dir)]\n",
+    "for i, val in enumerate(listed_dir):\n",
+    "    os.rename(os.path.join(base_dir, val), os.path.join(output_dir, f\"amitaro_{i}.wav\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "34c1fd46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "out_json = {}\n",
+    "for val in file_list:\n",
+    "    out_json[val] = {\"path\":val, \"kana\":\"\"}\n",
+    "    \n",
+    "with open(\"./amitaro.json\", \"w\") as outfile:\n",
+    "    outfile.write(json.dumps(out_json))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/ConvertBitrate.py b/ConvertBitrate.py
new file mode 100644
index 0000000000000000000000000000000000000000..001f1d80ae22aec85da2501db06b727c9351cc5a
--- /dev/null
+++ b/ConvertBitrate.py
@@ -0,0 +1,77 @@
+import librosa
+import os
+import soundfile
+from tqdm import tqdm, tqdm_notebook
+
+base_dir = "./data_sakuramiko_senbetsu"
+output_dir = "./plachta/VITS-fast-fine-tuning/custom_character_voice/sakuramiko"
+all_dir = [f for f in os.listdir(base_dir) if not os.path.isfile(os.path.join(base_dir, f))]
+
+file_list = []
+
+skip_dir = ["301_dousa",
+            "801_eng_suuji",
+            "801_eng_jikan",
+            "803_eng_others",
+            "912_alphabet",
+            "912_alphabet2",
+            "913_web",
+            "sample"]
+
+total_file_write = 0
+
+def recursive_til_audio_file_found(path):
+    listed_dir = [f for f in os.listdir(path)]
+    if len(listed_dir) == 0:
+        return
+    test_path_first = os.path.join(path, listed_dir[0])
+    
+    # continue through the directory if not a file
+    if not os.path.isfile(test_path_first):
+        for next_dir in listed_dir:
+            next_path = os.path.join(path, next_dir)
+            # skip any directory specify in skip_dir
+            for skip in skip_dir:
+                if next_path.find(skip) != -1:
+                    break
+            else:
+                recursive_til_audio_file_found(next_path)
+        return
+
+    #for new_dir in tqdm_notebook(listed_dir, desc=f"Processing : {path}"):
+    for new_dir in listed_dir:
+        new_path = os.path.join(path, new_dir)
+        
+        #if it is file, convert the audio to 16k and write to output directory
+#        output_path_base = path.replace(base_dir, output_dir)
+#        if not os.path.exists(output_path_base):
+#            os.makedirs(output_path_base, exist_ok=True)
+
+        # not an audio file
+        if new_path.find(".wav") == -1 and new_path.find(".mp3") == -1:
+            continue
+
+        global total_file_write
+#        audio, rate = librosa.load(new_path, sr=16000)
+        audio, rate = librosa.load(new_path, sr=22050)
+#        output_path = os.path.join(output_path_base, new_dir)
+        output_path = os.path.join(output_dir, "sakuramiko_" + str(total_file_write) + ".wav")
+#        output_path = os.path.join(output_dir, new_dir[0:-4] + ".wav")
+        soundfile.write(output_path, audio, rate, format='wav', subtype="PCM_16")
+        file_list.append(new_dir)
+        
+        total_file_write += 1
+        pbar.update(1)
+        #print(f"\rWrite file{output_path}", end="")
+        
+with tqdm(total=24778) as pbar:
+    recursive_til_audio_file_found(base_dir)
+print(f"Total audio file written : {total_file_write}")
+
+import json
+out_json = {}
+for val in file_list:
+    out_json[val] = {"path":val, "kana":""}
+    
+with open("./amitaro.json", "w") as outfile:
+    outfile.write(json.dumps(out_json))
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
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+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
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+      by You to the Licensor shall be under the terms and conditions of
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+      the terms of any separate license agreement you may have executed
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+
+   6. Trademarks. This License does not grant permission to use the trade
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+      Contributor provides its Contributions) on an "AS IS" BASIS,
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+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
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+      on Your own behalf and on Your sole responsibility, not on behalf
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+   END OF TERMS AND CONDITIONS
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+
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+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
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+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
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+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/OUTPUT_MODEL/D_Amitaro.pth b/OUTPUT_MODEL/D_Amitaro.pth
new file mode 100644
index 0000000000000000000000000000000000000000..6c8fbfc9b633361c4f441e7c68f5582b84c4600f
--- /dev/null
+++ b/OUTPUT_MODEL/D_Amitaro.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4610d88f7ce89c54e7bbee6fe1a60b9c98ade40dc8ec052624d0fcac67d6676c
+size 187027092
diff --git a/OUTPUT_MODEL/G_Amitaro.pth b/OUTPUT_MODEL/G_Amitaro.pth
new file mode 100644
index 0000000000000000000000000000000000000000..48bbb1653a6c716bd56323c7c4ec54e79b72f172
--- /dev/null
+++ b/OUTPUT_MODEL/G_Amitaro.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7644eed4b2c8afd8102ba6ec231a81d620d3a9bd5b659c1481552a3b2d4fdbc9
+size 158888169
diff --git a/OUTPUT_MODEL/config.json b/OUTPUT_MODEL/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c132188785f33ec789445ff7aa21a0f99fdea69
--- /dev/null
+++ b/OUTPUT_MODEL/config.json
@@ -0,0 +1,56 @@
+{
+  "train": {
+    "log_interval": 200,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 2e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 1,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 8192,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "training_files":"./final_annotation_train.txt",
+    "validation_files":"./final_annotation_val.txt",
+    "text_cleaners":["japanese_cleaners"],
+    "max_wav_value": 32768.0,
+    "sampling_rate": 22050,
+    "filter_length": 1024,
+    "hop_length": 256,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null,
+    "add_blank": true,
+    "n_speakers": 1,
+    "cleaned_text": true
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [8,8,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256
+  },
+  "speakers": {"amitaro":0
+  },
+  "symbols": ["_", ",", ".", "!", "?", "-", "A", "E", "I", "N", "O", "Q", "U", "a", "b", "d", "e", "f", "g", "h", "i", "j", "k", "m", "n", "o", "p", "r", "s", "t", "u", "v", "w", "y", "z", "\u0283", "\u02a7", "\u2193", "\u2191", " "]
+}
diff --git a/ParseAmitaroHTML.py b/ParseAmitaroHTML.py
new file mode 100644
index 0000000000000000000000000000000000000000..ab6ae7ff9944d68f504db5225ac24c5ffa2a1cb1
--- /dev/null
+++ b/ParseAmitaroHTML.py
@@ -0,0 +1,68 @@
+pip --cert /etc/pki/ca-trust/source/anchors/tri-ace-CA-2015.cer install --trusted-host pypi.org --trusted-host files.pythonhosted.org beautifulsoup4
+
+from bs4 import BeautifulSoup
+
+f = open("./amitaro.htm", "r")
+txt = f.read()
+soup = BeautifulSoup(txt)
+print(soup.prettify())
+
+import json
+f = open('amitaro.json')
+file_list = json.load(f)
+
+td = soup.find_all('td')
+for i, val in enumerate(td):
+    if len(val.contents) == 0:
+        continue
+    key = val.contents[0]
+    if key in file_list:
+        #print(td[i-1].contents[0])
+        if len(td[i-1].contents) > 0:
+            #print(td[i-1].contents[0])
+            temp = BeautifulSoup(str(td[i-1].contents[0]))
+            a = temp.find_all('a')
+            print(a[0].contents[0])
+            file_list[key]["kana"] = str(a[0].contents[0])
+
+with open("./amitaro_with_kana.json", "w") as outfile:
+    outfile.write(json.dumps(file_list, indent=4,ensure_ascii=False))
+
+for key, val in file_list.items():
+    val["path"] = "./data_amitaro22k/" + val["path"]
+
+with open("./amitaro_with_kana.json", "w") as outfile:
+    outfile.write(json.dumps(file_list, indent=4,ensure_ascii=False))
+
+file = []
+for key, val in file_list.items():
+    if len(val['kana']) == 0:
+        continue
+    if val['kana'].find("（") != -1:
+        continue
+    file.append(f"{val['path']}|10|{val['kana']}")
+    
+amitaro_train = []
+amitaro_val = []
+for val in file:
+    amitaro_train.append(val)
+
+import random
+
+rands = []    
+while len(rands) < len(file)/10:
+    rand_num = random.randint(0, len(file)-1)
+    if rand_num in rands:
+        continue
+    amitaro_val.append(file[rand_num])
+    rands.append(rand_num)
+
+f = open("amitaro_train.txt", "w")
+for val in amitaro_train:
+    f.write(f"{val}\n")
+f.close()
+
+f = open("amitaro_val.txt", "w")
+for val in amitaro_val:
+    f.write(f"{val}\n")
+f.close()
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..42db7a72760e256f2bebd4c4fe911d3fc1e0ef0f
--- /dev/null
+++ b/README.md
@@ -0,0 +1,13 @@
+---
+title: VITS-TTS-Japanese-Only-Amitaro
+emoji: 🚀
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: 3.27.0
+app_file: app.py
+pinned: false
+python_version: '3.10'
+license: apache-2.0
+duplicated_from: Lycoris53/VITS-TTS-Japanese-Only-Amitaro
+---
diff --git a/Test_Inference.ipynb b/Test_Inference.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e0343b621c6aa787615dc1b1b62161569b44721e
--- /dev/null
+++ b/Test_Inference.ipynb
@@ -0,0 +1,129 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5dde1b9d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import utils\n",
+    "from models import SynthesizerTrn\n",
+    "import torch\n",
+    "from torch import no_grad, LongTensor\n",
+    "import librosa\n",
+    "from text import text_to_sequence, _clean_text\n",
+    "import commons\n",
+    "import scipy.io.wavfile as wavf\n",
+    "import os\n",
+    "\n",
+    "import IPython.display as ipd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f4bc040a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:root:Loaded checkpoint './OUTPUT_MODEL/G_latest.pth' (iteration 601)\n",
+      "o↑hayoogozaima↓sU.\n",
+      " length:18\n",
+      " length:18\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <audio  controls=\"controls\" >\n",
+       "                    <source 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type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model_path = \"./OUTPUT_MODEL/G_latest.pth\"\n",
+    "config_path = \"./OUTPUT_MODEL/config.json\"\n",
+    "\n",
+    "length = 1.0\n",
+    "device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n",
+    "\n",
+    "def get_text(text, hps, is_symbol):\n",
+    "    text_norm = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)\n",
+    "    if hps.data.add_blank:\n",
+    "        text_norm = commons.intersperse(text_norm, 0)\n",
+    "    text_norm = LongTensor(text_norm)\n",
+    "    return text_norm\n",
+    "\n",
+    "hps = utils.get_hparams_from_file(config_path)\n",
+    "net_g = SynthesizerTrn(\n",
+    "    len(hps.symbols),\n",
+    "    hps.data.filter_length // 2 + 1,\n",
+    "    hps.train.segment_size // hps.data.hop_length,\n",
+    "    n_speakers=hps.data.n_speakers,\n",
+    "    **hps.model).to(device)\n",
+    "_ = net_g.eval()\n",
+    "_ = utils.load_checkpoint(model_path, net_g, None)\n",
+    "\n",
+    "speaker_ids = hps.speakers\n",
+    "\n",
+    "text = \"おはようございます。\"\n",
+    "#text = \"[JA]\" + text + \"[JA]\"\n",
+    "speaker_id = 0\n",
+    "stn_tst = get_text(text, hps, False)\n",
+    "with no_grad():\n",
+    "    x_tst = stn_tst.unsqueeze(0).to(device)\n",
+    "    x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)\n",
+    "    sid = LongTensor([speaker_id]).to(device)\n",
+    "    audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.6,\n",
+    "                        length_scale=1.0 / length)[0][0, 0].data.cpu().float().numpy()\n",
+    "del stn_tst, x_tst, x_tst_lengths, sid\n",
+    "\n",
+    "ipd.display(ipd.Audio(audio, rate=hps.data.sampling_rate, normalize=False))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "032cc92d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/VC_inference.py b/VC_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..8b5db1fcb267213020f5d16f1b671b0ea346f37a
--- /dev/null
+++ b/VC_inference.py
@@ -0,0 +1,146 @@
+import os
+import numpy as np
+import torch
+from torch import no_grad, LongTensor
+import argparse
+import commons
+from mel_processing import spectrogram_torch
+import utils
+from models import SynthesizerTrn
+import gradio as gr
+import librosa
+import webbrowser
+
+from text import text_to_sequence, _clean_text
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+import logging
+logging.getLogger("PIL").setLevel(logging.WARNING)
+logging.getLogger("urllib3").setLevel(logging.WARNING)
+logging.getLogger("markdown_it").setLevel(logging.WARNING)
+logging.getLogger("httpx").setLevel(logging.WARNING)
+logging.getLogger("asyncio").setLevel(logging.WARNING)
+
+language_marks = {
+    "Japanese": "",
+    "日本語": "[JA]",
+    "简体中文": "[ZH]",
+    "English": "[EN]",
+    "Mix": "",
+}
+lang = ['日本語', '简体中文', 'English', 'Mix']
+def get_text(text, hps, is_symbol):
+    text_norm = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = LongTensor(text_norm)
+    return text_norm
+
+def create_tts_fn(model, hps, speaker_ids):
+    def tts_fn(text, speaker, language, speed):
+        if language is not None:
+            text = language_marks[language] + text + language_marks[language]
+        speaker_id = speaker_ids[speaker]
+        stn_tst = get_text(text, hps, False)
+        with no_grad():
+            x_tst = stn_tst.unsqueeze(0).to(device)
+            x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
+            sid = LongTensor([speaker_id]).to(device)
+            audio = model.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8,
+                                length_scale=1.0 / speed)[0][0, 0].data.cpu().float().numpy()
+        del stn_tst, x_tst, x_tst_lengths, sid
+        return "Success", (hps.data.sampling_rate, audio)
+
+    return tts_fn
+
+def create_vc_fn(model, hps, speaker_ids):
+    def vc_fn(original_speaker, target_speaker, record_audio, upload_audio):
+        input_audio = record_audio if record_audio is not None else upload_audio
+        if input_audio is None:
+            return "You need to record or upload an audio", None
+        sampling_rate, audio = input_audio
+        original_speaker_id = speaker_ids[original_speaker]
+        target_speaker_id = speaker_ids[target_speaker]
+
+        audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32)
+        if len(audio.shape) > 1:
+            audio = librosa.to_mono(audio.transpose(1, 0))
+        if sampling_rate != hps.data.sampling_rate:
+            audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=hps.data.sampling_rate)
+        with no_grad():
+            y = torch.FloatTensor(audio)
+            y = y / max(-y.min(), y.max()) / 0.99
+            y = y.to(device)
+            y = y.unsqueeze(0)
+            spec = spectrogram_torch(y, hps.data.filter_length,
+                                     hps.data.sampling_rate, hps.data.hop_length, hps.data.win_length,
+                                     center=False).to(device)
+            spec_lengths = LongTensor([spec.size(-1)]).to(device)
+            sid_src = LongTensor([original_speaker_id]).to(device)
+            sid_tgt = LongTensor([target_speaker_id]).to(device)
+            audio = model.voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt)[0][
+                0, 0].data.cpu().float().numpy()
+        del y, spec, spec_lengths, sid_src, sid_tgt
+        return "Success", (hps.data.sampling_rate, audio)
+
+    return vc_fn
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model_dir", default="./G_latest.pth", help="directory to your fine-tuned model")
+    parser.add_argument("--config_dir", default="./finetune_speaker.json", help="directory to your model config file")
+    parser.add_argument("--share", default=False, help="make link public (used in colab)")
+
+    args = parser.parse_args()
+    hps = utils.get_hparams_from_file(args.config_dir)
+
+
+    net_g = SynthesizerTrn(
+        len(hps.symbols),
+        hps.data.filter_length // 2 + 1,
+        hps.train.segment_size // hps.data.hop_length,
+        n_speakers=hps.data.n_speakers,
+        **hps.model).to(device)
+    _ = net_g.eval()
+
+    _ = utils.load_checkpoint(args.model_dir, net_g, None)
+    speaker_ids = hps.speakers
+    speakers = list(hps.speakers.keys())
+    tts_fn = create_tts_fn(net_g, hps, speaker_ids)
+    vc_fn = create_vc_fn(net_g, hps, speaker_ids)
+    app = gr.Blocks()
+    with app:
+        with gr.Tab("Text-to-Speech"):
+            with gr.Row():
+                with gr.Column():
+                    textbox = gr.TextArea(label="Text",
+                                          placeholder="Type your sentence here",
+                                          value="こんにちわ。", elem_id=f"tts-input")
+                    # select character
+                    char_dropdown = gr.Dropdown(choices=speakers, value=speakers[0], label='character')
+                    language_dropdown = gr.Dropdown(choices=lang, value=lang[0], label='language')
+                    duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1,
+                                                label='速度 Speed')
+                with gr.Column():
+                    text_output = gr.Textbox(label="Message")
+                    audio_output = gr.Audio(label="Output Audio", elem_id="tts-audio")
+                    btn = gr.Button("Generate!")
+                    btn.click(tts_fn,
+                              inputs=[textbox, char_dropdown, language_dropdown, duration_slider,],
+                              outputs=[text_output, audio_output])
+        with gr.Tab("Voice Conversion"):
+            gr.Markdown("""
+                            录制或上传声音，并选择要转换的音色。
+            """)
+            with gr.Column():
+                record_audio = gr.Audio(label="record your voice", source="microphone")
+                upload_audio = gr.Audio(label="or upload audio here", source="upload")
+                source_speaker = gr.Dropdown(choices=speakers, value=speakers[0], label="source speaker")
+                target_speaker = gr.Dropdown(choices=speakers, value=speakers[0], label="target speaker")
+            with gr.Column():
+                message_box = gr.Textbox(label="Message")
+                converted_audio = gr.Audio(label='converted audio')
+            btn = gr.Button("Convert!")
+            btn.click(vc_fn, inputs=[source_speaker, target_speaker, record_audio, upload_audio],
+                      outputs=[message_box, converted_audio])
+    webbrowser.open("http://127.0.0.1:7860")
+    app.launch(share=args.share)
+
diff --git a/amitaro_jp_base.json b/amitaro_jp_base.json
new file mode 100644
index 0000000000000000000000000000000000000000..3b85fb40fc11e618718101990bf457c64f53dcdf
--- /dev/null
+++ b/amitaro_jp_base.json
@@ -0,0 +1,56 @@
+{
+  "train": {
+    "log_interval": 200,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 2e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 8,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 8192,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "training_files":"./final_annotation_train.txt",
+    "validation_files":"./final_annotation_val.txt",
+    "text_cleaners":["japanese_cleaners"],
+    "max_wav_value": 32768.0,
+    "sampling_rate": 22050,
+    "filter_length": 1024,
+    "hop_length": 256,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null,
+    "add_blank": true,
+    "n_speakers": 1,
+    "cleaned_text": true
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [8,8,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256
+  },
+  "speakers": {"amitaro":0
+  },
+  "symbols": ["_", ",", ".", "!", "?", "-", "A", "E", "I", "N", "O", "Q", "U", "a", "b", "d", "e", "f", "g", "h", "i", "j", "k", "m", "n", "o", "p", "r", "s", "t", "u", "v", "w", "y", "z", "\u0283", "\u02a7", "\u2193", "\u2191", " "]
+}
diff --git a/app.py b/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..3f807ced7df992565fb2ac2f43f01111325c53d9
--- /dev/null
+++ b/app.py
@@ -0,0 +1,66 @@
+import utils
+from models import SynthesizerTrn
+import torch
+from torch import no_grad, LongTensor
+from text import text_to_sequence
+import gradio as gr
+import commons
+
+model_path = "./OUTPUT_MODEL/G_Amitaro.pth"
+config_path = "./OUTPUT_MODEL/config.json"
+
+length = 1.0
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+def get_text(text, hps, is_symbol):
+    text_norm = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = LongTensor(text_norm)
+    return text_norm
+
+def get_vits_array(text):
+    hps = utils.get_hparams_from_file(config_path)
+    net_g = SynthesizerTrn(
+        len(hps.symbols),
+        hps.data.filter_length // 2 + 1,
+        hps.train.segment_size // hps.data.hop_length,
+        n_speakers=hps.data.n_speakers,
+        **hps.model).to(device)
+    _ = net_g.eval()
+    _ = utils.load_checkpoint(model_path, net_g, None)
+    
+    speaker_ids = hps.speakers
+    
+    #text = "[JA]" + text + "[JA]"
+    speaker_id = 0
+    stn_tst = get_text(text, hps, False)
+    with no_grad():
+        x_tst = stn_tst.unsqueeze(0).to(device)
+        x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
+        sid = LongTensor([speaker_id]).to(device)
+        audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.6,
+                            length_scale=1.0 / length)[0][0, 0].data.cpu().float().numpy()
+    del stn_tst, x_tst, x_tst_lengths, sid
+    
+    return (hps.data.sampling_rate, audio)
+
+app = gr.Blocks()
+with app:
+    gr.Markdown("# VITS-TTS-Japanese-Only-Amitaro\n\n"
+        		"Sample usage of Finetune model [Lycoris53/Vits-Japanese-Only-Amitaro](https://huggingface.co/Lycoris53/Vits-Japanese-Only-Amitaro) \n"
+                "Base finetuning code is from [Plachtaa/VITS-fast-fine-tuning](https://github.com/Plachtaa/VITS-fast-fine-tuning)"
+                )
+    with gr.Row():
+        with gr.Column():
+            textbox = gr.TextArea(label="Text",
+                                  placeholder="Type your sentence here (Maximum 150 words)",
+                                  value="おはようございます。")
+        with gr.Column():
+            audio_output = gr.Audio(label="Output Audio")
+            btn = gr.Button("Generate　Voice!")
+            btn.click(get_vits_array,
+                      inputs=[textbox],
+                      outputs=[audio_output])
+
+app.queue(concurrency_count=3).launch()
\ No newline at end of file
diff --git a/attentions.py b/attentions.py
new file mode 100644
index 0000000000000000000000000000000000000000..7258a9e6b95e741a9a7d5faf3789d50b3404a343
--- /dev/null
+++ b/attentions.py
@@ -0,0 +1,303 @@
+import copy
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+import commons
+import modules
+from modules import LayerNorm
+   
+
+class Encoder(nn.Module):
+  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4, **kwargs):
+    super().__init__()
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.window_size = window_size
+
+    self.drop = nn.Dropout(p_dropout)
+    self.attn_layers = nn.ModuleList()
+    self.norm_layers_1 = nn.ModuleList()
+    self.ffn_layers = nn.ModuleList()
+    self.norm_layers_2 = nn.ModuleList()
+    for i in range(self.n_layers):
+      self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size))
+      self.norm_layers_1.append(LayerNorm(hidden_channels))
+      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout))
+      self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+  def forward(self, x, x_mask):
+    attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+    x = x * x_mask
+    for i in range(self.n_layers):
+      y = self.attn_layers[i](x, x, attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_1[i](x + y)
+
+      y = self.ffn_layers[i](x, x_mask)
+      y = self.drop(y)
+      x = self.norm_layers_2[i](x + y)
+    x = x * x_mask
+    return x
+
+
+class Decoder(nn.Module):
+  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs):
+    super().__init__()
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.proximal_bias = proximal_bias
+    self.proximal_init = proximal_init
+
+    self.drop = nn.Dropout(p_dropout)
+    self.self_attn_layers = nn.ModuleList()
+    self.norm_layers_0 = nn.ModuleList()
+    self.encdec_attn_layers = nn.ModuleList()
+    self.norm_layers_1 = nn.ModuleList()
+    self.ffn_layers = nn.ModuleList()
+    self.norm_layers_2 = nn.ModuleList()
+    for i in range(self.n_layers):
+      self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init))
+      self.norm_layers_0.append(LayerNorm(hidden_channels))
+      self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout))
+      self.norm_layers_1.append(LayerNorm(hidden_channels))
+      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
+      self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+  def forward(self, x, x_mask, h, h_mask):
+    """
+    x: decoder input
+    h: encoder output
+    """
+    self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
+    encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+    x = x * x_mask
+    for i in range(self.n_layers):
+      y = self.self_attn_layers[i](x, x, self_attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_0[i](x + y)
+
+      y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
+      y = self.drop(y)
+      x = self.norm_layers_1[i](x + y)
+      
+      y = self.ffn_layers[i](x, x_mask)
+      y = self.drop(y)
+      x = self.norm_layers_2[i](x + y)
+    x = x * x_mask
+    return x
+
+
+class MultiHeadAttention(nn.Module):
+  def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False):
+    super().__init__()
+    assert channels % n_heads == 0
+
+    self.channels = channels
+    self.out_channels = out_channels
+    self.n_heads = n_heads
+    self.p_dropout = p_dropout
+    self.window_size = window_size
+    self.heads_share = heads_share
+    self.block_length = block_length
+    self.proximal_bias = proximal_bias
+    self.proximal_init = proximal_init
+    self.attn = None
+
+    self.k_channels = channels // n_heads
+    self.conv_q = nn.Conv1d(channels, channels, 1)
+    self.conv_k = nn.Conv1d(channels, channels, 1)
+    self.conv_v = nn.Conv1d(channels, channels, 1)
+    self.conv_o = nn.Conv1d(channels, out_channels, 1)
+    self.drop = nn.Dropout(p_dropout)
+
+    if window_size is not None:
+      n_heads_rel = 1 if heads_share else n_heads
+      rel_stddev = self.k_channels**-0.5
+      self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
+      self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
+
+    nn.init.xavier_uniform_(self.conv_q.weight)
+    nn.init.xavier_uniform_(self.conv_k.weight)
+    nn.init.xavier_uniform_(self.conv_v.weight)
+    if proximal_init:
+      with torch.no_grad():
+        self.conv_k.weight.copy_(self.conv_q.weight)
+        self.conv_k.bias.copy_(self.conv_q.bias)
+      
+  def forward(self, x, c, attn_mask=None):
+    q = self.conv_q(x)
+    k = self.conv_k(c)
+    v = self.conv_v(c)
+    
+    x, self.attn = self.attention(q, k, v, mask=attn_mask)
+
+    x = self.conv_o(x)
+    return x
+
+  def attention(self, query, key, value, mask=None):
+    # reshape [b, d, t] -> [b, n_h, t, d_k]
+    b, d, t_s, t_t = (*key.size(), query.size(2))
+    query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
+    key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+    value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+
+    scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
+    if self.window_size is not None:
+      assert t_s == t_t, "Relative attention is only available for self-attention."
+      key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
+      rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings)
+      scores_local = self._relative_position_to_absolute_position(rel_logits)
+      scores = scores + scores_local
+    if self.proximal_bias:
+      assert t_s == t_t, "Proximal bias is only available for self-attention."
+      scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype)
+    if mask is not None:
+      scores = scores.masked_fill(mask == 0, -1e4)
+      if self.block_length is not None:
+        assert t_s == t_t, "Local attention is only available for self-attention."
+        block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length)
+        scores = scores.masked_fill(block_mask == 0, -1e4)
+    p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
+    p_attn = self.drop(p_attn)
+    output = torch.matmul(p_attn, value)
+    if self.window_size is not None:
+      relative_weights = self._absolute_position_to_relative_position(p_attn)
+      value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s)
+      output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings)
+    output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t]
+    return output, p_attn
+
+  def _matmul_with_relative_values(self, x, y):
+    """
+    x: [b, h, l, m]
+    y: [h or 1, m, d]
+    ret: [b, h, l, d]
+    """
+    ret = torch.matmul(x, y.unsqueeze(0))
+    return ret
+
+  def _matmul_with_relative_keys(self, x, y):
+    """
+    x: [b, h, l, d]
+    y: [h or 1, m, d]
+    ret: [b, h, l, m]
+    """
+    ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
+    return ret
+
+  def _get_relative_embeddings(self, relative_embeddings, length):
+    max_relative_position = 2 * self.window_size + 1
+    # Pad first before slice to avoid using cond ops.
+    pad_length = max(length - (self.window_size + 1), 0)
+    slice_start_position = max((self.window_size + 1) - length, 0)
+    slice_end_position = slice_start_position + 2 * length - 1
+    if pad_length > 0:
+      padded_relative_embeddings = F.pad(
+          relative_embeddings,
+          commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]))
+    else:
+      padded_relative_embeddings = relative_embeddings
+    used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position]
+    return used_relative_embeddings
+
+  def _relative_position_to_absolute_position(self, x):
+    """
+    x: [b, h, l, 2*l-1]
+    ret: [b, h, l, l]
+    """
+    batch, heads, length, _ = x.size()
+    # Concat columns of pad to shift from relative to absolute indexing.
+    x = F.pad(x, commons.convert_pad_shape([[0,0],[0,0],[0,0],[0,1]]))
+
+    # Concat extra elements so to add up to shape (len+1, 2*len-1).
+    x_flat = x.view([batch, heads, length * 2 * length])
+    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0,0],[0,0],[0,length-1]]))
+
+    # Reshape and slice out the padded elements.
+    x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:]
+    return x_final
+
+  def _absolute_position_to_relative_position(self, x):
+    """
+    x: [b, h, l, l]
+    ret: [b, h, l, 2*l-1]
+    """
+    batch, heads, length, _ = x.size()
+    # padd along column
+    x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length-1]]))
+    x_flat = x.view([batch, heads, length**2 + length*(length -1)])
+    # add 0's in the beginning that will skew the elements after reshape
+    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
+    x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:]
+    return x_final
+
+  def _attention_bias_proximal(self, length):
+    """Bias for self-attention to encourage attention to close positions.
+    Args:
+      length: an integer scalar.
+    Returns:
+      a Tensor with shape [1, 1, length, length]
+    """
+    r = torch.arange(length, dtype=torch.float32)
+    diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
+    return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
+
+
+class FFN(nn.Module):
+  def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False):
+    super().__init__()
+    self.in_channels = in_channels
+    self.out_channels = out_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.activation = activation
+    self.causal = causal
+
+    if causal:
+      self.padding = self._causal_padding
+    else:
+      self.padding = self._same_padding
+
+    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
+    self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
+    self.drop = nn.Dropout(p_dropout)
+
+  def forward(self, x, x_mask):
+    x = self.conv_1(self.padding(x * x_mask))
+    if self.activation == "gelu":
+      x = x * torch.sigmoid(1.702 * x)
+    else:
+      x = torch.relu(x)
+    x = self.drop(x)
+    x = self.conv_2(self.padding(x * x_mask))
+    return x * x_mask
+  
+  def _causal_padding(self, x):
+    if self.kernel_size == 1:
+      return x
+    pad_l = self.kernel_size - 1
+    pad_r = 0
+    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+    x = F.pad(x, commons.convert_pad_shape(padding))
+    return x
+
+  def _same_padding(self, x):
+    if self.kernel_size == 1:
+      return x
+    pad_l = (self.kernel_size - 1) // 2
+    pad_r = self.kernel_size // 2
+    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+    x = F.pad(x, commons.convert_pad_shape(padding))
+    return x
diff --git a/cmd_inference.py b/cmd_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..cfaee189e3905d5e6f0fc6c85f36fbc978cb1508
--- /dev/null
+++ b/cmd_inference.py
@@ -0,0 +1,106 @@
+"""该模块用于生成VITS文件
+使用方法
+
+python cmd_inference.py -m 模型路径 -c 配置文件路径 -o 输出文件路径 -l 输入的语言 -t 输入文本 -s 合成目标说话人名称
+
+可选参数
+-ns 感情变化程度
+-nsw 音素发音长度
+-ls 整体语速
+-on 输出文件的名称
+
+"""
+
+from pathlib import Path
+import utils
+from models import SynthesizerTrn
+import torch
+from torch import no_grad, LongTensor
+import librosa
+from text import text_to_sequence, _clean_text
+import commons
+import scipy.io.wavfile as wavf
+import os
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+language_marks = {
+    "Japanese": "",
+    "日本語": "[JA]",
+    "简体中文": "[ZH]",
+    "English": "[EN]",
+    "Mix": "",
+}
+
+
+def get_text(text, hps, is_symbol):
+    text_norm = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = LongTensor(text_norm)
+    return text_norm
+
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(description='vits inference')
+    #必须参数
+    parser.add_argument('-m', '--model_path', type=str, default="logs/44k/G_0.pth", help='模型路径')
+    parser.add_argument('-c', '--config_path', type=str, default="configs/config.json", help='配置文件路径')
+    parser.add_argument('-o', '--output_path', type=str, default="output/vits", help='输出文件路径')
+    parser.add_argument('-l', '--language', type=str, default="日本語", help='输入的语言')
+    parser.add_argument('-t', '--text', type=str, help='输入文本')
+    parser.add_argument('-s', '--spk', type=str, help='合成目标说话人名称')
+    #可选参数
+    parser.add_argument('-on', '--output_name', type=str, default="output", help='输出文件的名称')
+    parser.add_argument('-ns', '--noise_scale', type=float,default= .667,help='感情变化程度')
+    parser.add_argument('-nsw', '--noise_scale_w', type=float,default=0.6, help='音素发音长度')
+    parser.add_argument('-ls', '--length_scale', type=float,default=1, help='整体语速')
+    
+    args = parser.parse_args()
+    
+    model_path = args.model_path
+    config_path = args.config_path
+    output_dir = Path(args.output_path)
+    output_dir.mkdir(parents=True, exist_ok=True)
+    
+    language = args.language
+    text = args.text
+    spk = args.spk
+    noise_scale = args.noise_scale
+    noise_scale_w = args.noise_scale_w
+    length = args.length_scale
+    output_name = args.output_name
+    
+    hps = utils.get_hparams_from_file(config_path)
+    net_g = SynthesizerTrn(
+        len(hps.symbols),
+        hps.data.filter_length // 2 + 1,
+        hps.train.segment_size // hps.data.hop_length,
+        n_speakers=hps.data.n_speakers,
+        **hps.model).to(device)
+    _ = net_g.eval()
+    _ = utils.load_checkpoint(model_path, net_g, None)
+    
+    speaker_ids = hps.speakers
+
+
+    if language is not None:
+        text = language_marks[language] + text + language_marks[language]
+        speaker_id = speaker_ids[spk]
+        stn_tst = get_text(text, hps, False)
+        with no_grad():
+            x_tst = stn_tst.unsqueeze(0).to(device)
+            x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
+            sid = LongTensor([speaker_id]).to(device)
+            audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
+                                length_scale=1.0 / length)[0][0, 0].data.cpu().float().numpy()
+        del stn_tst, x_tst, x_tst_lengths, sid
+
+        wavf.write(str(output_dir)+"/"+output_name+".wav",hps.data.sampling_rate,audio)
+    
+
+    
+    
\ No newline at end of file
diff --git a/commons.py b/commons.py
new file mode 100644
index 0000000000000000000000000000000000000000..09e6742475a4724ac0789c320039bed82961213c
--- /dev/null
+++ b/commons.py
@@ -0,0 +1,164 @@
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+
+def init_weights(m, mean=0.0, std=0.01):
+  classname = m.__class__.__name__
+  if classname.find("Conv") != -1:
+    m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+  return int((kernel_size*dilation - dilation)/2)
+
+
+def convert_pad_shape(pad_shape):
+  l = pad_shape[::-1]
+  pad_shape = [item for sublist in l for item in sublist]
+  return pad_shape
+
+
+def intersperse(lst, item):
+  result = [item] * (len(lst) * 2 + 1)
+  result[1::2] = lst
+  return result
+
+
+def kl_divergence(m_p, logs_p, m_q, logs_q):
+  """KL(P||Q)"""
+  kl = (logs_q - logs_p) - 0.5
+  kl += 0.5 * (torch.exp(2. * logs_p) + ((m_p - m_q)**2)) * torch.exp(-2. * logs_q)
+  return kl
+
+
+def rand_gumbel(shape):
+  """Sample from the Gumbel distribution, protect from overflows."""
+  uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
+  return -torch.log(-torch.log(uniform_samples))
+
+
+def rand_gumbel_like(x):
+  g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
+  return g
+
+
+def slice_segments(x, ids_str, segment_size=4):
+  ret = torch.zeros_like(x[:, :, :segment_size])
+  for i in range(x.size(0)):
+    idx_str = ids_str[i]
+    idx_end = idx_str + segment_size
+    try:
+      ret[i] = x[i, :, idx_str:idx_end]
+    except RuntimeError:
+      print("?")
+  return ret
+
+
+def rand_slice_segments(x, x_lengths=None, segment_size=4):
+  b, d, t = x.size()
+  if x_lengths is None:
+    x_lengths = t
+  ids_str_max = x_lengths - segment_size + 1
+  ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
+  ret = slice_segments(x, ids_str, segment_size)
+  return ret, ids_str
+
+
+def get_timing_signal_1d(
+    length, channels, min_timescale=1.0, max_timescale=1.0e4):
+  position = torch.arange(length, dtype=torch.float)
+  num_timescales = channels // 2
+  log_timescale_increment = (
+      math.log(float(max_timescale) / float(min_timescale)) /
+      (num_timescales - 1))
+  inv_timescales = min_timescale * torch.exp(
+      torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment)
+  scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
+  signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
+  signal = F.pad(signal, [0, 0, 0, channels % 2])
+  signal = signal.view(1, channels, length)
+  return signal
+
+
+def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
+  b, channels, length = x.size()
+  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+  return x + signal.to(dtype=x.dtype, device=x.device)
+
+
+def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
+  b, channels, length = x.size()
+  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+  return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
+
+
+def subsequent_mask(length):
+  mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
+  return mask
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
+  n_channels_int = n_channels[0]
+  in_act = input_a + input_b
+  t_act = torch.tanh(in_act[:, :n_channels_int, :])
+  s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
+  acts = t_act * s_act
+  return acts
+
+
+def convert_pad_shape(pad_shape):
+  l = pad_shape[::-1]
+  pad_shape = [item for sublist in l for item in sublist]
+  return pad_shape
+
+
+def shift_1d(x):
+  x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
+  return x
+
+
+def sequence_mask(length, max_length=None):
+  if max_length is None:
+    max_length = length.max()
+  x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+  return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def generate_path(duration, mask):
+  """
+  duration: [b, 1, t_x]
+  mask: [b, 1, t_y, t_x]
+  """
+  device = duration.device
+  
+  b, _, t_y, t_x = mask.shape
+  cum_duration = torch.cumsum(duration, -1)
+  
+  cum_duration_flat = cum_duration.view(b * t_x)
+  path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
+  path = path.view(b, t_x, t_y)
+  path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
+  path = path.unsqueeze(1).transpose(2,3) * mask
+  return path
+
+
+def clip_grad_value_(parameters, clip_value, norm_type=2):
+  if isinstance(parameters, torch.Tensor):
+    parameters = [parameters]
+  parameters = list(filter(lambda p: p.grad is not None, parameters))
+  norm_type = float(norm_type)
+  if clip_value is not None:
+    clip_value = float(clip_value)
+
+  total_norm = 0
+  for p in parameters:
+    param_norm = p.grad.data.norm(norm_type)
+    total_norm += param_norm.item() ** norm_type
+    if clip_value is not None:
+      p.grad.data.clamp_(min=-clip_value, max=clip_value)
+  total_norm = total_norm ** (1. / norm_type)
+  return total_norm
diff --git a/configs/amitaro_jp_base.json b/configs/amitaro_jp_base.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c132188785f33ec789445ff7aa21a0f99fdea69
--- /dev/null
+++ b/configs/amitaro_jp_base.json
@@ -0,0 +1,56 @@
+{
+  "train": {
+    "log_interval": 200,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 2e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 1,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 8192,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "training_files":"./final_annotation_train.txt",
+    "validation_files":"./final_annotation_val.txt",
+    "text_cleaners":["japanese_cleaners"],
+    "max_wav_value": 32768.0,
+    "sampling_rate": 22050,
+    "filter_length": 1024,
+    "hop_length": 256,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null,
+    "add_blank": true,
+    "n_speakers": 1,
+    "cleaned_text": true
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [8,8,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256
+  },
+  "speakers": {"amitaro":0
+  },
+  "symbols": ["_", ",", ".", "!", "?", "-", "A", "E", "I", "N", "O", "Q", "U", "a", "b", "d", "e", "f", "g", "h", "i", "j", "k", "m", "n", "o", "p", "r", "s", "t", "u", "v", "w", "y", "z", "\u0283", "\u02a7", "\u2193", "\u2191", " "]
+}
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new file mode 100644
index 0000000000000000000000000000000000000000..bb9f3d69c843cecc09a8ed230a4f81fa70b65082
--- /dev/null
+++ b/custom_character_voice/amitaro/amitaro_24.wav
@@ -0,0 +1,4 @@
+[ViewState]
+Mode=
+Vid=
+FolderType=Generic
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diff --git a/data_utils.py b/data_utils.py
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index 0000000000000000000000000000000000000000..fae525a40ecb825205ff08789e703ebc610b1137
--- /dev/null
+++ b/data_utils.py
@@ -0,0 +1,276 @@
+import time
+import os
+import random
+import numpy as np
+import torch
+import torch.utils.data
+import torchaudio
+
+import commons
+from mel_processing import spectrogram_torch
+from utils import load_wav_to_torch, load_filepaths_and_text
+from text import text_to_sequence, cleaned_text_to_sequence
+"""Multi speaker version"""
+
+
+class TextAudioSpeakerLoader(torch.utils.data.Dataset):
+    """
+        1) loads audio, speaker_id, text pairs
+        2) normalizes text and converts them to sequences of integers
+        3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, audiopaths_sid_text, hparams, symbols):
+        self.audiopaths_sid_text = load_filepaths_and_text(audiopaths_sid_text)
+        self.text_cleaners = hparams.text_cleaners
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+
+        self.cleaned_text = getattr(hparams, "cleaned_text", False)
+
+        self.add_blank = hparams.add_blank
+        self.min_text_len = getattr(hparams, "min_text_len", 1)
+        self.max_text_len = getattr(hparams, "max_text_len", 190)
+        self.symbols = symbols
+
+        random.seed(1234)
+        random.shuffle(self.audiopaths_sid_text)
+        self._filter()
+
+    def _filter(self):
+        """
+        Filter text & store spec lengths
+        """
+        # Store spectrogram lengths for Bucketing
+        # wav_length ~= file_size / (wav_channels * Bytes per dim) = file_size / (1 * 2)
+        # spec_length = wav_length // hop_length
+
+        audiopaths_sid_text_new = []
+        lengths = []
+        for audiopath, sid, text in self.audiopaths_sid_text:
+            # audiopath = "./user_voice/" + audiopath
+
+            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
+                audiopaths_sid_text_new.append([audiopath, sid, text])
+                lengths.append(os.path.getsize(audiopath) // (2 * self.hop_length))
+        self.audiopaths_sid_text = audiopaths_sid_text_new
+        self.lengths = lengths
+
+    def get_audio_text_speaker_pair(self, audiopath_sid_text):
+        # separate filename, speaker_id and text
+        audiopath, sid, text = audiopath_sid_text[0], audiopath_sid_text[1], audiopath_sid_text[2]
+        text = self.get_text(text)
+        spec, wav = self.get_audio(audiopath)
+        sid = self.get_sid(sid)
+        return (text, spec, wav, sid)
+
+    def get_audio(self, filename):
+        # audio, sampling_rate = load_wav_to_torch(filename)
+        # if sampling_rate != self.sampling_rate:
+        #     raise ValueError("{} {} SR doesn't match target {} SR".format(
+        #         sampling_rate, self.sampling_rate))
+        # audio_norm = audio / self.max_wav_value if audio.max() > 10 else audio
+        # audio_norm = audio_norm.unsqueeze(0)
+        audio_norm, sampling_rate = torchaudio.load(filename, frame_offset=0, num_frames=-1, normalize=True, channels_first=True)
+        # spec_filename = filename.replace(".wav", ".spec.pt")
+        # if os.path.exists(spec_filename):
+        #     spec = torch.load(spec_filename)
+        # else:
+        #     try:
+        spec = spectrogram_torch(audio_norm, self.filter_length,
+                                 self.sampling_rate, self.hop_length, self.win_length,
+                                 center=False)
+        spec = spec.squeeze(0)
+            # except NotImplementedError:
+            #     print("?")
+            # spec = torch.squeeze(spec, 0)
+            # torch.save(spec, spec_filename)
+        return spec, audio_norm
+
+    def get_text(self, text):
+        if self.cleaned_text:
+            text_norm = cleaned_text_to_sequence(text, self.symbols)
+        else:
+            text_norm = text_to_sequence(text, self.text_cleaners)
+        if self.add_blank:
+            text_norm = commons.intersperse(text_norm, 0)
+        text_norm = torch.LongTensor(text_norm)
+        return text_norm
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def __getitem__(self, index):
+        return self.get_audio_text_speaker_pair(self.audiopaths_sid_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_sid_text)
+
+
+class TextAudioSpeakerCollate():
+    """ Zero-pads model inputs and targets
+    """
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text, audio and speaker identities
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized, sid]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[1].size(1) for x in batch]),
+            dim=0, descending=True)
+
+        max_text_len = max([len(x[0]) for x in batch])
+        max_spec_len = max([x[1].size(1) for x in batch])
+        max_wav_len = max([x[2].size(1) for x in batch])
+
+        text_lengths = torch.LongTensor(len(batch))
+        spec_lengths = torch.LongTensor(len(batch))
+        wav_lengths = torch.LongTensor(len(batch))
+        sid = torch.LongTensor(len(batch))
+
+        text_padded = torch.LongTensor(len(batch), max_text_len)
+        spec_padded = torch.FloatTensor(len(batch), batch[0][1].size(0), max_spec_len)
+        wav_padded = torch.FloatTensor(len(batch), 1, max_wav_len)
+        text_padded.zero_()
+        spec_padded.zero_()
+        wav_padded.zero_()
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            text = row[0]
+            text_padded[i, :text.size(0)] = text
+            text_lengths[i] = text.size(0)
+
+            spec = row[1]
+            spec_padded[i, :, :spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wav = row[2]
+            wav_padded[i, :, :wav.size(1)] = wav
+            wav_lengths[i] = wav.size(1)
+
+            sid[i] = row[3]
+
+        if self.return_ids:
+            return text_padded, text_lengths, spec_padded, spec_lengths, wav_padded, wav_lengths, sid, ids_sorted_decreasing
+        return text_padded, text_lengths, spec_padded, spec_lengths, wav_padded, wav_lengths, sid
+
+
+class DistributedBucketSampler(torch.utils.data.distributed.DistributedSampler):
+    """
+    Maintain similar input lengths in a batch.
+    Length groups are specified by boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any batch is included either {x | b1 < length(x) <=b2} or {x | b2 < length(x) <= b3}.
+
+    It removes samples which are not included in the boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any x s.t. length(x) <= b1 or length(x) > b3 are discarded.
+    """
+
+    def __init__(self, dataset, batch_size, boundaries, num_replicas=None, rank=None, shuffle=True):
+        super().__init__(dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle)
+        self.lengths = dataset.lengths
+        self.batch_size = batch_size
+        self.boundaries = boundaries
+
+        self.buckets, self.num_samples_per_bucket = self._create_buckets()
+        self.total_size = sum(self.num_samples_per_bucket)
+        self.num_samples = self.total_size // self.num_replicas
+
+    def _create_buckets(self):
+        buckets = [[] for _ in range(len(self.boundaries) - 1)]
+        for i in range(len(self.lengths)):
+            length = self.lengths[i]
+            idx_bucket = self._bisect(length)
+            if idx_bucket != -1:
+                buckets[idx_bucket].append(i)
+
+        try: 
+            for i in range(len(buckets) - 1, 0, -1):
+                if len(buckets[i]) == 0:
+                    buckets.pop(i)
+                    self.boundaries.pop(i + 1)
+            assert all(len(bucket) > 0 for bucket in buckets)
+        # When one bucket is not traversed
+        except Exception as e:
+            print('Bucket warning ', e)
+            for i in range(len(buckets) - 1, -1, -1):
+                if len(buckets[i]) == 0:
+                    buckets.pop(i)
+                    self.boundaries.pop(i + 1)
+
+        num_samples_per_bucket = []
+        for i in range(len(buckets)):
+            len_bucket = len(buckets[i])
+            total_batch_size = self.num_replicas * self.batch_size
+            rem = (total_batch_size - (len_bucket % total_batch_size)) % total_batch_size
+            num_samples_per_bucket.append(len_bucket + rem)
+        return buckets, num_samples_per_bucket
+
+    def __iter__(self):
+        # deterministically shuffle based on epoch
+        g = torch.Generator()
+        g.manual_seed(self.epoch)
+
+        indices = []
+        if self.shuffle:
+            for bucket in self.buckets:
+                indices.append(torch.randperm(len(bucket), generator=g).tolist())
+        else:
+            for bucket in self.buckets:
+                indices.append(list(range(len(bucket))))
+
+        batches = []
+        for i in range(len(self.buckets)):
+            bucket = self.buckets[i]
+            len_bucket = len(bucket)
+            ids_bucket = indices[i]
+            num_samples_bucket = self.num_samples_per_bucket[i]
+
+            # add extra samples to make it evenly divisible
+            rem = num_samples_bucket - len_bucket
+            ids_bucket = ids_bucket + ids_bucket * (rem // len_bucket) + ids_bucket[:(rem % len_bucket)]
+
+            # subsample
+            ids_bucket = ids_bucket[self.rank::self.num_replicas]
+
+            # batching
+            for j in range(len(ids_bucket) // self.batch_size):
+                batch = [bucket[idx] for idx in ids_bucket[j * self.batch_size:(j + 1) * self.batch_size]]
+                batches.append(batch)
+
+        if self.shuffle:
+            batch_ids = torch.randperm(len(batches), generator=g).tolist()
+            batches = [batches[i] for i in batch_ids]
+        self.batches = batches
+
+        assert len(self.batches) * self.batch_size == self.num_samples
+        return iter(self.batches)
+
+    def _bisect(self, x, lo=0, hi=None):
+        if hi is None:
+            hi = len(self.boundaries) - 1
+
+        if hi > lo:
+            mid = (hi + lo) // 2
+            if self.boundaries[mid] < x and x <= self.boundaries[mid + 1]:
+                return mid
+            elif x <= self.boundaries[mid]:
+                return self._bisect(x, lo, mid)
+            else:
+                return self._bisect(x, mid + 1, hi)
+        else:
+            return -1
+
+    def __len__(self):
+        return self.num_samples // self.batch_size
diff --git a/final_annotation_train.txt b/final_annotation_train.txt
new file mode 100644
index 0000000000000000000000000000000000000000..538f8147116f606d1e0bf4c2aedafc3b7e7a9067
--- /dev/null
+++ b/final_annotation_train.txt
@@ -0,0 +1,76 @@
+./custom_character_voice/amitaro/processed_0.wav|0|i↑Q↓keN ra↑kUʧaku... ka↑na?
+./custom_character_voice/amitaro/processed_1.wav|0|he↑esuQgo↓oi
+./custom_character_voice/amitaro/processed_2.wav|0|a↑na↓taga i↑naito wa↑taʃi...
+./custom_character_voice/amitaro/processed_3.wav|0|go↑ʧu↓umoNwa o↑ki↓maridesUka?
+./custom_character_voice/amitaro/processed_4.wav|0|d o, do↓o ʃI↑ta↓ra i↓ikana?
+./custom_character_voice/amitaro/processed_5.wav|0|ha↓ai! da↑ijo↓obudesUyoo!
+./custom_character_voice/amitaro/processed_6.wav|0|e↑Qto, tsu↓mari...
+./custom_character_voice/amitaro/processed_7.wav|0|mi↑nasaN↓otsUkaresamadeʃIta
+./custom_character_voice/amitaro/processed_8.wav|0|ba↓QkU ʃi↑maa↓sU o↑ni↓iʧaN, o↑ne↓eʧaN a↑bunai↓kara ha↓naretetene
+./custom_character_voice/amitaro/processed_9.wav|0|da↓Qte a↑Nnani ga↑Nba↓Qte ki↓tanoni
+./custom_character_voice/amitaro/processed_10.wav|0|mi↑gini ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_11.wav|0|a↑Qtsu↓i e↑akoN tsU↑ke↓ruyo
+./custom_character_voice/amitaro/processed_12.wav|0|i↑tadakima↓sU
+./custom_character_voice/amitaro/processed_13.wav|0|a↑reo... ko↑oʃIte... a↑Qʧi↓ga... ko↑o da↓kara...
+./custom_character_voice/amitaro/processed_14.wav|0|i↑QteraQʃaima↓se, go↑ʃu↓jiNsama
+./custom_character_voice/amitaro/processed_16.wav|0|ki↑Nkyuu ʃa↑ryooga ʧi↓kakuni i↑ruyo
+./custom_character_voice/amitaro/processed_17.wav|0|ko↓Ndokoso de↑ki↓ruyo
+./custom_character_voice/amitaro/processed_18.wav|0|ha↓ai, do↓ozoo
+./custom_character_voice/amitaro/processed_19.wav|0|ma↑ʧiga↓Qte i↑ru no↑wa do↓reda?
+./custom_character_voice/amitaro/processed_20.wav|0|a↑buna↓kaQta
+./custom_character_voice/amitaro/processed_21.wav|0|yo↑N↓meesama go↑ra↓iteN
+./custom_character_voice/amitaro/processed_22.wav|0|mi↑ʧino e↓kiga a↓ruyo, kyu↑ukee ʃi↑mase↓Nka?
+./custom_character_voice/amitaro/processed_23.wav|0|do↓nataka i↑raQʃaimase↓Nka?
+./custom_character_voice/amitaro/processed_24.wav|0|ta↑maniwa ka↑ma↓Qtehoʃiinaa
+./custom_character_voice/amitaro/processed_25.wav|0|i↑Ntaane↓Qtoni tsu↑nagarimase↓N
+./custom_character_voice/amitaro/processed_26.wav|0|da↑ijo↓obudayo sa↑iʃokara u↑ma↓ku i↑ku↓niNnaNte i↑nai N↓dakara
+./custom_character_voice/amitaro/processed_27.wav|0|ha↓ai! hi↑ra↓itemasUyoo!
+./custom_character_voice/amitaro/processed_28.wav|0|ku↑rumaga ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_29.wav|0|ko↑harune a↓mi u↑taima↓sU
+./custom_character_voice/amitaro/processed_30.wav|0|o↑yoso ni↑hyakumeetorusakio hi↑dariho↓okoodesU.
+./custom_character_voice/amitaro/processed_31.wav|0|ga↑Nbarisugiwa yo↓kunaidesUyo
+./custom_character_voice/amitaro/processed_32.wav|0|ja↓NkeN po↓N!
+./custom_character_voice/amitaro/processed_33.wav|0|tsu↑gi↓no na↓kakara ma↑ʧiga↓Qte i↑ru mo↑no↓o e↑ra↓Ndene
+./custom_character_voice/amitaro/processed_34.wav|0|go↑meNnasa↓ai
+./custom_character_voice/amitaro/processed_35.wav|0|ko↓eno so↑zaio tsU↑ku↓Qta hI↑to↓ami ta↓roo
+./custom_character_voice/amitaro/processed_36.wav|0|hi↑do↓iyo o
+./custom_character_voice/amitaro/processed_37.wav|0|hi↑darini ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_38.wav|0|ga↑Nba↓ru no↑mo ho↑dohodoni ʃI↑te ku↑dasa↓ine
+./custom_character_voice/amitaro/processed_39.wav|0|i↑kIka↓eruu...
+./custom_character_voice/amitaro/processed_40.wav|0|ki↑doo ʃi↑ma↓ʃIta kyo↓omo a↑NzeN u↑NteNyoroʃIkuonegaiʃimasU
+./custom_character_voice/amitaro/processed_41.wav|0|kyo↓owa do↓koe i↑kima↓sUka?
+./custom_character_voice/amitaro/processed_42.wav|0|a↑soNde ku↑rete a↑ri↓gatoo
+./custom_character_voice/amitaro/processed_43.wav|0|ko↑rede to↑dome↓da a
+./custom_character_voice/amitaro/processed_44.wav|0|ko↑no ma↑ma↓ja ya↑rareʧau↓kamo
+./custom_character_voice/amitaro/processed_45.wav|0|ko↑N na↑noQte↓naiyo
+./custom_character_voice/amitaro/processed_46.wav|0|ko↑no o↓Nseewa, a↑mi↓tarono ko↑esozaiko↓obooga o↑to↓doke ʃi↑ma↓ʃIta.
+./custom_character_voice/amitaro/processed_47.wav|0|do↓nataka i↑raQʃaima↓sUka?
+./custom_character_voice/amitaro/processed_48.wav|0|go↑ʧu↓umoNwa i↓joode yo↑roʃi↓idesUka?
+./custom_character_voice/amitaro/processed_49.wav|0|go↑ʧIsoosamade↓ʃIta
+./custom_character_voice/amitaro/processed_50.wav|0|ha↓ai, ʧu↑umokuu!
+./custom_character_voice/amitaro/processed_51.wav|0|a, o↑koQte↓ru?
+./custom_character_voice/amitaro/processed_52.wav|0|ko↑no a↓taride ʧo↓Qto kyu↑ukee ʃi↑mase↓Nka?
+./custom_character_voice/amitaro/processed_53.wav|0|a↑kirame↓naide mo↓o i↑Q↓kai ya↓Qte mi↓yoo! ne↓Q!
+./custom_character_voice/amitaro/processed_54.wav|0|ha↓yakuokIte
+./custom_character_voice/amitaro/processed_55.wav|0|a↑rane
+./custom_character_voice/amitaro/processed_56.wav|0|de↓mo de↓mo da↑ijo↓obudayo ko↑rekara na↑N↓dodaQte ʧo↑oseN su↑re↓ba i↓i N↓dakara
+./custom_character_voice/amitaro/processed_57.wav|0|ko↑no na↓kadato...
+./custom_character_voice/amitaro/processed_58.wav|0|da↓Qte, a↑Nnani ga↑Nba↓Qtajanai
+./custom_character_voice/amitaro/processed_59.wav|0|sU↑ko↓ʃidake kyu↑ukee ʃi↑mase↓Nka
+./custom_character_voice/amitaro/processed_60.wav|0|ko↑remo ku↑rae!
+./custom_character_voice/amitaro/processed_61.wav|0|e↑Qto, da↓kara...
+./custom_character_voice/amitaro/processed_62.wav|0|go↑meN, o↑kora↓naide
+./custom_character_voice/amitaro/processed_63.wav|0|ka↓NbeN ʃI↑teyo
+./custom_character_voice/amitaro/processed_64.wav|0|mo↓o i↑jiwa↓ru
+./custom_character_voice/amitaro/processed_65.wav|0|do↓okanaa?
+./custom_character_voice/amitaro/processed_66.wav|0|ko↑no yo↓ona ke↑Qkani na↑rima↓ʃIta
+./custom_character_voice/amitaro/processed_67.wav|0|ko↓NnaNde i↓i no↑kanaa
+./custom_character_voice/amitaro/processed_68.wav|0|u↓N, ha↑ji↓metenanoni jo↑odekidayo
+./custom_character_voice/amitaro/processed_69.wav|0|d o, do↓o ʃi↑yoo...
+./custom_character_voice/amitaro/processed_70.wav|0|sa↑N, n i, i↑ʧi, ze↓ro
+./custom_character_voice/amitaro/processed_71.wav|0|a, a↑re? mo↓o o↑wari?
+./custom_character_voice/amitaro/processed_72.wav|0|a↓kino ko↑otsuu a↑NzeN u↑Ndooʃu↓ukaNdesU
+./custom_character_voice/amitaro/processed_73.wav|0|so↓rosoro ho↑Ntooni ya↑su↓Nde ku↑dasa↓i
+./custom_character_voice/amitaro/processed_74.wav|0|wa↑wawawawawawa!
+./custom_character_voice/amitaro/processed_75.wav|0|a↑Nmari mu↑zukaʃIkukaNgaesugi↓ruto i↑roiro ta↑iheNdaʃine ʃi↑Qka↓ri ha↑Nsee ʃI↑ta↓ra pa↑pa↓Qto tsu↑gi i↑koo
+./custom_character_voice/amitaro/processed_76.wav|0|da↓kara ko↑rega ko↓ude ko↑oyuu ko↑to↓dayone
diff --git a/final_annotation_val.txt b/final_annotation_val.txt
new file mode 100644
index 0000000000000000000000000000000000000000..538f8147116f606d1e0bf4c2aedafc3b7e7a9067
--- /dev/null
+++ b/final_annotation_val.txt
@@ -0,0 +1,76 @@
+./custom_character_voice/amitaro/processed_0.wav|0|i↑Q↓keN ra↑kUʧaku... ka↑na?
+./custom_character_voice/amitaro/processed_1.wav|0|he↑esuQgo↓oi
+./custom_character_voice/amitaro/processed_2.wav|0|a↑na↓taga i↑naito wa↑taʃi...
+./custom_character_voice/amitaro/processed_3.wav|0|go↑ʧu↓umoNwa o↑ki↓maridesUka?
+./custom_character_voice/amitaro/processed_4.wav|0|d o, do↓o ʃI↑ta↓ra i↓ikana?
+./custom_character_voice/amitaro/processed_5.wav|0|ha↓ai! da↑ijo↓obudesUyoo!
+./custom_character_voice/amitaro/processed_6.wav|0|e↑Qto, tsu↓mari...
+./custom_character_voice/amitaro/processed_7.wav|0|mi↑nasaN↓otsUkaresamadeʃIta
+./custom_character_voice/amitaro/processed_8.wav|0|ba↓QkU ʃi↑maa↓sU o↑ni↓iʧaN, o↑ne↓eʧaN a↑bunai↓kara ha↓naretetene
+./custom_character_voice/amitaro/processed_9.wav|0|da↓Qte a↑Nnani ga↑Nba↓Qte ki↓tanoni
+./custom_character_voice/amitaro/processed_10.wav|0|mi↑gini ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_11.wav|0|a↑Qtsu↓i e↑akoN tsU↑ke↓ruyo
+./custom_character_voice/amitaro/processed_12.wav|0|i↑tadakima↓sU
+./custom_character_voice/amitaro/processed_13.wav|0|a↑reo... ko↑oʃIte... a↑Qʧi↓ga... ko↑o da↓kara...
+./custom_character_voice/amitaro/processed_14.wav|0|i↑QteraQʃaima↓se, go↑ʃu↓jiNsama
+./custom_character_voice/amitaro/processed_16.wav|0|ki↑Nkyuu ʃa↑ryooga ʧi↓kakuni i↑ruyo
+./custom_character_voice/amitaro/processed_17.wav|0|ko↓Ndokoso de↑ki↓ruyo
+./custom_character_voice/amitaro/processed_18.wav|0|ha↓ai, do↓ozoo
+./custom_character_voice/amitaro/processed_19.wav|0|ma↑ʧiga↓Qte i↑ru no↑wa do↓reda?
+./custom_character_voice/amitaro/processed_20.wav|0|a↑buna↓kaQta
+./custom_character_voice/amitaro/processed_21.wav|0|yo↑N↓meesama go↑ra↓iteN
+./custom_character_voice/amitaro/processed_22.wav|0|mi↑ʧino e↓kiga a↓ruyo, kyu↑ukee ʃi↑mase↓Nka?
+./custom_character_voice/amitaro/processed_23.wav|0|do↓nataka i↑raQʃaimase↓Nka?
+./custom_character_voice/amitaro/processed_24.wav|0|ta↑maniwa ka↑ma↓Qtehoʃiinaa
+./custom_character_voice/amitaro/processed_25.wav|0|i↑Ntaane↓Qtoni tsu↑nagarimase↓N
+./custom_character_voice/amitaro/processed_26.wav|0|da↑ijo↓obudayo sa↑iʃokara u↑ma↓ku i↑ku↓niNnaNte i↑nai N↓dakara
+./custom_character_voice/amitaro/processed_27.wav|0|ha↓ai! hi↑ra↓itemasUyoo!
+./custom_character_voice/amitaro/processed_28.wav|0|ku↑rumaga ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_29.wav|0|ko↑harune a↓mi u↑taima↓sU
+./custom_character_voice/amitaro/processed_30.wav|0|o↑yoso ni↑hyakumeetorusakio hi↑dariho↓okoodesU.
+./custom_character_voice/amitaro/processed_31.wav|0|ga↑Nbarisugiwa yo↓kunaidesUyo
+./custom_character_voice/amitaro/processed_32.wav|0|ja↓NkeN po↓N!
+./custom_character_voice/amitaro/processed_33.wav|0|tsu↑gi↓no na↓kakara ma↑ʧiga↓Qte i↑ru mo↑no↓o e↑ra↓Ndene
+./custom_character_voice/amitaro/processed_34.wav|0|go↑meNnasa↓ai
+./custom_character_voice/amitaro/processed_35.wav|0|ko↓eno so↑zaio tsU↑ku↓Qta hI↑to↓ami ta↓roo
+./custom_character_voice/amitaro/processed_36.wav|0|hi↑do↓iyo o
+./custom_character_voice/amitaro/processed_37.wav|0|hi↑darini ma↑garima↓sU. go↑ʧu↓ui ku↑dasa↓i.
+./custom_character_voice/amitaro/processed_38.wav|0|ga↑Nba↓ru no↑mo ho↑dohodoni ʃI↑te ku↑dasa↓ine
+./custom_character_voice/amitaro/processed_39.wav|0|i↑kIka↓eruu...
+./custom_character_voice/amitaro/processed_40.wav|0|ki↑doo ʃi↑ma↓ʃIta kyo↓omo a↑NzeN u↑NteNyoroʃIkuonegaiʃimasU
+./custom_character_voice/amitaro/processed_41.wav|0|kyo↓owa do↓koe i↑kima↓sUka?
+./custom_character_voice/amitaro/processed_42.wav|0|a↑soNde ku↑rete a↑ri↓gatoo
+./custom_character_voice/amitaro/processed_43.wav|0|ko↑rede to↑dome↓da a
+./custom_character_voice/amitaro/processed_44.wav|0|ko↑no ma↑ma↓ja ya↑rareʧau↓kamo
+./custom_character_voice/amitaro/processed_45.wav|0|ko↑N na↑noQte↓naiyo
+./custom_character_voice/amitaro/processed_46.wav|0|ko↑no o↓Nseewa, a↑mi↓tarono ko↑esozaiko↓obooga o↑to↓doke ʃi↑ma↓ʃIta.
+./custom_character_voice/amitaro/processed_47.wav|0|do↓nataka i↑raQʃaima↓sUka?
+./custom_character_voice/amitaro/processed_48.wav|0|go↑ʧu↓umoNwa i↓joode yo↑roʃi↓idesUka?
+./custom_character_voice/amitaro/processed_49.wav|0|go↑ʧIsoosamade↓ʃIta
+./custom_character_voice/amitaro/processed_50.wav|0|ha↓ai, ʧu↑umokuu!
+./custom_character_voice/amitaro/processed_51.wav|0|a, o↑koQte↓ru?
+./custom_character_voice/amitaro/processed_52.wav|0|ko↑no a↓taride ʧo↓Qto kyu↑ukee ʃi↑mase↓Nka?
+./custom_character_voice/amitaro/processed_53.wav|0|a↑kirame↓naide mo↓o i↑Q↓kai ya↓Qte mi↓yoo! ne↓Q!
+./custom_character_voice/amitaro/processed_54.wav|0|ha↓yakuokIte
+./custom_character_voice/amitaro/processed_55.wav|0|a↑rane
+./custom_character_voice/amitaro/processed_56.wav|0|de↓mo de↓mo da↑ijo↓obudayo ko↑rekara na↑N↓dodaQte ʧo↑oseN su↑re↓ba i↓i N↓dakara
+./custom_character_voice/amitaro/processed_57.wav|0|ko↑no na↓kadato...
+./custom_character_voice/amitaro/processed_58.wav|0|da↓Qte, a↑Nnani ga↑Nba↓Qtajanai
+./custom_character_voice/amitaro/processed_59.wav|0|sU↑ko↓ʃidake kyu↑ukee ʃi↑mase↓Nka
+./custom_character_voice/amitaro/processed_60.wav|0|ko↑remo ku↑rae!
+./custom_character_voice/amitaro/processed_61.wav|0|e↑Qto, da↓kara...
+./custom_character_voice/amitaro/processed_62.wav|0|go↑meN, o↑kora↓naide
+./custom_character_voice/amitaro/processed_63.wav|0|ka↓NbeN ʃI↑teyo
+./custom_character_voice/amitaro/processed_64.wav|0|mo↓o i↑jiwa↓ru
+./custom_character_voice/amitaro/processed_65.wav|0|do↓okanaa?
+./custom_character_voice/amitaro/processed_66.wav|0|ko↑no yo↓ona ke↑Qkani na↑rima↓ʃIta
+./custom_character_voice/amitaro/processed_67.wav|0|ko↓NnaNde i↓i no↑kanaa
+./custom_character_voice/amitaro/processed_68.wav|0|u↓N, ha↑ji↓metenanoni jo↑odekidayo
+./custom_character_voice/amitaro/processed_69.wav|0|d o, do↓o ʃi↑yoo...
+./custom_character_voice/amitaro/processed_70.wav|0|sa↑N, n i, i↑ʧi, ze↓ro
+./custom_character_voice/amitaro/processed_71.wav|0|a, a↑re? mo↓o o↑wari?
+./custom_character_voice/amitaro/processed_72.wav|0|a↓kino ko↑otsuu a↑NzeN u↑Ndooʃu↓ukaNdesU
+./custom_character_voice/amitaro/processed_73.wav|0|so↓rosoro ho↑Ntooni ya↑su↓Nde ku↑dasa↓i
+./custom_character_voice/amitaro/processed_74.wav|0|wa↑wawawawawawa!
+./custom_character_voice/amitaro/processed_75.wav|0|a↑Nmari mu↑zukaʃIkukaNgaesugi↓ruto i↑roiro ta↑iheNdaʃine ʃi↑Qka↓ri ha↑Nsee ʃI↑ta↓ra pa↑pa↓Qto tsu↑gi i↑koo
+./custom_character_voice/amitaro/processed_76.wav|0|da↓kara ko↑rega ko↓ude ko↑oyuu ko↑to↓dayone
diff --git a/finetune_speaker_v2.py b/finetune_speaker_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..5fc4fd85fc2d03aa412f0c3681070fcbbd655a9f
--- /dev/null
+++ b/finetune_speaker_v2.py
@@ -0,0 +1,351 @@
+import os
+import json
+import argparse
+import itertools
+import math
+import torch
+from torch import nn, optim
+from torch.nn import functional as F
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+import torch.multiprocessing as mp
+import torch.distributed as dist
+from torch.nn.parallel import DistributedDataParallel as DDP
+from torch.cuda.amp import autocast, GradScaler
+from tqdm import tqdm
+
+import librosa
+import logging
+
+logging.getLogger('numba').setLevel(logging.WARNING)
+
+import commons
+import utils
+from data_utils import (
+  TextAudioSpeakerLoader,
+  TextAudioSpeakerCollate,
+  DistributedBucketSampler
+)
+from models import (
+  SynthesizerTrn,
+  MultiPeriodDiscriminator,
+)
+from losses import (
+  generator_loss,
+  discriminator_loss,
+  feature_loss,
+  kl_loss
+)
+from mel_processing import mel_spectrogram_torch, spec_to_mel_torch
+
+
+torch.backends.cudnn.benchmark = True
+global_step = 0
+
+
+def main():
+  """Assume Single Node Multi GPUs Training Only"""
+  assert torch.cuda.is_available(), "CPU training is not allowed."
+
+  n_gpus = torch.cuda.device_count()
+  os.environ['MASTER_ADDR'] = 'localhost'
+  os.environ['MASTER_PORT'] = '8000'
+
+  hps = utils.get_hparams()
+  mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,))
+
+
+def run(rank, n_gpus, hps):
+  global global_step
+  symbols = hps['symbols']
+  if rank == 0:
+    logger = utils.get_logger(hps.model_dir)
+    logger.info(hps)
+    utils.check_git_hash(hps.model_dir)
+    writer = SummaryWriter(log_dir=hps.model_dir)
+    writer_eval = SummaryWriter(log_dir=os.path.join(hps.model_dir, "eval"))
+
+  # Use gloo backend on Windows for Pytorch
+  dist.init_process_group(backend=  'gloo' if os.name == 'nt' else 'nccl', init_method='env://', world_size=n_gpus, rank=rank)
+  torch.manual_seed(hps.train.seed)
+  torch.cuda.set_device(rank)
+
+  train_dataset = TextAudioSpeakerLoader(hps.data.training_files, hps.data, symbols)
+  train_sampler = DistributedBucketSampler(
+      train_dataset,
+      hps.train.batch_size,
+      [32,300,400,500,600,700,800,900,1000],
+      num_replicas=n_gpus,
+      rank=rank,
+      shuffle=True)
+  collate_fn = TextAudioSpeakerCollate()
+  train_loader = DataLoader(train_dataset, num_workers=2, shuffle=False, pin_memory=True,
+      collate_fn=collate_fn, batch_sampler=train_sampler)
+  # train_loader = DataLoader(train_dataset, batch_size=hps.train.batch_size, num_workers=2, shuffle=False, pin_memory=True,
+  #                           collate_fn=collate_fn)
+  if rank == 0:
+    eval_dataset = TextAudioSpeakerLoader(hps.data.validation_files, hps.data, symbols)
+    eval_loader = DataLoader(eval_dataset, num_workers=0, shuffle=False,
+        batch_size=hps.train.batch_size, pin_memory=True,
+        drop_last=False, collate_fn=collate_fn)
+
+  net_g = SynthesizerTrn(
+      len(symbols),
+      hps.data.filter_length // 2 + 1,
+      hps.train.segment_size // hps.data.hop_length,
+      n_speakers=hps.data.n_speakers,
+      **hps.model).cuda(rank)
+  net_d = MultiPeriodDiscriminator(hps.model.use_spectral_norm).cuda(rank)
+
+  # load existing model
+  if hps.cont:
+      try:
+          _, _, _, epoch_str = utils.load_checkpoint(utils.latest_checkpoint_path(hps.model_dir, "G_latest.pth"), net_g, None)
+          _, _, _, epoch_str = utils.load_checkpoint(utils.latest_checkpoint_path(hps.model_dir, "D_latest.pth"), net_d, None)
+          global_step = (epoch_str - 1) * len(train_loader)
+      except:
+          print("Failed to find latest checkpoint, loading G_0.pth...")
+          if hps.train_with_pretrained_model:
+              print("Train with pretrained model...")
+              _, _, _, epoch_str = utils.load_checkpoint("./pretrained_models/G_0.pth", net_g, None)
+              _, _, _, epoch_str = utils.load_checkpoint("./pretrained_models/D_0.pth", net_d, None)
+          else:
+              print("Train without pretrained model...")
+          epoch_str = 1
+          global_step = 0
+  else:
+      if hps.train_with_pretrained_model:
+          print("Train with pretrained model...")
+          _, _, _, epoch_str = utils.load_checkpoint("./pretrained_models/G_0.pth", net_g, None)
+          _, _, _, epoch_str = utils.load_checkpoint("./pretrained_models/D_0.pth", net_d, None)
+      else:
+          print("Train without pretrained model...")
+      epoch_str = 1
+      global_step = 0
+  # freeze all other layers except speaker embedding
+  for p in net_g.parameters():
+      p.requires_grad = True
+  for p in net_d.parameters():
+      p.requires_grad = True
+  # for p in net_d.parameters():
+  #     p.requires_grad = False
+  # net_g.emb_g.weight.requires_grad = True
+  optim_g = torch.optim.AdamW(
+      net_g.parameters(),
+      hps.train.learning_rate,
+      betas=hps.train.betas,
+      eps=hps.train.eps)
+  optim_d = torch.optim.AdamW(
+      net_d.parameters(),
+      hps.train.learning_rate,
+      betas=hps.train.betas,
+      eps=hps.train.eps)
+  # optim_d = None
+  net_g = DDP(net_g, device_ids=[rank])
+  net_d = DDP(net_d, device_ids=[rank])
+
+  scheduler_g = torch.optim.lr_scheduler.ExponentialLR(optim_g, gamma=hps.train.lr_decay)
+  scheduler_d = torch.optim.lr_scheduler.ExponentialLR(optim_d, gamma=hps.train.lr_decay)
+
+  scaler = GradScaler(enabled=hps.train.fp16_run)
+
+  for epoch in range(epoch_str, hps.train.epochs + 1):
+    if rank==0:
+      train_and_evaluate(rank, epoch, hps, [net_g, net_d], [optim_g, optim_d], [scheduler_g, scheduler_d], scaler, [train_loader, eval_loader], logger, [writer, writer_eval])
+    else:
+      train_and_evaluate(rank, epoch, hps, [net_g, net_d], [optim_g, optim_d], [scheduler_g, scheduler_d], scaler, [train_loader, None], None, None)
+    scheduler_g.step()
+    scheduler_d.step()
+
+
+def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loaders, logger, writers):
+  net_g, net_d = nets
+  optim_g, optim_d = optims
+  scheduler_g, scheduler_d = schedulers
+  train_loader, eval_loader = loaders
+  if writers is not None:
+    writer, writer_eval = writers
+
+  # train_loader.batch_sampler.set_epoch(epoch)
+  global global_step
+
+  net_g.train()
+  net_d.train()
+  for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers) in enumerate(tqdm(train_loader)):
+    x, x_lengths = x.cuda(rank, non_blocking=True), x_lengths.cuda(rank, non_blocking=True)
+    spec, spec_lengths = spec.cuda(rank, non_blocking=True), spec_lengths.cuda(rank, non_blocking=True)
+    y, y_lengths = y.cuda(rank, non_blocking=True), y_lengths.cuda(rank, non_blocking=True)
+    speakers = speakers.cuda(rank, non_blocking=True)
+
+    with autocast(enabled=hps.train.fp16_run):
+      y_hat, l_length, attn, ids_slice, x_mask, z_mask,\
+      (z, z_p, m_p, logs_p, m_q, logs_q) = net_g(x, x_lengths, spec, spec_lengths, speakers)
+
+      mel = spec_to_mel_torch(
+          spec,
+          hps.data.filter_length,
+          hps.data.n_mel_channels,
+          hps.data.sampling_rate,
+          hps.data.mel_fmin,
+          hps.data.mel_fmax)
+      y_mel = commons.slice_segments(mel, ids_slice, hps.train.segment_size // hps.data.hop_length)
+      y_hat_mel = mel_spectrogram_torch(
+          y_hat.squeeze(1),
+          hps.data.filter_length,
+          hps.data.n_mel_channels,
+          hps.data.sampling_rate,
+          hps.data.hop_length,
+          hps.data.win_length,
+          hps.data.mel_fmin,
+          hps.data.mel_fmax
+      )
+
+      y = commons.slice_segments(y, ids_slice * hps.data.hop_length, hps.train.segment_size) # slice
+
+      # Discriminator
+      y_d_hat_r, y_d_hat_g, _, _ = net_d(y, y_hat.detach())
+      with autocast(enabled=False):
+        loss_disc, losses_disc_r, losses_disc_g = discriminator_loss(y_d_hat_r, y_d_hat_g)
+        loss_disc_all = loss_disc
+    optim_d.zero_grad()
+    scaler.scale(loss_disc_all).backward()
+    scaler.unscale_(optim_d)
+    grad_norm_d = commons.clip_grad_value_(net_d.parameters(), None)
+    scaler.step(optim_d)
+
+    with autocast(enabled=hps.train.fp16_run):
+      # Generator
+      y_d_hat_r, y_d_hat_g, fmap_r, fmap_g = net_d(y, y_hat)
+      with autocast(enabled=False):
+        loss_dur = torch.sum(l_length.float())
+        loss_mel = F.l1_loss(y_mel, y_hat_mel) * hps.train.c_mel
+        loss_kl = kl_loss(z_p, logs_q, m_p, logs_p, z_mask) * hps.train.c_kl
+
+        loss_fm = feature_loss(fmap_r, fmap_g)
+        loss_gen, losses_gen = generator_loss(y_d_hat_g)
+        loss_gen_all = loss_gen + loss_fm + loss_mel + loss_dur + loss_kl
+    optim_g.zero_grad()
+    scaler.scale(loss_gen_all).backward()
+    scaler.unscale_(optim_g)
+    grad_norm_g = commons.clip_grad_value_(net_g.parameters(), None)
+    scaler.step(optim_g)
+    scaler.update()
+
+    if rank==0:
+      if global_step % hps.train.log_interval == 0:
+        lr = optim_g.param_groups[0]['lr']
+        losses = [loss_disc, loss_gen, loss_fm, loss_mel, loss_dur, loss_kl]
+        logger.info('Train Epoch: {} [{:.0f}%]'.format(
+          epoch,
+          100. * batch_idx / len(train_loader)))
+        logger.info([x.item() for x in losses] + [global_step, lr])
+
+        scalar_dict = {"loss/g/total": loss_gen_all, "loss/d/total": loss_disc_all, "learning_rate": lr, "grad_norm_g": grad_norm_g}
+        scalar_dict.update({"loss/g/fm": loss_fm, "loss/g/mel": loss_mel, "loss/g/dur": loss_dur, "loss/g/kl": loss_kl})
+
+        scalar_dict.update({"loss/g/{}".format(i): v for i, v in enumerate(losses_gen)})
+        scalar_dict.update({"loss/d_r/{}".format(i): v for i, v in enumerate(losses_disc_r)})
+        scalar_dict.update({"loss/d_g/{}".format(i): v for i, v in enumerate(losses_disc_g)})
+        image_dict = {
+            "slice/mel_org": utils.plot_spectrogram_to_numpy(y_mel[0].data.cpu().numpy()),
+            "slice/mel_gen": utils.plot_spectrogram_to_numpy(y_hat_mel[0].data.cpu().numpy()),
+            "all/mel": utils.plot_spectrogram_to_numpy(mel[0].data.cpu().numpy()),
+            "all/attn": utils.plot_alignment_to_numpy(attn[0,0].data.cpu().numpy())
+        }
+        utils.summarize(
+          writer=writer,
+          global_step=global_step,
+          images=image_dict,
+          scalars=scalar_dict)
+
+      if global_step % hps.train.eval_interval == 0:
+        evaluate(hps, net_g, eval_loader, writer_eval)
+        
+        utils.save_checkpoint(net_g, None, hps.train.learning_rate, epoch,
+                              os.path.join(hps.model_dir, "G_latest.pth".format(global_step)))
+        
+        utils.save_checkpoint(net_d, None, hps.train.learning_rate, epoch,
+                              os.path.join(hps.model_dir, "D_latest.pth".format(global_step)))
+        if hps.preserved > 0:
+          utils.save_checkpoint(net_g, None, hps.train.learning_rate, epoch,
+                                  os.path.join(hps.model_dir, "G_{}.pth".format(global_step)))
+          utils.save_checkpoint(net_d, None, hps.train.learning_rate, epoch,
+                                  os.path.join(hps.model_dir, "D_{}.pth".format(global_step)))
+          old_g = utils.oldest_checkpoint_path(hps.model_dir, "G_[0-9]*.pth",
+                                               preserved=hps.preserved)  # Preserve 4 (default) historical checkpoints.
+          old_d = utils.oldest_checkpoint_path(hps.model_dir, "D_[0-9]*.pth", preserved=hps.preserved)
+          if os.path.exists(old_g):
+            print(f"remove {old_g}")
+            os.remove(old_g)
+          if os.path.exists(old_d):
+            print(f"remove {old_d}")
+            os.remove(old_d)
+    global_step += 1
+    if epoch > hps.max_epochs:
+        print("Maximum epoch reached, closing training...")
+        exit()
+
+  if rank == 0:
+    logger.info('====> Epoch: {}'.format(epoch))
+
+
+def evaluate(hps, generator, eval_loader, writer_eval):
+    generator.eval()
+    with torch.no_grad():
+      for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers) in enumerate(eval_loader):
+        x, x_lengths = x.cuda(0), x_lengths.cuda(0)
+        spec, spec_lengths = spec.cuda(0), spec_lengths.cuda(0)
+        y, y_lengths = y.cuda(0), y_lengths.cuda(0)
+        speakers = speakers.cuda(0)
+
+        # remove else
+        x = x[:1]
+        x_lengths = x_lengths[:1]
+        spec = spec[:1]
+        spec_lengths = spec_lengths[:1]
+        y = y[:1]
+        y_lengths = y_lengths[:1]
+        speakers = speakers[:1]
+        break
+      y_hat, attn, mask, *_ = generator.module.infer(x, x_lengths, speakers, max_len=1000)
+      y_hat_lengths = mask.sum([1,2]).long() * hps.data.hop_length
+
+      mel = spec_to_mel_torch(
+        spec,
+        hps.data.filter_length,
+        hps.data.n_mel_channels,
+        hps.data.sampling_rate,
+        hps.data.mel_fmin,
+        hps.data.mel_fmax)
+      y_hat_mel = mel_spectrogram_torch(
+        y_hat.squeeze(1).float(),
+        hps.data.filter_length,
+        hps.data.n_mel_channels,
+        hps.data.sampling_rate,
+        hps.data.hop_length,
+        hps.data.win_length,
+        hps.data.mel_fmin,
+        hps.data.mel_fmax
+      )
+    image_dict = {
+      "gen/mel": utils.plot_spectrogram_to_numpy(y_hat_mel[0].cpu().numpy())
+    }
+    audio_dict = {
+      "gen/audio": y_hat[0,:,:y_hat_lengths[0]]
+    }
+    if global_step == 0:
+      image_dict.update({"gt/mel": utils.plot_spectrogram_to_numpy(mel[0].cpu().numpy())})
+      audio_dict.update({"gt/audio": y[0,:,:y_lengths[0]]})
+
+    utils.summarize(
+      writer=writer_eval,
+      global_step=global_step,
+      images=image_dict,
+      audios=audio_dict,
+      audio_sampling_rate=hps.data.sampling_rate
+    )
+    generator.train()
+
+
+if __name__ == "__main__":
+  main()
diff --git a/losses.py b/losses.py
new file mode 100644
index 0000000000000000000000000000000000000000..c5d410ea5f3c25175f2d848b7b7d779b93f91b9d
--- /dev/null
+++ b/losses.py
@@ -0,0 +1,61 @@
+import torch 
+from torch.nn import functional as F
+
+import commons
+
+
+def feature_loss(fmap_r, fmap_g):
+  loss = 0
+  for dr, dg in zip(fmap_r, fmap_g):
+    for rl, gl in zip(dr, dg):
+      rl = rl.float().detach()
+      gl = gl.float()
+      loss += torch.mean(torch.abs(rl - gl))
+
+  return loss * 2 
+
+
+def discriminator_loss(disc_real_outputs, disc_generated_outputs):
+  loss = 0
+  r_losses = []
+  g_losses = []
+  for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
+    dr = dr.float()
+    dg = dg.float()
+    r_loss = torch.mean((1-dr)**2)
+    g_loss = torch.mean(dg**2)
+    loss += (r_loss + g_loss)
+    r_losses.append(r_loss.item())
+    g_losses.append(g_loss.item())
+
+  return loss, r_losses, g_losses
+
+
+def generator_loss(disc_outputs):
+  loss = 0
+  gen_losses = []
+  for dg in disc_outputs:
+    dg = dg.float()
+    l = torch.mean((1-dg)**2)
+    gen_losses.append(l)
+    loss += l
+
+  return loss, gen_losses
+
+
+def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
+  """
+  z_p, logs_q: [b, h, t_t]
+  m_p, logs_p: [b, h, t_t]
+  """
+  z_p = z_p.float()
+  logs_q = logs_q.float()
+  m_p = m_p.float()
+  logs_p = logs_p.float()
+  z_mask = z_mask.float()
+
+  kl = logs_p - logs_q - 0.5
+  kl += 0.5 * ((z_p - m_p)**2) * torch.exp(-2. * logs_p)
+  kl = torch.sum(kl * z_mask)
+  l = kl / torch.sum(z_mask)
+  return l
diff --git a/mel_processing.py b/mel_processing.py
new file mode 100644
index 0000000000000000000000000000000000000000..2607b77d30e319ddb7f6e5788d40ce3ccaf6b015
--- /dev/null
+++ b/mel_processing.py
@@ -0,0 +1,112 @@
+import math
+import os
+import random
+import torch
+from torch import nn
+import torch.nn.functional as F
+import torch.utils.data
+import numpy as np
+import librosa
+import librosa.util as librosa_util
+from librosa.util import normalize, pad_center, tiny
+from scipy.signal import get_window
+from scipy.io.wavfile import read
+from librosa.filters import mel as librosa_mel_fn
+
+MAX_WAV_VALUE = 32768.0
+
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+    """
+    PARAMS
+    ------
+    C: compression factor
+    """
+    return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def dynamic_range_decompression_torch(x, C=1):
+    """
+    PARAMS
+    ------
+    C: compression factor used to compress
+    """
+    return torch.exp(x) / C
+
+
+def spectral_normalize_torch(magnitudes):
+    output = dynamic_range_compression_torch(magnitudes)
+    return output
+
+
+def spectral_de_normalize_torch(magnitudes):
+    output = dynamic_range_decompression_torch(magnitudes)
+    return output
+
+
+mel_basis = {}
+hann_window = {}
+
+
+def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+
+    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+                      center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=False)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+    return spec
+
+
+def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
+    global mel_basis
+    dtype_device = str(spec.dtype) + '_' + str(spec.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=spec.dtype, device=spec.device)
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+    return spec
+
+
+def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global mel_basis, hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+
+    spec = torch.stft(y.float(), n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+        center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=False)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+
+    return spec
diff --git a/models.py b/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..23f7a0fff77d011954fe5958066da2715799c14c
--- /dev/null
+++ b/models.py
@@ -0,0 +1,533 @@
+import copy
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+import commons
+import modules
+import attentions
+import monotonic_align
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from commons import init_weights, get_padding
+
+
+class StochasticDurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, n_flows=4, gin_channels=0):
+    super().__init__()
+    filter_channels = in_channels # it needs to be removed from future version.
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.log_flow = modules.Log()
+    self.flows = nn.ModuleList()
+    self.flows.append(modules.ElementwiseAffine(2))
+    for i in range(n_flows):
+      self.flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.flows.append(modules.Flip())
+
+    self.post_pre = nn.Conv1d(1, filter_channels, 1)
+    self.post_proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.post_convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    self.post_flows = nn.ModuleList()
+    self.post_flows.append(modules.ElementwiseAffine(2))
+    for i in range(4):
+      self.post_flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.post_flows.append(modules.Flip())
+
+    self.pre = nn.Conv1d(in_channels, filter_channels, 1)
+    self.proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, filter_channels, 1)
+
+  def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scale=1.0):
+    x = torch.detach(x)
+    x = self.pre(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.convs(x, x_mask)
+    x = self.proj(x) * x_mask
+
+    if not reverse:
+      flows = self.flows
+      assert w is not None
+
+      logdet_tot_q = 0
+      h_w = self.post_pre(w)
+      h_w = self.post_convs(h_w, x_mask)
+      h_w = self.post_proj(h_w) * x_mask
+      e_q = torch.randn(w.size(0), 2, w.size(2)).to(device=x.device, dtype=x.dtype) * x_mask
+      z_q = e_q
+      for flow in self.post_flows:
+        z_q, logdet_q = flow(z_q, x_mask, g=(x + h_w))
+        logdet_tot_q += logdet_q
+      z_u, z1 = torch.split(z_q, [1, 1], 1)
+      u = torch.sigmoid(z_u) * x_mask
+      z0 = (w - u) * x_mask
+      logdet_tot_q += torch.sum((F.logsigmoid(z_u) + F.logsigmoid(-z_u)) * x_mask, [1,2])
+      logq = torch.sum(-0.5 * (math.log(2*math.pi) + (e_q**2)) * x_mask, [1,2]) - logdet_tot_q
+
+      logdet_tot = 0
+      z0, logdet = self.log_flow(z0, x_mask)
+      logdet_tot += logdet
+      z = torch.cat([z0, z1], 1)
+      for flow in flows:
+        z, logdet = flow(z, x_mask, g=x, reverse=reverse)
+        logdet_tot = logdet_tot + logdet
+      nll = torch.sum(0.5 * (math.log(2*math.pi) + (z**2)) * x_mask, [1,2]) - logdet_tot
+      return nll + logq # [b]
+    else:
+      flows = list(reversed(self.flows))
+      flows = flows[:-2] + [flows[-1]] # remove a useless vflow
+      z = torch.randn(x.size(0), 2, x.size(2)).to(device=x.device, dtype=x.dtype) * noise_scale
+      for flow in flows:
+        z = flow(z, x_mask, g=x, reverse=reverse)
+      z0, z1 = torch.split(z, [1, 1], 1)
+      logw = z0
+      return logw
+
+
+class DurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
+    super().__init__()
+
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.gin_channels = gin_channels
+
+    self.drop = nn.Dropout(p_dropout)
+    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_1 = modules.LayerNorm(filter_channels)
+    self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_2 = modules.LayerNorm(filter_channels)
+    self.proj = nn.Conv1d(filter_channels, 1, 1)
+
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, in_channels, 1)
+
+  def forward(self, x, x_mask, g=None):
+    x = torch.detach(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.conv_1(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_1(x)
+    x = self.drop(x)
+    x = self.conv_2(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_2(x)
+    x = self.drop(x)
+    x = self.proj(x * x_mask)
+    return x * x_mask
+
+
+class TextEncoder(nn.Module):
+  def __init__(self,
+      n_vocab,
+      out_channels,
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout):
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+
+    self.emb = nn.Embedding(n_vocab, hidden_channels)
+    nn.init.normal_(self.emb.weight, 0.0, hidden_channels**-0.5)
+
+    self.encoder = attentions.Encoder(
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout)
+    self.proj= nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths):
+    x = self.emb(x) * math.sqrt(self.hidden_channels) # [b, t, h]
+    x = torch.transpose(x, 1, -1) # [b, h, t]
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+
+    x = self.encoder(x * x_mask, x_mask)
+    stats = self.proj(x) * x_mask
+
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    return x, m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      n_flows=4,
+      gin_channels=0):
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.flows = nn.ModuleList()
+    for i in range(n_flows):
+      self.flows.append(modules.ResidualCouplingLayer(channels, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels, mean_only=True))
+      self.flows.append(modules.Flip())
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    if not reverse:
+      for flow in self.flows:
+        x, _ = flow(x, x_mask, g=g, reverse=reverse)
+    else:
+      for flow in reversed(self.flows):
+        x = flow(x, x_mask, g=g, reverse=reverse)
+    return x
+
+
+class PosteriorEncoder(nn.Module):
+  def __init__(self,
+      in_channels,
+      out_channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      gin_channels=0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+
+    self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+    self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
+    self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths, g=None):
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+    x = self.pre(x) * x_mask
+    x = self.enc(x, x_mask, g=g)
+    stats = self.proj(x) * x_mask
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+    return z, m, logs, x_mask
+
+
+class Generator(torch.nn.Module):
+    def __init__(self, initial_channel, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=0):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(initial_channel, upsample_initial_channel, 7, 1, padding=3)
+        resblock = modules.ResBlock1 if resblock == '1' else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(weight_norm(
+                ConvTranspose1d(upsample_initial_channel//(2**i), upsample_initial_channel//(2**(i+1)),
+                                k, u, padding=(k-u)//2)))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel//(2**(i+1))
+            for j, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+          x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i*self.num_kernels+j](x)
+                else:
+                    xs += self.resblocks[i*self.num_kernels+j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        print('Removing weight norm...')
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv2d(1, 32, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(32, 128, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(128, 512, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(512, 1024, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(1024, 1024, (kernel_size, 1), 1, padding=(get_padding(kernel_size, 1), 0))),
+        ])
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0: # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+            norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+            norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+            norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+            norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+            norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+        ])
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2,3,5,7,11]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+
+class SynthesizerTrn(nn.Module):
+  """
+  Synthesizer for Training
+  """
+
+  def __init__(self,
+    n_vocab,
+    spec_channels,
+    segment_size,
+    inter_channels,
+    hidden_channels,
+    filter_channels,
+    n_heads,
+    n_layers,
+    kernel_size,
+    p_dropout,
+    resblock,
+    resblock_kernel_sizes,
+    resblock_dilation_sizes,
+    upsample_rates,
+    upsample_initial_channel,
+    upsample_kernel_sizes,
+    n_speakers=0,
+    gin_channels=0,
+    use_sdp=True,
+    **kwargs):
+
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.spec_channels = spec_channels
+    self.inter_channels = inter_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.resblock = resblock
+    self.resblock_kernel_sizes = resblock_kernel_sizes
+    self.resblock_dilation_sizes = resblock_dilation_sizes
+    self.upsample_rates = upsample_rates
+    self.upsample_initial_channel = upsample_initial_channel
+    self.upsample_kernel_sizes = upsample_kernel_sizes
+    self.segment_size = segment_size
+    self.n_speakers = n_speakers
+    self.gin_channels = gin_channels
+
+    self.use_sdp = use_sdp
+
+    self.enc_p = TextEncoder(n_vocab,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout)
+    self.dec = Generator(inter_channels, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=gin_channels)
+    self.enc_q = PosteriorEncoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16, gin_channels=gin_channels)
+    self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, 4, gin_channels=gin_channels)
+
+    if use_sdp:
+      self.dp = StochasticDurationPredictor(hidden_channels, 192, 3, 0.5, 4, gin_channels=gin_channels)
+    else:
+      self.dp = DurationPredictor(hidden_channels, 256, 3, 0.5, gin_channels=gin_channels)
+
+    if n_speakers >= 1:
+      self.emb_g = nn.Embedding(n_speakers, gin_channels)
+
+  def forward(self, x, x_lengths, y, y_lengths, sid=None):
+
+    x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
+    if self.n_speakers > 0:
+      g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
+    else:
+      g = None
+
+    z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+    z_p = self.flow(z, y_mask, g=g)
+
+    with torch.no_grad():
+      # negative cross-entropy
+      s_p_sq_r = torch.exp(-2 * logs_p) # [b, d, t]
+      neg_cent1 = torch.sum(-0.5 * math.log(2 * math.pi) - logs_p, [1], keepdim=True) # [b, 1, t_s]
+      neg_cent2 = torch.matmul(-0.5 * (z_p ** 2).transpose(1, 2), s_p_sq_r) # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
+      neg_cent3 = torch.matmul(z_p.transpose(1, 2), (m_p * s_p_sq_r)) # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
+      neg_cent4 = torch.sum(-0.5 * (m_p ** 2) * s_p_sq_r, [1], keepdim=True) # [b, 1, t_s]
+      neg_cent = neg_cent1 + neg_cent2 + neg_cent3 + neg_cent4
+
+      attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
+      attn = monotonic_align.maximum_path(neg_cent, attn_mask.squeeze(1)).unsqueeze(1).detach()
+
+    w = attn.sum(2)
+    if self.use_sdp:
+      l_length = self.dp(x, x_mask, w, g=g)
+      l_length = l_length / torch.sum(x_mask)
+    else:
+      logw_ = torch.log(w + 1e-6) * x_mask
+      logw = self.dp(x, x_mask, g=g)
+      l_length = torch.sum((logw - logw_)**2, [1,2]) / torch.sum(x_mask) # for averaging
+
+    # expand prior
+    m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2)).transpose(1, 2)
+    logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2)).transpose(1, 2)
+
+    z_slice, ids_slice = commons.rand_slice_segments(z, y_lengths, self.segment_size)
+    o = self.dec(z_slice, g=g)
+    return o, l_length, attn, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+  def infer(self, x, x_lengths, sid=None, noise_scale=1, length_scale=1, noise_scale_w=1., max_len=None):
+    x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
+    if self.n_speakers > 0:
+      g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
+    else:
+      g = None
+
+    if self.use_sdp:
+      logw = self.dp(x, x_mask, g=g, reverse=True, noise_scale=noise_scale_w)
+    else:
+      logw = self.dp(x, x_mask, g=g)
+    w = torch.exp(logw) * x_mask * length_scale
+    w_ceil = torch.ceil(w)
+    y_lengths = torch.clamp_min(torch.sum(w_ceil, [1, 2]), 1).long()
+    y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, None), 1).to(x_mask.dtype)
+    attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
+    attn = commons.generate_path(w_ceil, attn_mask)
+
+    m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2)).transpose(1, 2) # [b, t', t], [b, t, d] -> [b, d, t']
+    logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2)).transpose(1, 2) # [b, t', t], [b, t, d] -> [b, d, t']
+
+    z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
+    z = self.flow(z_p, y_mask, g=g, reverse=True)
+    o = self.dec((z * y_mask)[:,:,:max_len], g=g)
+    return o, attn, y_mask, (z, z_p, m_p, logs_p)
+
+  def voice_conversion(self, y, y_lengths, sid_src, sid_tgt):
+    assert self.n_speakers > 0, "n_speakers have to be larger than 0."
+    g_src = self.emb_g(sid_src).unsqueeze(-1)
+    g_tgt = self.emb_g(sid_tgt).unsqueeze(-1)
+    z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g_src)
+    z_p = self.flow(z, y_mask, g=g_src)
+    z_hat = self.flow(z_p, y_mask, g=g_tgt, reverse=True)
+    o_hat = self.dec(z_hat * y_mask, g=g_tgt)
+    return o_hat, y_mask, (z, z_p, z_hat)
diff --git a/models_infer.py b/models_infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b9bb82bf5831c5264f3e1e52b23e8e875f5fd9e
--- /dev/null
+++ b/models_infer.py
@@ -0,0 +1,402 @@
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+import commons
+import modules
+import attentions
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from commons import init_weights, get_padding
+
+
+class StochasticDurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, n_flows=4, gin_channels=0):
+    super().__init__()
+    filter_channels = in_channels # it needs to be removed from future version.
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.log_flow = modules.Log()
+    self.flows = nn.ModuleList()
+    self.flows.append(modules.ElementwiseAffine(2))
+    for i in range(n_flows):
+      self.flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.flows.append(modules.Flip())
+
+    self.post_pre = nn.Conv1d(1, filter_channels, 1)
+    self.post_proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.post_convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    self.post_flows = nn.ModuleList()
+    self.post_flows.append(modules.ElementwiseAffine(2))
+    for i in range(4):
+      self.post_flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.post_flows.append(modules.Flip())
+
+    self.pre = nn.Conv1d(in_channels, filter_channels, 1)
+    self.proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, filter_channels, 1)
+
+  def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scale=1.0):
+    x = torch.detach(x)
+    x = self.pre(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.convs(x, x_mask)
+    x = self.proj(x) * x_mask
+
+    if not reverse:
+      flows = self.flows
+      assert w is not None
+
+      logdet_tot_q = 0
+      h_w = self.post_pre(w)
+      h_w = self.post_convs(h_w, x_mask)
+      h_w = self.post_proj(h_w) * x_mask
+      e_q = torch.randn(w.size(0), 2, w.size(2)).to(device=x.device, dtype=x.dtype) * x_mask
+      z_q = e_q
+      for flow in self.post_flows:
+        z_q, logdet_q = flow(z_q, x_mask, g=(x + h_w))
+        logdet_tot_q += logdet_q
+      z_u, z1 = torch.split(z_q, [1, 1], 1)
+      u = torch.sigmoid(z_u) * x_mask
+      z0 = (w - u) * x_mask
+      logdet_tot_q += torch.sum((F.logsigmoid(z_u) + F.logsigmoid(-z_u)) * x_mask, [1,2])
+      logq = torch.sum(-0.5 * (math.log(2*math.pi) + (e_q**2)) * x_mask, [1,2]) - logdet_tot_q
+
+      logdet_tot = 0
+      z0, logdet = self.log_flow(z0, x_mask)
+      logdet_tot += logdet
+      z = torch.cat([z0, z1], 1)
+      for flow in flows:
+        z, logdet = flow(z, x_mask, g=x, reverse=reverse)
+        logdet_tot = logdet_tot + logdet
+      nll = torch.sum(0.5 * (math.log(2*math.pi) + (z**2)) * x_mask, [1,2]) - logdet_tot
+      return nll + logq # [b]
+    else:
+      flows = list(reversed(self.flows))
+      flows = flows[:-2] + [flows[-1]] # remove a useless vflow
+      z = torch.randn(x.size(0), 2, x.size(2)).to(device=x.device, dtype=x.dtype) * noise_scale
+      for flow in flows:
+        z = flow(z, x_mask, g=x, reverse=reverse)
+      z0, z1 = torch.split(z, [1, 1], 1)
+      logw = z0
+      return logw
+
+
+class DurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
+    super().__init__()
+
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.gin_channels = gin_channels
+
+    self.drop = nn.Dropout(p_dropout)
+    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_1 = modules.LayerNorm(filter_channels)
+    self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_2 = modules.LayerNorm(filter_channels)
+    self.proj = nn.Conv1d(filter_channels, 1, 1)
+
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, in_channels, 1)
+
+  def forward(self, x, x_mask, g=None):
+    x = torch.detach(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.conv_1(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_1(x)
+    x = self.drop(x)
+    x = self.conv_2(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_2(x)
+    x = self.drop(x)
+    x = self.proj(x * x_mask)
+    return x * x_mask
+
+
+class TextEncoder(nn.Module):
+  def __init__(self,
+      n_vocab,
+      out_channels,
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout):
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+
+    self.emb = nn.Embedding(n_vocab, hidden_channels)
+    nn.init.normal_(self.emb.weight, 0.0, hidden_channels**-0.5)
+
+    self.encoder = attentions.Encoder(
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout)
+    self.proj= nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths):
+    x = self.emb(x) * math.sqrt(self.hidden_channels) # [b, t, h]
+    x = torch.transpose(x, 1, -1) # [b, h, t]
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+
+    x = self.encoder(x * x_mask, x_mask)
+    stats = self.proj(x) * x_mask
+
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    return x, m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      n_flows=4,
+      gin_channels=0):
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.flows = nn.ModuleList()
+    for i in range(n_flows):
+      self.flows.append(modules.ResidualCouplingLayer(channels, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels, mean_only=True))
+      self.flows.append(modules.Flip())
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    if not reverse:
+      for flow in self.flows:
+        x, _ = flow(x, x_mask, g=g, reverse=reverse)
+    else:
+      for flow in reversed(self.flows):
+        x = flow(x, x_mask, g=g, reverse=reverse)
+    return x
+
+
+class PosteriorEncoder(nn.Module):
+  def __init__(self,
+      in_channels,
+      out_channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      gin_channels=0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+
+    self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+    self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
+    self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths, g=None):
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+    x = self.pre(x) * x_mask
+    x = self.enc(x, x_mask, g=g)
+    stats = self.proj(x) * x_mask
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+    return z, m, logs, x_mask
+
+
+class Generator(torch.nn.Module):
+    def __init__(self, initial_channel, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=0):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(initial_channel, upsample_initial_channel, 7, 1, padding=3)
+        resblock = modules.ResBlock1 if resblock == '1' else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(weight_norm(
+                ConvTranspose1d(upsample_initial_channel//(2**i), upsample_initial_channel//(2**(i+1)),
+                                k, u, padding=(k-u)//2)))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel//(2**(i+1))
+            for j, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+          x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i*self.num_kernels+j](x)
+                else:
+                    xs += self.resblocks[i*self.num_kernels+j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        print('Removing weight norm...')
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+
+class SynthesizerTrn(nn.Module):
+  """
+  Synthesizer for Training
+  """
+
+  def __init__(self,
+    n_vocab,
+    spec_channels,
+    segment_size,
+    inter_channels,
+    hidden_channels,
+    filter_channels,
+    n_heads,
+    n_layers,
+    kernel_size,
+    p_dropout,
+    resblock,
+    resblock_kernel_sizes,
+    resblock_dilation_sizes,
+    upsample_rates,
+    upsample_initial_channel,
+    upsample_kernel_sizes,
+    n_speakers=0,
+    gin_channels=0,
+    use_sdp=True,
+    **kwargs):
+
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.spec_channels = spec_channels
+    self.inter_channels = inter_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.resblock = resblock
+    self.resblock_kernel_sizes = resblock_kernel_sizes
+    self.resblock_dilation_sizes = resblock_dilation_sizes
+    self.upsample_rates = upsample_rates
+    self.upsample_initial_channel = upsample_initial_channel
+    self.upsample_kernel_sizes = upsample_kernel_sizes
+    self.segment_size = segment_size
+    self.n_speakers = n_speakers
+    self.gin_channels = gin_channels
+
+    self.use_sdp = use_sdp
+
+    self.enc_p = TextEncoder(n_vocab,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout)
+    self.dec = Generator(inter_channels, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=gin_channels)
+    self.enc_q = PosteriorEncoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16, gin_channels=gin_channels)
+    self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, 4, gin_channels=gin_channels)
+
+    if use_sdp:
+      self.dp = StochasticDurationPredictor(hidden_channels, 192, 3, 0.5, 4, gin_channels=gin_channels)
+    else:
+      self.dp = DurationPredictor(hidden_channels, 256, 3, 0.5, gin_channels=gin_channels)
+
+    if n_speakers > 1:
+      self.emb_g = nn.Embedding(n_speakers, gin_channels)
+
+  def infer(self, x, x_lengths, sid=None, noise_scale=1, length_scale=1, noise_scale_w=1., max_len=None):
+    x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
+    if self.n_speakers > 0:
+      g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
+    else:
+      g = None
+
+    if self.use_sdp:
+      logw = self.dp(x, x_mask, g=g, reverse=True, noise_scale=noise_scale_w)
+    else:
+      logw = self.dp(x, x_mask, g=g)
+    w = torch.exp(logw) * x_mask * length_scale
+    w_ceil = torch.ceil(w)
+    y_lengths = torch.clamp_min(torch.sum(w_ceil, [1, 2]), 1).long()
+    y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, None), 1).to(x_mask.dtype)
+    attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
+    attn = commons.generate_path(w_ceil, attn_mask)
+
+    m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2)).transpose(1, 2) # [b, t', t], [b, t, d] -> [b, d, t']
+    logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2)).transpose(1, 2) # [b, t', t], [b, t, d] -> [b, d, t']
+
+    z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
+    z = self.flow(z_p, y_mask, g=g, reverse=True)
+    o = self.dec((z * y_mask)[:,:,:max_len], g=g)
+    return o, attn, y_mask, (z, z_p, m_p, logs_p)
+
+  def voice_conversion(self, y, y_lengths, sid_src, sid_tgt):
+    assert self.n_speakers > 0, "n_speakers have to be larger than 0."
+    g_src = self.emb_g(sid_src).unsqueeze(-1)
+    g_tgt = self.emb_g(sid_tgt).unsqueeze(-1)
+    z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g_src)
+    z_p = self.flow(z, y_mask, g=g_src)
+    z_hat = self.flow(z_p, y_mask, g=g_tgt, reverse=True)
+    o_hat = self.dec(z_hat * y_mask, g=g_tgt)
+    return o_hat, y_mask, (z, z_p, z_hat)
+
diff --git a/modules.py b/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..9c7fd9cd6eb8b7e0ec0e08957e970744a374a924
--- /dev/null
+++ b/modules.py
@@ -0,0 +1,390 @@
+import copy
+import math
+import numpy as np
+import scipy
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+import commons
+from commons import init_weights, get_padding
+from transforms import piecewise_rational_quadratic_transform
+
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+  def __init__(self, channels, eps=1e-5):
+    super().__init__()
+    self.channels = channels
+    self.eps = eps
+
+    self.gamma = nn.Parameter(torch.ones(channels))
+    self.beta = nn.Parameter(torch.zeros(channels))
+
+  def forward(self, x):
+    x = x.transpose(1, -1)
+    x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+    return x.transpose(1, -1)
+
+ 
+class ConvReluNorm(nn.Module):
+  def __init__(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout):
+    super().__init__()
+    self.in_channels = in_channels
+    self.hidden_channels = hidden_channels
+    self.out_channels = out_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+    assert n_layers > 1, "Number of layers should be larger than 0."
+
+    self.conv_layers = nn.ModuleList()
+    self.norm_layers = nn.ModuleList()
+    self.conv_layers.append(nn.Conv1d(in_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+    self.norm_layers.append(LayerNorm(hidden_channels))
+    self.relu_drop = nn.Sequential(
+        nn.ReLU(),
+        nn.Dropout(p_dropout))
+    for _ in range(n_layers-1):
+      self.conv_layers.append(nn.Conv1d(hidden_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+      self.norm_layers.append(LayerNorm(hidden_channels))
+    self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask):
+    x_org = x
+    for i in range(self.n_layers):
+      x = self.conv_layers[i](x * x_mask)
+      x = self.norm_layers[i](x)
+      x = self.relu_drop(x)
+    x = x_org + self.proj(x)
+    return x * x_mask
+
+
+class DDSConv(nn.Module):
+  """
+  Dialted and Depth-Separable Convolution
+  """
+  def __init__(self, channels, kernel_size, n_layers, p_dropout=0.):
+    super().__init__()
+    self.channels = channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+
+    self.drop = nn.Dropout(p_dropout)
+    self.convs_sep = nn.ModuleList()
+    self.convs_1x1 = nn.ModuleList()
+    self.norms_1 = nn.ModuleList()
+    self.norms_2 = nn.ModuleList()
+    for i in range(n_layers):
+      dilation = kernel_size ** i
+      padding = (kernel_size * dilation - dilation) // 2
+      self.convs_sep.append(nn.Conv1d(channels, channels, kernel_size, 
+          groups=channels, dilation=dilation, padding=padding
+      ))
+      self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+      self.norms_1.append(LayerNorm(channels))
+      self.norms_2.append(LayerNorm(channels))
+
+  def forward(self, x, x_mask, g=None):
+    if g is not None:
+      x = x + g
+    for i in range(self.n_layers):
+      y = self.convs_sep[i](x * x_mask)
+      y = self.norms_1[i](y)
+      y = F.gelu(y)
+      y = self.convs_1x1[i](y)
+      y = self.norms_2[i](y)
+      y = F.gelu(y)
+      y = self.drop(y)
+      x = x + y
+    return x * x_mask
+
+
+class WN(torch.nn.Module):
+  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=0, p_dropout=0):
+    super(WN, self).__init__()
+    assert(kernel_size % 2 == 1)
+    self.hidden_channels =hidden_channels
+    self.kernel_size = kernel_size,
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+    self.p_dropout = p_dropout
+
+    self.in_layers = torch.nn.ModuleList()
+    self.res_skip_layers = torch.nn.ModuleList()
+    self.drop = nn.Dropout(p_dropout)
+
+    if gin_channels != 0:
+      cond_layer = torch.nn.Conv1d(gin_channels, 2*hidden_channels*n_layers, 1)
+      self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name='weight')
+
+    for i in range(n_layers):
+      dilation = dilation_rate ** i
+      padding = int((kernel_size * dilation - dilation) / 2)
+      in_layer = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
+                                 dilation=dilation, padding=padding)
+      in_layer = torch.nn.utils.weight_norm(in_layer, name='weight')
+      self.in_layers.append(in_layer)
+
+      # last one is not necessary
+      if i < n_layers - 1:
+        res_skip_channels = 2 * hidden_channels
+      else:
+        res_skip_channels = hidden_channels
+
+      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+      res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
+      self.res_skip_layers.append(res_skip_layer)
+
+  def forward(self, x, x_mask, g=None, **kwargs):
+    output = torch.zeros_like(x)
+    n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+    if g is not None:
+      g = self.cond_layer(g)
+
+    for i in range(self.n_layers):
+      x_in = self.in_layers[i](x)
+      if g is not None:
+        cond_offset = i * 2 * self.hidden_channels
+        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
+      else:
+        g_l = torch.zeros_like(x_in)
+
+      acts = commons.fused_add_tanh_sigmoid_multiply(
+          x_in,
+          g_l,
+          n_channels_tensor)
+      acts = self.drop(acts)
+
+      res_skip_acts = self.res_skip_layers[i](acts)
+      if i < self.n_layers - 1:
+        res_acts = res_skip_acts[:,:self.hidden_channels,:]
+        x = (x + res_acts) * x_mask
+        output = output + res_skip_acts[:,self.hidden_channels:,:]
+      else:
+        output = output + res_skip_acts
+    return output * x_mask
+
+  def remove_weight_norm(self):
+    if self.gin_channels != 0:
+      torch.nn.utils.remove_weight_norm(self.cond_layer)
+    for l in self.in_layers:
+      torch.nn.utils.remove_weight_norm(l)
+    for l in self.res_skip_layers:
+     torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+        super(ResBlock1, self).__init__()
+        self.convs1 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[2],
+                               padding=get_padding(kernel_size, dilation[2])))
+        ])
+        self.convs1.apply(init_weights)
+
+        self.convs2 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1)))
+        ])
+        self.convs2.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c1, c2 in zip(self.convs1, self.convs2):
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c1(xt)
+            xt = F.leaky_relu(xt, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c2(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs1:
+            remove_weight_norm(l)
+        for l in self.convs2:
+            remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+        super(ResBlock2, self).__init__()
+        self.convs = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1])))
+        ])
+        self.convs.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c in self.convs:
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs:
+            remove_weight_norm(l)
+
+
+class Log(nn.Module):
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+      logdet = torch.sum(-y, [1, 2])
+      return y, logdet
+    else:
+      x = torch.exp(x) * x_mask
+      return x
+    
+
+class Flip(nn.Module):
+  def forward(self, x, *args, reverse=False, **kwargs):
+    x = torch.flip(x, [1])
+    if not reverse:
+      logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+      return x, logdet
+    else:
+      return x
+
+
+class ElementwiseAffine(nn.Module):
+  def __init__(self, channels):
+    super().__init__()
+    self.channels = channels
+    self.m = nn.Parameter(torch.zeros(channels,1))
+    self.logs = nn.Parameter(torch.zeros(channels,1))
+
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = self.m + torch.exp(self.logs) * x
+      y = y * x_mask
+      logdet = torch.sum(self.logs * x_mask, [1,2])
+      return y, logdet
+    else:
+      x = (x - self.m) * torch.exp(-self.logs) * x_mask
+      return x
+
+
+class ResidualCouplingLayer(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      p_dropout=0,
+      gin_channels=0,
+      mean_only=False):
+    assert channels % 2 == 0, "channels should be divisible by 2"
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.half_channels = channels // 2
+    self.mean_only = mean_only
+
+    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+    self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers, p_dropout=p_dropout, gin_channels=gin_channels)
+    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+    self.post.weight.data.zero_()
+    self.post.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0) * x_mask
+    h = self.enc(h, x_mask, g=g)
+    stats = self.post(h) * x_mask
+    if not self.mean_only:
+      m, logs = torch.split(stats, [self.half_channels]*2, 1)
+    else:
+      m = stats
+      logs = torch.zeros_like(m)
+
+    if not reverse:
+      x1 = m + x1 * torch.exp(logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      logdet = torch.sum(logs, [1,2])
+      return x, logdet
+    else:
+      x1 = (x1 - m) * torch.exp(-logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      return x
+
+
+class ConvFlow(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, n_layers, num_bins=10, tail_bound=5.0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.num_bins = num_bins
+    self.tail_bound = tail_bound
+    self.half_channels = in_channels // 2
+
+    self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+    self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.)
+    self.proj = nn.Conv1d(filter_channels, self.half_channels * (num_bins * 3 - 1), 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0)
+    h = self.convs(h, x_mask, g=g)
+    h = self.proj(h) * x_mask
+
+    b, c, t = x0.shape
+    h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2) # [b, cx?, t] -> [b, c, t, ?]
+
+    unnormalized_widths = h[..., :self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_heights = h[..., self.num_bins:2*self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_derivatives = h[..., 2 * self.num_bins:]
+
+    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
+        unnormalized_widths,
+        unnormalized_heights,
+        unnormalized_derivatives,
+        inverse=reverse,
+        tails='linear',
+        tail_bound=self.tail_bound
+    )
+
+    x = torch.cat([x0, x1], 1) * x_mask
+    logdet = torch.sum(logabsdet * x_mask, [1,2])
+    if not reverse:
+        return x, logdet
+    else:
+        return x
diff --git a/monotonic_align/__init__.py b/monotonic_align/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce9763c9f29283598d561d802a0db2de76835a54
--- /dev/null
+++ b/monotonic_align/__init__.py
@@ -0,0 +1,19 @@
+import numpy as np
+import torch
+from .monotonic_align.core import maximum_path_c
+
+
+def maximum_path(neg_cent, mask):
+  """ Cython optimized version.
+  neg_cent: [b, t_t, t_s]
+  mask: [b, t_t, t_s]
+  """
+  device = neg_cent.device
+  dtype = neg_cent.dtype
+  neg_cent = neg_cent.data.cpu().numpy().astype(np.float32)
+  path = np.zeros(neg_cent.shape, dtype=np.int32)
+
+  t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(np.int32)
+  t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(np.int32)
+  maximum_path_c(path, neg_cent, t_t_max, t_s_max)
+  return torch.from_numpy(path).to(device=device, dtype=dtype)
diff --git a/monotonic_align/build/lib.linux-x86_64-cpython-310/monotonic_align/core.cpython-310-x86_64-linux-gnu.so b/monotonic_align/build/lib.linux-x86_64-cpython-310/monotonic_align/core.cpython-310-x86_64-linux-gnu.so
new file mode 100644
index 0000000000000000000000000000000000000000..8acb4d1eac6192654b643fa9e186a7e75e580889
Binary files /dev/null and b/monotonic_align/build/lib.linux-x86_64-cpython-310/monotonic_align/core.cpython-310-x86_64-linux-gnu.so differ
diff --git a/monotonic_align/build/temp.linux-x86_64-cpython-310/core.o b/monotonic_align/build/temp.linux-x86_64-cpython-310/core.o
new file mode 100644
index 0000000000000000000000000000000000000000..6e490dd1411071d7dad90c3d3c826d14843192b1
Binary files /dev/null and b/monotonic_align/build/temp.linux-x86_64-cpython-310/core.o differ
diff --git a/monotonic_align/core.c b/monotonic_align/core.c
new file mode 100644
index 0000000000000000000000000000000000000000..d3687d97070a9f0a46abfc7cbd488076a42fd0d3
--- /dev/null
+++ b/monotonic_align/core.c
@@ -0,0 +1,21608 @@
+/* Generated by Cython 0.29.34 */
+
+/* BEGIN: Cython Metadata
+{
+    "distutils": {
+        "name": "monotonic_align.core",
+        "sources": [
+            "core.pyx"
+        ]
+    },
+    "module_name": "monotonic_align.core"
+}
+END: Cython Metadata */
+
+#ifndef PY_SSIZE_T_CLEAN
+#define PY_SSIZE_T_CLEAN
+#endif /* PY_SSIZE_T_CLEAN */
+#include "Python.h"
+#ifndef Py_PYTHON_H
+    #error Python headers needed to compile C extensions, please install development version of Python.
+#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000)
+    #error Cython requires Python 2.6+ or Python 3.3+.
+#else
+#define CYTHON_ABI "0_29_34"
+#define CYTHON_HEX_VERSION 0x001D22F0
+#define CYTHON_FUTURE_DIVISION 0
+#include <stddef.h>
+#ifndef offsetof
+  #define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
+#endif
+#if !defined(WIN32) && !defined(MS_WINDOWS)
+  #ifndef __stdcall
+    #define __stdcall
+  #endif
+  #ifndef __cdecl
+    #define __cdecl
+  #endif
+  #ifndef __fastcall
+    #define __fastcall
+  #endif
+#endif
+#ifndef DL_IMPORT
+  #define DL_IMPORT(t) t
+#endif
+#ifndef DL_EXPORT
+  #define DL_EXPORT(t) t
+#endif
+#define __PYX_COMMA ,
+#ifndef HAVE_LONG_LONG
+  #if PY_VERSION_HEX >= 0x02070000
+    #define HAVE_LONG_LONG
+  #endif
+#endif
+#ifndef PY_LONG_LONG
+  #define PY_LONG_LONG LONG_LONG
+#endif
+#ifndef Py_HUGE_VAL
+  #define Py_HUGE_VAL HUGE_VAL
+#endif
+#ifdef PYPY_VERSION
+  #define CYTHON_COMPILING_IN_PYPY 1
+  #define CYTHON_COMPILING_IN_PYSTON 0
+  #define CYTHON_COMPILING_IN_CPYTHON 0
+  #define CYTHON_COMPILING_IN_NOGIL 0
+  #undef CYTHON_USE_TYPE_SLOTS
+  #define CYTHON_USE_TYPE_SLOTS 0
+  #undef CYTHON_USE_PYTYPE_LOOKUP
+  #define CYTHON_USE_PYTYPE_LOOKUP 0
+  #if PY_VERSION_HEX < 0x03050000
+    #undef CYTHON_USE_ASYNC_SLOTS
+    #define CYTHON_USE_ASYNC_SLOTS 0
+  #elif !defined(CYTHON_USE_ASYNC_SLOTS)
+    #define CYTHON_USE_ASYNC_SLOTS 1
+  #endif
+  #undef CYTHON_USE_PYLIST_INTERNALS
+  #define CYTHON_USE_PYLIST_INTERNALS 0
+  #undef CYTHON_USE_UNICODE_INTERNALS
+  #define CYTHON_USE_UNICODE_INTERNALS 0
+  #undef CYTHON_USE_UNICODE_WRITER
+  #define CYTHON_USE_UNICODE_WRITER 0
+  #undef CYTHON_USE_PYLONG_INTERNALS
+  #define CYTHON_USE_PYLONG_INTERNALS 0
+  #undef CYTHON_AVOID_BORROWED_REFS
+  #define CYTHON_AVOID_BORROWED_REFS 1
+  #undef CYTHON_ASSUME_SAFE_MACROS
+  #define CYTHON_ASSUME_SAFE_MACROS 0
+  #undef CYTHON_UNPACK_METHODS
+  #define CYTHON_UNPACK_METHODS 0
+  #undef CYTHON_FAST_THREAD_STATE
+  #define CYTHON_FAST_THREAD_STATE 0
+  #undef CYTHON_FAST_PYCALL
+  #define CYTHON_FAST_PYCALL 0
+  #undef CYTHON_PEP489_MULTI_PHASE_INIT
+  #define CYTHON_PEP489_MULTI_PHASE_INIT 0
+  #undef CYTHON_USE_TP_FINALIZE
+  #define CYTHON_USE_TP_FINALIZE 0
+  #undef CYTHON_USE_DICT_VERSIONS
+  #define CYTHON_USE_DICT_VERSIONS 0
+  #undef CYTHON_USE_EXC_INFO_STACK
+  #define CYTHON_USE_EXC_INFO_STACK 0
+  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
+    #define CYTHON_UPDATE_DESCRIPTOR_DOC 0
+  #endif
+#elif defined(PYSTON_VERSION)
+  #define CYTHON_COMPILING_IN_PYPY 0
+  #define CYTHON_COMPILING_IN_PYSTON 1
+  #define CYTHON_COMPILING_IN_CPYTHON 0
+  #define CYTHON_COMPILING_IN_NOGIL 0
+  #ifndef CYTHON_USE_TYPE_SLOTS
+    #define CYTHON_USE_TYPE_SLOTS 1
+  #endif
+  #undef CYTHON_USE_PYTYPE_LOOKUP
+  #define CYTHON_USE_PYTYPE_LOOKUP 0
+  #undef CYTHON_USE_ASYNC_SLOTS
+  #define CYTHON_USE_ASYNC_SLOTS 0
+  #undef CYTHON_USE_PYLIST_INTERNALS
+  #define CYTHON_USE_PYLIST_INTERNALS 0
+  #ifndef CYTHON_USE_UNICODE_INTERNALS
+    #define CYTHON_USE_UNICODE_INTERNALS 1
+  #endif
+  #undef CYTHON_USE_UNICODE_WRITER
+  #define CYTHON_USE_UNICODE_WRITER 0
+  #undef CYTHON_USE_PYLONG_INTERNALS
+  #define CYTHON_USE_PYLONG_INTERNALS 0
+  #ifndef CYTHON_AVOID_BORROWED_REFS
+    #define CYTHON_AVOID_BORROWED_REFS 0
+  #endif
+  #ifndef CYTHON_ASSUME_SAFE_MACROS
+    #define CYTHON_ASSUME_SAFE_MACROS 1
+  #endif
+  #ifndef CYTHON_UNPACK_METHODS
+    #define CYTHON_UNPACK_METHODS 1
+  #endif
+  #undef CYTHON_FAST_THREAD_STATE
+  #define CYTHON_FAST_THREAD_STATE 0
+  #undef CYTHON_FAST_PYCALL
+  #define CYTHON_FAST_PYCALL 0
+  #undef CYTHON_PEP489_MULTI_PHASE_INIT
+  #define CYTHON_PEP489_MULTI_PHASE_INIT 0
+  #undef CYTHON_USE_TP_FINALIZE
+  #define CYTHON_USE_TP_FINALIZE 0
+  #undef CYTHON_USE_DICT_VERSIONS
+  #define CYTHON_USE_DICT_VERSIONS 0
+  #undef CYTHON_USE_EXC_INFO_STACK
+  #define CYTHON_USE_EXC_INFO_STACK 0
+  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
+    #define CYTHON_UPDATE_DESCRIPTOR_DOC 0
+  #endif
+#elif defined(PY_NOGIL)
+  #define CYTHON_COMPILING_IN_PYPY 0
+  #define CYTHON_COMPILING_IN_PYSTON 0
+  #define CYTHON_COMPILING_IN_CPYTHON 0
+  #define CYTHON_COMPILING_IN_NOGIL 1
+  #ifndef CYTHON_USE_TYPE_SLOTS
+    #define CYTHON_USE_TYPE_SLOTS 1
+  #endif
+  #undef CYTHON_USE_PYTYPE_LOOKUP
+  #define CYTHON_USE_PYTYPE_LOOKUP 0
+  #ifndef CYTHON_USE_ASYNC_SLOTS
+    #define CYTHON_USE_ASYNC_SLOTS 1
+  #endif
+  #undef CYTHON_USE_PYLIST_INTERNALS
+  #define CYTHON_USE_PYLIST_INTERNALS 0
+  #ifndef CYTHON_USE_UNICODE_INTERNALS
+    #define CYTHON_USE_UNICODE_INTERNALS 1
+  #endif
+  #undef CYTHON_USE_UNICODE_WRITER
+  #define CYTHON_USE_UNICODE_WRITER 0
+  #undef CYTHON_USE_PYLONG_INTERNALS
+  #define CYTHON_USE_PYLONG_INTERNALS 0
+  #ifndef CYTHON_AVOID_BORROWED_REFS
+    #define CYTHON_AVOID_BORROWED_REFS 0
+  #endif
+  #ifndef CYTHON_ASSUME_SAFE_MACROS
+    #define CYTHON_ASSUME_SAFE_MACROS 1
+  #endif
+  #ifndef CYTHON_UNPACK_METHODS
+    #define CYTHON_UNPACK_METHODS 1
+  #endif
+  #undef CYTHON_FAST_THREAD_STATE
+  #define CYTHON_FAST_THREAD_STATE 0
+  #undef CYTHON_FAST_PYCALL
+  #define CYTHON_FAST_PYCALL 0
+  #ifndef CYTHON_PEP489_MULTI_PHASE_INIT
+    #define CYTHON_PEP489_MULTI_PHASE_INIT 1
+  #endif
+  #ifndef CYTHON_USE_TP_FINALIZE
+    #define CYTHON_USE_TP_FINALIZE 1
+  #endif
+  #undef CYTHON_USE_DICT_VERSIONS
+  #define CYTHON_USE_DICT_VERSIONS 0
+  #undef CYTHON_USE_EXC_INFO_STACK
+  #define CYTHON_USE_EXC_INFO_STACK 0
+#else
+  #define CYTHON_COMPILING_IN_PYPY 0
+  #define CYTHON_COMPILING_IN_PYSTON 0
+  #define CYTHON_COMPILING_IN_CPYTHON 1
+  #define CYTHON_COMPILING_IN_NOGIL 0
+  #ifndef CYTHON_USE_TYPE_SLOTS
+    #define CYTHON_USE_TYPE_SLOTS 1
+  #endif
+  #if PY_VERSION_HEX < 0x02070000
+    #undef CYTHON_USE_PYTYPE_LOOKUP
+    #define CYTHON_USE_PYTYPE_LOOKUP 0
+  #elif !defined(CYTHON_USE_PYTYPE_LOOKUP)
+    #define CYTHON_USE_PYTYPE_LOOKUP 1
+  #endif
+  #if PY_MAJOR_VERSION < 3
+    #undef CYTHON_USE_ASYNC_SLOTS
+    #define CYTHON_USE_ASYNC_SLOTS 0
+  #elif !defined(CYTHON_USE_ASYNC_SLOTS)
+    #define CYTHON_USE_ASYNC_SLOTS 1
+  #endif
+  #if PY_VERSION_HEX < 0x02070000
+    #undef CYTHON_USE_PYLONG_INTERNALS
+    #define CYTHON_USE_PYLONG_INTERNALS 0
+  #elif !defined(CYTHON_USE_PYLONG_INTERNALS)
+    #define CYTHON_USE_PYLONG_INTERNALS (PY_VERSION_HEX < 0x030C00A5)
+  #endif
+  #ifndef CYTHON_USE_PYLIST_INTERNALS
+    #define CYTHON_USE_PYLIST_INTERNALS 1
+  #endif
+  #ifndef CYTHON_USE_UNICODE_INTERNALS
+    #define CYTHON_USE_UNICODE_INTERNALS 1
+  #endif
+  #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2
+    #undef CYTHON_USE_UNICODE_WRITER
+    #define CYTHON_USE_UNICODE_WRITER 0
+  #elif !defined(CYTHON_USE_UNICODE_WRITER)
+    #define CYTHON_USE_UNICODE_WRITER 1
+  #endif
+  #ifndef CYTHON_AVOID_BORROWED_REFS
+    #define CYTHON_AVOID_BORROWED_REFS 0
+  #endif
+  #ifndef CYTHON_ASSUME_SAFE_MACROS
+    #define CYTHON_ASSUME_SAFE_MACROS 1
+  #endif
+  #ifndef CYTHON_UNPACK_METHODS
+    #define CYTHON_UNPACK_METHODS 1
+  #endif
+  #if PY_VERSION_HEX >= 0x030B00A4
+    #undef CYTHON_FAST_THREAD_STATE
+    #define CYTHON_FAST_THREAD_STATE 0
+  #elif !defined(CYTHON_FAST_THREAD_STATE)
+    #define CYTHON_FAST_THREAD_STATE 1
+  #endif
+  #ifndef CYTHON_FAST_PYCALL
+    #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030A0000)
+  #endif
+  #ifndef CYTHON_PEP489_MULTI_PHASE_INIT
+    #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000)
+  #endif
+  #ifndef CYTHON_USE_TP_FINALIZE
+    #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1)
+  #endif
+  #ifndef CYTHON_USE_DICT_VERSIONS
+    #define CYTHON_USE_DICT_VERSIONS ((PY_VERSION_HEX >= 0x030600B1) && (PY_VERSION_HEX < 0x030C00A5))
+  #endif
+  #if PY_VERSION_HEX >= 0x030B00A4
+    #undef CYTHON_USE_EXC_INFO_STACK
+    #define CYTHON_USE_EXC_INFO_STACK 0
+  #elif !defined(CYTHON_USE_EXC_INFO_STACK)
+    #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3)
+  #endif
+  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
+    #define CYTHON_UPDATE_DESCRIPTOR_DOC 1
+  #endif
+#endif
+#if !defined(CYTHON_FAST_PYCCALL)
+#define CYTHON_FAST_PYCCALL  (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1)
+#endif
+#if CYTHON_USE_PYLONG_INTERNALS
+  #if PY_MAJOR_VERSION < 3
+    #include "longintrepr.h"
+  #endif
+  #undef SHIFT
+  #undef BASE
+  #undef MASK
+  #ifdef SIZEOF_VOID_P
+    enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) };
+  #endif
+#endif
+#ifndef __has_attribute
+  #define __has_attribute(x) 0
+#endif
+#ifndef __has_cpp_attribute
+  #define __has_cpp_attribute(x) 0
+#endif
+#ifndef CYTHON_RESTRICT
+  #if defined(__GNUC__)
+    #define CYTHON_RESTRICT __restrict__
+  #elif defined(_MSC_VER) && _MSC_VER >= 1400
+    #define CYTHON_RESTRICT __restrict
+  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+    #define CYTHON_RESTRICT restrict
+  #else
+    #define CYTHON_RESTRICT
+  #endif
+#endif
+#ifndef CYTHON_UNUSED
+# if defined(__GNUC__)
+#   if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
+#     define CYTHON_UNUSED __attribute__ ((__unused__))
+#   else
+#     define CYTHON_UNUSED
+#   endif
+# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
+#   define CYTHON_UNUSED __attribute__ ((__unused__))
+# else
+#   define CYTHON_UNUSED
+# endif
+#endif
+#ifndef CYTHON_MAYBE_UNUSED_VAR
+#  if defined(__cplusplus)
+     template<class T> void CYTHON_MAYBE_UNUSED_VAR( const T& ) { }
+#  else
+#    define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x)
+#  endif
+#endif
+#ifndef CYTHON_NCP_UNUSED
+# if CYTHON_COMPILING_IN_CPYTHON
+#  define CYTHON_NCP_UNUSED
+# else
+#  define CYTHON_NCP_UNUSED CYTHON_UNUSED
+# endif
+#endif
+#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None)
+#ifdef _MSC_VER
+    #ifndef _MSC_STDINT_H_
+        #if _MSC_VER < 1300
+           typedef unsigned char     uint8_t;
+           typedef unsigned int      uint32_t;
+        #else
+           typedef unsigned __int8   uint8_t;
+           typedef unsigned __int32  uint32_t;
+        #endif
+    #endif
+#else
+   #include <stdint.h>
+#endif
+#ifndef CYTHON_FALLTHROUGH
+  #if defined(__cplusplus) && __cplusplus >= 201103L
+    #if __has_cpp_attribute(fallthrough)
+      #define CYTHON_FALLTHROUGH [[fallthrough]]
+    #elif __has_cpp_attribute(clang::fallthrough)
+      #define CYTHON_FALLTHROUGH [[clang::fallthrough]]
+    #elif __has_cpp_attribute(gnu::fallthrough)
+      #define CYTHON_FALLTHROUGH [[gnu::fallthrough]]
+    #endif
+  #endif
+  #ifndef CYTHON_FALLTHROUGH
+    #if __has_attribute(fallthrough)
+      #define CYTHON_FALLTHROUGH __attribute__((fallthrough))
+    #else
+      #define CYTHON_FALLTHROUGH
+    #endif
+  #endif
+  #if defined(__clang__ ) && defined(__apple_build_version__)
+    #if __apple_build_version__ < 7000000
+      #undef  CYTHON_FALLTHROUGH
+      #define CYTHON_FALLTHROUGH
+    #endif
+  #endif
+#endif
+
+#ifndef CYTHON_INLINE
+  #if defined(__clang__)
+    #define CYTHON_INLINE __inline__ __attribute__ ((__unused__))
+  #elif defined(__GNUC__)
+    #define CYTHON_INLINE __inline__
+  #elif defined(_MSC_VER)
+    #define CYTHON_INLINE __inline
+  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+    #define CYTHON_INLINE inline
+  #else
+    #define CYTHON_INLINE
+  #endif
+#endif
+
+#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag)
+  #define Py_OptimizeFlag 0
+#endif
+#define __PYX_BUILD_PY_SSIZE_T "n"
+#define CYTHON_FORMAT_SSIZE_T "z"
+#if PY_MAJOR_VERSION < 3
+  #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
+  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
+          PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+  #define __Pyx_DefaultClassType PyClass_Type
+#else
+  #define __Pyx_BUILTIN_MODULE_NAME "builtins"
+  #define __Pyx_DefaultClassType PyType_Type
+#if PY_VERSION_HEX >= 0x030B00A1
+    static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f,
+                                                    PyObject *code, PyObject *c, PyObject* n, PyObject *v,
+                                                    PyObject *fv, PyObject *cell, PyObject* fn,
+                                                    PyObject *name, int fline, PyObject *lnos) {
+        PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL;
+        PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL;
+        const char *fn_cstr=NULL;
+        const char *name_cstr=NULL;
+        PyCodeObject* co=NULL;
+        PyObject *type, *value, *traceback;
+        PyErr_Fetch(&type, &value, &traceback);
+        if (!(kwds=PyDict_New())) goto end;
+        if (!(argcount=PyLong_FromLong(a))) goto end;
+        if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end;
+        if (!(posonlyargcount=PyLong_FromLong(0))) goto end;
+        if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end;
+        if (!(kwonlyargcount=PyLong_FromLong(k))) goto end;
+        if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end;
+        if (!(nlocals=PyLong_FromLong(l))) goto end;
+        if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end;
+        if (!(stacksize=PyLong_FromLong(s))) goto end;
+        if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end;
+        if (!(flags=PyLong_FromLong(f))) goto end;
+        if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end;
+        if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end;
+        if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end;
+        if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end;
+        if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end;
+        if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too;
+        if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here
+        if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too;
+        Py_XDECREF((PyObject*)co);
+        co = (PyCodeObject*)call_result;
+        call_result = NULL;
+        if (0) {
+            cleanup_code_too:
+            Py_XDECREF((PyObject*)co);
+            co = NULL;
+        }
+        end:
+        Py_XDECREF(kwds);
+        Py_XDECREF(argcount);
+        Py_XDECREF(posonlyargcount);
+        Py_XDECREF(kwonlyargcount);
+        Py_XDECREF(nlocals);
+        Py_XDECREF(stacksize);
+        Py_XDECREF(replace);
+        Py_XDECREF(call_result);
+        Py_XDECREF(empty);
+        if (type) {
+            PyErr_Restore(type, value, traceback);
+        }
+        return co;
+    }
+#else
+  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
+          PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+#endif
+  #define __Pyx_DefaultClassType PyType_Type
+#endif
+#ifndef Py_TPFLAGS_CHECKTYPES
+  #define Py_TPFLAGS_CHECKTYPES 0
+#endif
+#ifndef Py_TPFLAGS_HAVE_INDEX
+  #define Py_TPFLAGS_HAVE_INDEX 0
+#endif
+#ifndef Py_TPFLAGS_HAVE_NEWBUFFER
+  #define Py_TPFLAGS_HAVE_NEWBUFFER 0
+#endif
+#ifndef Py_TPFLAGS_HAVE_FINALIZE
+  #define Py_TPFLAGS_HAVE_FINALIZE 0
+#endif
+#ifndef METH_STACKLESS
+  #define METH_STACKLESS 0
+#endif
+#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL)
+  #ifndef METH_FASTCALL
+     #define METH_FASTCALL 0x80
+  #endif
+  typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs);
+  typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args,
+                                                          Py_ssize_t nargs, PyObject *kwnames);
+#else
+  #define __Pyx_PyCFunctionFast _PyCFunctionFast
+  #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords
+#endif
+#if CYTHON_FAST_PYCCALL
+#define __Pyx_PyFastCFunction_Check(func)\
+    ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS)))))
+#else
+#define __Pyx_PyFastCFunction_Check(func) 0
+#endif
+#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc)
+  #define PyObject_Malloc(s)   PyMem_Malloc(s)
+  #define PyObject_Free(p)     PyMem_Free(p)
+  #define PyObject_Realloc(p)  PyMem_Realloc(p)
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1
+  #define PyMem_RawMalloc(n)           PyMem_Malloc(n)
+  #define PyMem_RawRealloc(p, n)       PyMem_Realloc(p, n)
+  #define PyMem_RawFree(p)             PyMem_Free(p)
+#endif
+#if CYTHON_COMPILING_IN_PYSTON
+  #define __Pyx_PyCode_HasFreeVars(co)  PyCode_HasFreeVars(co)
+  #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno)
+#else
+  #define __Pyx_PyCode_HasFreeVars(co)  (PyCode_GetNumFree(co) > 0)
+  #define __Pyx_PyFrame_SetLineNumber(frame, lineno)  (frame)->f_lineno = (lineno)
+#endif
+#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000
+  #define __Pyx_PyThreadState_Current PyThreadState_GET()
+#elif PY_VERSION_HEX >= 0x03060000
+  #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet()
+#elif PY_VERSION_HEX >= 0x03000000
+  #define __Pyx_PyThreadState_Current PyThreadState_GET()
+#else
+  #define __Pyx_PyThreadState_Current _PyThreadState_Current
+#endif
+#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT)
+#include "pythread.h"
+#define Py_tss_NEEDS_INIT 0
+typedef int Py_tss_t;
+static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) {
+  *key = PyThread_create_key();
+  return 0;
+}
+static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) {
+  Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t));
+  *key = Py_tss_NEEDS_INIT;
+  return key;
+}
+static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) {
+  PyObject_Free(key);
+}
+static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) {
+  return *key != Py_tss_NEEDS_INIT;
+}
+static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) {
+  PyThread_delete_key(*key);
+  *key = Py_tss_NEEDS_INIT;
+}
+static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) {
+  return PyThread_set_key_value(*key, value);
+}
+static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) {
+  return PyThread_get_key_value(*key);
+}
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized)
+#define __Pyx_PyDict_NewPresized(n)  ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n))
+#else
+#define __Pyx_PyDict_NewPresized(n)  PyDict_New()
+#endif
+#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION
+  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_TrueDivide(x,y)
+  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceTrueDivide(x,y)
+#else
+  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_Divide(x,y)
+  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceDivide(x,y)
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS
+#define __Pyx_PyDict_GetItemStr(dict, name)  _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash)
+#else
+#define __Pyx_PyDict_GetItemStr(dict, name)  PyDict_GetItem(dict, name)
+#endif
+#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
+  #define CYTHON_PEP393_ENABLED 1
+  #if PY_VERSION_HEX >= 0x030C0000
+    #define __Pyx_PyUnicode_READY(op)       (0)
+  #else
+    #define __Pyx_PyUnicode_READY(op)       (likely(PyUnicode_IS_READY(op)) ?\
+                                                0 : _PyUnicode_Ready((PyObject *)(op)))
+  #endif
+  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_LENGTH(u)
+  #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
+  #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u)   PyUnicode_MAX_CHAR_VALUE(u)
+  #define __Pyx_PyUnicode_KIND(u)         PyUnicode_KIND(u)
+  #define __Pyx_PyUnicode_DATA(u)         PyUnicode_DATA(u)
+  #define __Pyx_PyUnicode_READ(k, d, i)   PyUnicode_READ(k, d, i)
+  #define __Pyx_PyUnicode_WRITE(k, d, i, ch)  PyUnicode_WRITE(k, d, i, ch)
+  #if PY_VERSION_HEX >= 0x030C0000
+    #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != PyUnicode_GET_LENGTH(u))
+  #else
+    #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000
+    #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length))
+    #else
+    #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u)))
+    #endif
+  #endif
+#else
+  #define CYTHON_PEP393_ENABLED 0
+  #define PyUnicode_1BYTE_KIND  1
+  #define PyUnicode_2BYTE_KIND  2
+  #define PyUnicode_4BYTE_KIND  4
+  #define __Pyx_PyUnicode_READY(op)       (0)
+  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_SIZE(u)
+  #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
+  #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u)   ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111)
+  #define __Pyx_PyUnicode_KIND(u)         (sizeof(Py_UNICODE))
+  #define __Pyx_PyUnicode_DATA(u)         ((void*)PyUnicode_AS_UNICODE(u))
+  #define __Pyx_PyUnicode_READ(k, d, i)   ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
+  #define __Pyx_PyUnicode_WRITE(k, d, i, ch)  (((void)(k)), ((Py_UNICODE*)d)[i] = ch)
+  #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != PyUnicode_GET_SIZE(u))
+#endif
+#if CYTHON_COMPILING_IN_PYPY
+  #define __Pyx_PyUnicode_Concat(a, b)      PyNumber_Add(a, b)
+  #define __Pyx_PyUnicode_ConcatSafe(a, b)  PyNumber_Add(a, b)
+#else
+  #define __Pyx_PyUnicode_Concat(a, b)      PyUnicode_Concat(a, b)
+  #define __Pyx_PyUnicode_ConcatSafe(a, b)  ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\
+      PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
+#endif
+#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains)
+  #define PyUnicode_Contains(u, s)  PySequence_Contains(u, s)
+#endif
+#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check)
+  #define PyByteArray_Check(obj)  PyObject_TypeCheck(obj, &PyByteArray_Type)
+#endif
+#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format)
+  #define PyObject_Format(obj, fmt)  PyObject_CallMethod(obj, "__format__", "O", fmt)
+#endif
+#define __Pyx_PyString_FormatSafe(a, b)   ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
+#define __Pyx_PyUnicode_FormatSafe(a, b)  ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
+#if PY_MAJOR_VERSION >= 3
+  #define __Pyx_PyString_Format(a, b)  PyUnicode_Format(a, b)
+#else
+  #define __Pyx_PyString_Format(a, b)  PyString_Format(a, b)
+#endif
+#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII)
+  #define PyObject_ASCII(o)            PyObject_Repr(o)
+#endif
+#if PY_MAJOR_VERSION >= 3
+  #define PyBaseString_Type            PyUnicode_Type
+  #define PyStringObject               PyUnicodeObject
+  #define PyString_Type                PyUnicode_Type
+  #define PyString_Check               PyUnicode_Check
+  #define PyString_CheckExact          PyUnicode_CheckExact
+#ifndef PyObject_Unicode
+  #define PyObject_Unicode             PyObject_Str
+#endif
+#endif
+#if PY_MAJOR_VERSION >= 3
+  #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
+  #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
+#else
+  #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
+  #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
+#endif
+#ifndef PySet_CheckExact
+  #define PySet_CheckExact(obj)        (Py_TYPE(obj) == &PySet_Type)
+#endif
+#if PY_VERSION_HEX >= 0x030900A4
+  #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt)
+  #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size)
+#else
+  #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt)
+  #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size)
+#endif
+#if CYTHON_ASSUME_SAFE_MACROS
+  #define __Pyx_PySequence_SIZE(seq)  Py_SIZE(seq)
+#else
+  #define __Pyx_PySequence_SIZE(seq)  PySequence_Size(seq)
+#endif
+#if PY_MAJOR_VERSION >= 3
+  #define PyIntObject                  PyLongObject
+  #define PyInt_Type                   PyLong_Type
+  #define PyInt_Check(op)              PyLong_Check(op)
+  #define PyInt_CheckExact(op)         PyLong_CheckExact(op)
+  #define PyInt_FromString             PyLong_FromString
+  #define PyInt_FromUnicode            PyLong_FromUnicode
+  #define PyInt_FromLong               PyLong_FromLong
+  #define PyInt_FromSize_t             PyLong_FromSize_t
+  #define PyInt_FromSsize_t            PyLong_FromSsize_t
+  #define PyInt_AsLong                 PyLong_AsLong
+  #define PyInt_AS_LONG                PyLong_AS_LONG
+  #define PyInt_AsSsize_t              PyLong_AsSsize_t
+  #define PyInt_AsUnsignedLongMask     PyLong_AsUnsignedLongMask
+  #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
+  #define PyNumber_Int                 PyNumber_Long
+#endif
+#if PY_MAJOR_VERSION >= 3
+  #define PyBoolObject                 PyLongObject
+#endif
+#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
+  #ifndef PyUnicode_InternFromString
+    #define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
+  #endif
+#endif
+#if PY_VERSION_HEX < 0x030200A4
+  typedef long Py_hash_t;
+  #define __Pyx_PyInt_FromHash_t PyInt_FromLong
+  #define __Pyx_PyInt_AsHash_t   __Pyx_PyIndex_AsHash_t
+#else
+  #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
+  #define __Pyx_PyInt_AsHash_t   __Pyx_PyIndex_AsSsize_t
+#endif
+#if PY_MAJOR_VERSION >= 3
+  #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func))
+#else
+  #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
+#endif
+#if CYTHON_USE_ASYNC_SLOTS
+  #if PY_VERSION_HEX >= 0x030500B1
+    #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods
+    #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async)
+  #else
+    #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved))
+  #endif
+#else
+  #define __Pyx_PyType_AsAsync(obj) NULL
+#endif
+#ifndef __Pyx_PyAsyncMethodsStruct
+    typedef struct {
+        unaryfunc am_await;
+        unaryfunc am_aiter;
+        unaryfunc am_anext;
+    } __Pyx_PyAsyncMethodsStruct;
+#endif
+
+#if defined(_WIN32) || defined(WIN32) || defined(MS_WINDOWS)
+  #if !defined(_USE_MATH_DEFINES)
+    #define _USE_MATH_DEFINES
+  #endif
+#endif
+#include <math.h>
+#ifdef NAN
+#define __PYX_NAN() ((float) NAN)
+#else
+static CYTHON_INLINE float __PYX_NAN() {
+  float value;
+  memset(&value, 0xFF, sizeof(value));
+  return value;
+}
+#endif
+#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL)
+#define __Pyx_truncl trunc
+#else
+#define __Pyx_truncl truncl
+#endif
+
+#define __PYX_MARK_ERR_POS(f_index, lineno) \
+    { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; }
+#define __PYX_ERR(f_index, lineno, Ln_error) \
+    { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; }
+
+#ifndef __PYX_EXTERN_C
+  #ifdef __cplusplus
+    #define __PYX_EXTERN_C extern "C"
+  #else
+    #define __PYX_EXTERN_C extern
+  #endif
+#endif
+
+#define __PYX_HAVE__monotonic_align__core
+#define __PYX_HAVE_API__monotonic_align__core
+/* Early includes */
+#include "pythread.h"
+#include <string.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include "pystate.h"
+#ifdef _OPENMP
+#include <omp.h>
+#endif /* _OPENMP */
+
+#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS)
+#define CYTHON_WITHOUT_ASSERTIONS
+#endif
+
+typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding;
+                const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
+
+#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
+#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0
+#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8)
+#define __PYX_DEFAULT_STRING_ENCODING ""
+#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
+#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#define __Pyx_uchar_cast(c) ((unsigned char)c)
+#define __Pyx_long_cast(x) ((long)x)
+#define __Pyx_fits_Py_ssize_t(v, type, is_signed)  (\
+    (sizeof(type) < sizeof(Py_ssize_t))  ||\
+    (sizeof(type) > sizeof(Py_ssize_t) &&\
+          likely(v < (type)PY_SSIZE_T_MAX ||\
+                 v == (type)PY_SSIZE_T_MAX)  &&\
+          (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\
+                                v == (type)PY_SSIZE_T_MIN)))  ||\
+    (sizeof(type) == sizeof(Py_ssize_t) &&\
+          (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\
+                               v == (type)PY_SSIZE_T_MAX)))  )
+static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) {
+    return (size_t) i < (size_t) limit;
+}
+#if defined (__cplusplus) && __cplusplus >= 201103L
+    #include <cstdlib>
+    #define __Pyx_sst_abs(value) std::abs(value)
+#elif SIZEOF_INT >= SIZEOF_SIZE_T
+    #define __Pyx_sst_abs(value) abs(value)
+#elif SIZEOF_LONG >= SIZEOF_SIZE_T
+    #define __Pyx_sst_abs(value) labs(value)
+#elif defined (_MSC_VER)
+    #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value))
+#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
+    #define __Pyx_sst_abs(value) llabs(value)
+#elif defined (__GNUC__)
+    #define __Pyx_sst_abs(value) __builtin_llabs(value)
+#else
+    #define __Pyx_sst_abs(value) ((value<0) ? -value : value)
+#endif
+static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*);
+static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
+#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
+#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
+#define __Pyx_PyBytes_FromString        PyBytes_FromString
+#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
+#if PY_MAJOR_VERSION < 3
+    #define __Pyx_PyStr_FromString        __Pyx_PyBytes_FromString
+    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
+#else
+    #define __Pyx_PyStr_FromString        __Pyx_PyUnicode_FromString
+    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
+#endif
+#define __Pyx_PyBytes_AsWritableString(s)     ((char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyBytes_AsWritableSString(s)    ((signed char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyBytes_AsWritableUString(s)    ((unsigned char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyBytes_AsString(s)     ((const char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyBytes_AsSString(s)    ((const signed char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyBytes_AsUString(s)    ((const unsigned char*) PyBytes_AS_STRING(s))
+#define __Pyx_PyObject_AsWritableString(s)    ((char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsWritableSString(s)    ((signed char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsWritableUString(s)    ((unsigned char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsSString(s)    ((const signed char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_AsUString(s)    ((const unsigned char*) __Pyx_PyObject_AsString(s))
+#define __Pyx_PyObject_FromCString(s)  __Pyx_PyObject_FromString((const char*)s)
+#define __Pyx_PyBytes_FromCString(s)   __Pyx_PyBytes_FromString((const char*)s)
+#define __Pyx_PyByteArray_FromCString(s)   __Pyx_PyByteArray_FromString((const char*)s)
+#define __Pyx_PyStr_FromCString(s)     __Pyx_PyStr_FromString((const char*)s)
+#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
+static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) {
+    const Py_UNICODE *u_end = u;
+    while (*u_end++) ;
+    return (size_t)(u_end - u - 1);
+}
+#define __Pyx_PyUnicode_FromUnicode(u)       PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
+#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
+#define __Pyx_PyUnicode_AsUnicode            PyUnicode_AsUnicode
+#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj)
+#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
+static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b);
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
+static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*);
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x);
+#define __Pyx_PySequence_Tuple(obj)\
+    (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj))
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
+static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*);
+#if CYTHON_ASSUME_SAFE_MACROS
+#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
+#else
+#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
+#endif
+#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
+#if PY_MAJOR_VERSION >= 3
+#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
+#else
+#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
+#endif
+#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x))
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+static int __Pyx_sys_getdefaultencoding_not_ascii;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+    PyObject* sys;
+    PyObject* default_encoding = NULL;
+    PyObject* ascii_chars_u = NULL;
+    PyObject* ascii_chars_b = NULL;
+    const char* default_encoding_c;
+    sys = PyImport_ImportModule("sys");
+    if (!sys) goto bad;
+    default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
+    Py_DECREF(sys);
+    if (!default_encoding) goto bad;
+    default_encoding_c = PyBytes_AsString(default_encoding);
+    if (!default_encoding_c) goto bad;
+    if (strcmp(default_encoding_c, "ascii") == 0) {
+        __Pyx_sys_getdefaultencoding_not_ascii = 0;
+    } else {
+        char ascii_chars[128];
+        int c;
+        for (c = 0; c < 128; c++) {
+            ascii_chars[c] = c;
+        }
+        __Pyx_sys_getdefaultencoding_not_ascii = 1;
+        ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
+        if (!ascii_chars_u) goto bad;
+        ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
+        if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
+            PyErr_Format(
+                PyExc_ValueError,
+                "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
+                default_encoding_c);
+            goto bad;
+        }
+        Py_DECREF(ascii_chars_u);
+        Py_DECREF(ascii_chars_b);
+    }
+    Py_DECREF(default_encoding);
+    return 0;
+bad:
+    Py_XDECREF(default_encoding);
+    Py_XDECREF(ascii_chars_u);
+    Py_XDECREF(ascii_chars_b);
+    return -1;
+}
+#endif
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
+#else
+#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
+#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+static char* __PYX_DEFAULT_STRING_ENCODING;
+static int __Pyx_init_sys_getdefaultencoding_params(void) {
+    PyObject* sys;
+    PyObject* default_encoding = NULL;
+    char* default_encoding_c;
+    sys = PyImport_ImportModule("sys");
+    if (!sys) goto bad;
+    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
+    Py_DECREF(sys);
+    if (!default_encoding) goto bad;
+    default_encoding_c = PyBytes_AsString(default_encoding);
+    if (!default_encoding_c) goto bad;
+    __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1);
+    if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
+    strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
+    Py_DECREF(default_encoding);
+    return 0;
+bad:
+    Py_XDECREF(default_encoding);
+    return -1;
+}
+#endif
+#endif
+
+
+/* Test for GCC > 2.95 */
+#if defined(__GNUC__)     && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
+  #define likely(x)   __builtin_expect(!!(x), 1)
+  #define unlikely(x) __builtin_expect(!!(x), 0)
+#else /* !__GNUC__ or GCC < 2.95 */
+  #define likely(x)   (x)
+  #define unlikely(x) (x)
+#endif /* __GNUC__ */
+static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; }
+
+static PyObject *__pyx_m = NULL;
+static PyObject *__pyx_d;
+static PyObject *__pyx_b;
+static PyObject *__pyx_cython_runtime = NULL;
+static PyObject *__pyx_empty_tuple;
+static PyObject *__pyx_empty_bytes;
+static PyObject *__pyx_empty_unicode;
+static int __pyx_lineno;
+static int __pyx_clineno = 0;
+static const char * __pyx_cfilenm= __FILE__;
+static const char *__pyx_filename;
+
+
+static const char *__pyx_f[] = {
+  "core.pyx",
+  "stringsource",
+};
+/* NoFastGil.proto */
+#define __Pyx_PyGILState_Ensure PyGILState_Ensure
+#define __Pyx_PyGILState_Release PyGILState_Release
+#define __Pyx_FastGIL_Remember()
+#define __Pyx_FastGIL_Forget()
+#define __Pyx_FastGilFuncInit()
+
+/* MemviewSliceStruct.proto */
+struct __pyx_memoryview_obj;
+typedef struct {
+  struct __pyx_memoryview_obj *memview;
+  char *data;
+  Py_ssize_t shape[8];
+  Py_ssize_t strides[8];
+  Py_ssize_t suboffsets[8];
+} __Pyx_memviewslice;
+#define __Pyx_MemoryView_Len(m)  (m.shape[0])
+
+/* Atomics.proto */
+#include <pythread.h>
+#ifndef CYTHON_ATOMICS
+    #define CYTHON_ATOMICS 1
+#endif
+#define __PYX_CYTHON_ATOMICS_ENABLED() CYTHON_ATOMICS
+#define __pyx_atomic_int_type int
+#if CYTHON_ATOMICS && (__GNUC__ >= 5 || (__GNUC__ == 4 &&\
+                    (__GNUC_MINOR__ > 1 ||\
+                    (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL__ >= 2))))
+    #define __pyx_atomic_incr_aligned(value) __sync_fetch_and_add(value, 1)
+    #define __pyx_atomic_decr_aligned(value) __sync_fetch_and_sub(value, 1)
+    #ifdef __PYX_DEBUG_ATOMICS
+        #warning "Using GNU atomics"
+    #endif
+#elif CYTHON_ATOMICS && defined(_MSC_VER) && CYTHON_COMPILING_IN_NOGIL
+    #include <intrin.h>
+    #undef __pyx_atomic_int_type
+    #define __pyx_atomic_int_type long
+    #pragma intrinsic (_InterlockedExchangeAdd)
+    #define __pyx_atomic_incr_aligned(value) _InterlockedExchangeAdd(value, 1)
+    #define __pyx_atomic_decr_aligned(value) _InterlockedExchangeAdd(value, -1)
+    #ifdef __PYX_DEBUG_ATOMICS
+        #pragma message ("Using MSVC atomics")
+    #endif
+#else
+    #undef CYTHON_ATOMICS
+    #define CYTHON_ATOMICS 0
+    #ifdef __PYX_DEBUG_ATOMICS
+        #warning "Not using atomics"
+    #endif
+#endif
+typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
+#if CYTHON_ATOMICS
+    #define __pyx_add_acquisition_count(memview)\
+             __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview))
+    #define __pyx_sub_acquisition_count(memview)\
+            __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview))
+#else
+    #define __pyx_add_acquisition_count(memview)\
+            __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+    #define __pyx_sub_acquisition_count(memview)\
+            __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
+#endif
+
+/* ForceInitThreads.proto */
+#ifndef __PYX_FORCE_INIT_THREADS
+  #define __PYX_FORCE_INIT_THREADS 0
+#endif
+
+/* BufferFormatStructs.proto */
+#define IS_UNSIGNED(type) (((type) -1) > 0)
+struct __Pyx_StructField_;
+#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
+typedef struct {
+  const char* name;
+  struct __Pyx_StructField_* fields;
+  size_t size;
+  size_t arraysize[8];
+  int ndim;
+  char typegroup;
+  char is_unsigned;
+  int flags;
+} __Pyx_TypeInfo;
+typedef struct __Pyx_StructField_ {
+  __Pyx_TypeInfo* type;
+  const char* name;
+  size_t offset;
+} __Pyx_StructField;
+typedef struct {
+  __Pyx_StructField* field;
+  size_t parent_offset;
+} __Pyx_BufFmt_StackElem;
+typedef struct {
+  __Pyx_StructField root;
+  __Pyx_BufFmt_StackElem* head;
+  size_t fmt_offset;
+  size_t new_count, enc_count;
+  size_t struct_alignment;
+  int is_complex;
+  char enc_type;
+  char new_packmode;
+  char enc_packmode;
+  char is_valid_array;
+} __Pyx_BufFmt_Context;
+
+
+/*--- Type declarations ---*/
+struct __pyx_array_obj;
+struct __pyx_MemviewEnum_obj;
+struct __pyx_memoryview_obj;
+struct __pyx_memoryviewslice_obj;
+struct __pyx_opt_args_15monotonic_align_4core_maximum_path_each;
+
+/* "monotonic_align/core.pyx":7
+ * @cython.boundscheck(False)
+ * @cython.wraparound(False)
+ * cdef void maximum_path_each(int[:,::1] path, float[:,::1] value, int t_y, int t_x, float max_neg_val=-1e9) nogil:             # <<<<<<<<<<<<<<
+ *   cdef int x
+ *   cdef int y
+ */
+struct __pyx_opt_args_15monotonic_align_4core_maximum_path_each {
+  int __pyx_n;
+  float max_neg_val;
+};
+
+/* "View.MemoryView":106
+ * 
+ * @cname("__pyx_array")
+ * cdef class array:             # <<<<<<<<<<<<<<
+ * 
+ *     cdef:
+ */
+struct __pyx_array_obj {
+  PyObject_HEAD
+  struct __pyx_vtabstruct_array *__pyx_vtab;
+  char *data;
+  Py_ssize_t len;
+  char *format;
+  int ndim;
+  Py_ssize_t *_shape;
+  Py_ssize_t *_strides;
+  Py_ssize_t itemsize;
+  PyObject *mode;
+  PyObject *_format;
+  void (*callback_free_data)(void *);
+  int free_data;
+  int dtype_is_object;
+};
+
+
+/* "View.MemoryView":280
+ * 
+ * @cname('__pyx_MemviewEnum')
+ * cdef class Enum(object):             # <<<<<<<<<<<<<<
+ *     cdef object name
+ *     def __init__(self, name):
+ */
+struct __pyx_MemviewEnum_obj {
+  PyObject_HEAD
+  PyObject *name;
+};
+
+
+/* "View.MemoryView":331
+ * 
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object):             # <<<<<<<<<<<<<<
+ * 
+ *     cdef object obj
+ */
+struct __pyx_memoryview_obj {
+  PyObject_HEAD
+  struct __pyx_vtabstruct_memoryview *__pyx_vtab;
+  PyObject *obj;
+  PyObject *_size;
+  PyObject *_array_interface;
+  PyThread_type_lock lock;
+  __pyx_atomic_int acquisition_count[2];
+  __pyx_atomic_int *acquisition_count_aligned_p;
+  Py_buffer view;
+  int flags;
+  int dtype_is_object;
+  __Pyx_TypeInfo *typeinfo;
+};
+
+
+/* "View.MemoryView":967
+ * 
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview):             # <<<<<<<<<<<<<<
+ *     "Internal class for passing memoryview slices to Python"
+ * 
+ */
+struct __pyx_memoryviewslice_obj {
+  struct __pyx_memoryview_obj __pyx_base;
+  __Pyx_memviewslice from_slice;
+  PyObject *from_object;
+  PyObject *(*to_object_func)(char *);
+  int (*to_dtype_func)(char *, PyObject *);
+};
+
+
+
+/* "View.MemoryView":106
+ * 
+ * @cname("__pyx_array")
+ * cdef class array:             # <<<<<<<<<<<<<<
+ * 
+ *     cdef:
+ */
+
+struct __pyx_vtabstruct_array {
+  PyObject *(*get_memview)(struct __pyx_array_obj *);
+};
+static struct __pyx_vtabstruct_array *__pyx_vtabptr_array;
+
+
+/* "View.MemoryView":331
+ * 
+ * @cname('__pyx_memoryview')
+ * cdef class memoryview(object):             # <<<<<<<<<<<<<<
+ * 
+ *     cdef object obj
+ */
+
+struct __pyx_vtabstruct_memoryview {
+  char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
+  PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
+  PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+  PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
+  PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
+  PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
+  PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
+};
+static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
+
+
+/* "View.MemoryView":967
+ * 
+ * @cname('__pyx_memoryviewslice')
+ * cdef class _memoryviewslice(memoryview):             # <<<<<<<<<<<<<<
+ *     "Internal class for passing memoryview slices to Python"
+ * 
+ */
+
+struct __pyx_vtabstruct__memoryviewslice {
+  struct __pyx_vtabstruct_memoryview __pyx_base;
+};
+static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
+
+/* --- Runtime support code (head) --- */
+/* Refnanny.proto */
+#ifndef CYTHON_REFNANNY
+  #define CYTHON_REFNANNY 0
+#endif
+#if CYTHON_REFNANNY
+  typedef struct {
+    void (*INCREF)(void*, PyObject*, int);
+    void (*DECREF)(void*, PyObject*, int);
+    void (*GOTREF)(void*, PyObject*, int);
+    void (*GIVEREF)(void*, PyObject*, int);
+    void* (*SetupContext)(const char*, int, const char*);
+    void (*FinishContext)(void**);
+  } __Pyx_RefNannyAPIStruct;
+  static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
+  static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname);
+  #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL;
+#ifdef WITH_THREAD
+  #define __Pyx_RefNannySetupContext(name, acquire_gil)\
+          if (acquire_gil) {\
+              PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();\
+              __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\
+              PyGILState_Release(__pyx_gilstate_save);\
+          } else {\
+              __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__);\
+          }
+#else
+  #define __Pyx_RefNannySetupContext(name, acquire_gil)\
+          __pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__)
+#endif
+  #define __Pyx_RefNannyFinishContext()\
+          __Pyx_RefNanny->FinishContext(&__pyx_refnanny)
+  #define __Pyx_INCREF(r)  __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+  #define __Pyx_DECREF(r)  __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+  #define __Pyx_GOTREF(r)  __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+  #define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
+  #define __Pyx_XINCREF(r)  do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
+  #define __Pyx_XDECREF(r)  do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
+  #define __Pyx_XGOTREF(r)  do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
+  #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
+#else
+  #define __Pyx_RefNannyDeclarations
+  #define __Pyx_RefNannySetupContext(name, acquire_gil)
+  #define __Pyx_RefNannyFinishContext()
+  #define __Pyx_INCREF(r) Py_INCREF(r)
+  #define __Pyx_DECREF(r) Py_DECREF(r)
+  #define __Pyx_GOTREF(r)
+  #define __Pyx_GIVEREF(r)
+  #define __Pyx_XINCREF(r) Py_XINCREF(r)
+  #define __Pyx_XDECREF(r) Py_XDECREF(r)
+  #define __Pyx_XGOTREF(r)
+  #define __Pyx_XGIVEREF(r)
+#endif
+#define __Pyx_XDECREF_SET(r, v) do {\
+        PyObject *tmp = (PyObject *) r;\
+        r = v; __Pyx_XDECREF(tmp);\
+    } while (0)
+#define __Pyx_DECREF_SET(r, v) do {\
+        PyObject *tmp = (PyObject *) r;\
+        r = v; __Pyx_DECREF(tmp);\
+    } while (0)
+#define __Pyx_CLEAR(r)    do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
+#define __Pyx_XCLEAR(r)   do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
+
+/* PyObjectGetAttrStr.proto */
+#if CYTHON_USE_TYPE_SLOTS
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name);
+#else
+#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
+#endif
+
+/* GetBuiltinName.proto */
+static PyObject *__Pyx_GetBuiltinName(PyObject *name);
+
+/* MemviewSliceInit.proto */
+#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
+#define __Pyx_MEMVIEW_DIRECT   1
+#define __Pyx_MEMVIEW_PTR      2
+#define __Pyx_MEMVIEW_FULL     4
+#define __Pyx_MEMVIEW_CONTIG   8
+#define __Pyx_MEMVIEW_STRIDED  16
+#define __Pyx_MEMVIEW_FOLLOW   32
+#define __Pyx_IS_C_CONTIG 1
+#define __Pyx_IS_F_CONTIG 2
+static int __Pyx_init_memviewslice(
+                struct __pyx_memoryview_obj *memview,
+                int ndim,
+                __Pyx_memviewslice *memviewslice,
+                int memview_is_new_reference);
+static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
+    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
+    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
+#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
+#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
+#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
+#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
+static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
+
+/* RaiseArgTupleInvalid.proto */
+static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
+    Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
+
+/* RaiseDoubleKeywords.proto */
+static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
+
+/* ParseKeywords.proto */
+static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\
+    PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\
+    const char* function_name);
+
+/* None.proto */
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
+
+/* ArgTypeTest.proto */
+#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\
+    ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\
+        __Pyx__ArgTypeTest(obj, type, name, exact))
+static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact);
+
+/* PyObjectCall.proto */
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
+#else
+#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
+#endif
+
+/* PyThreadStateGet.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_PyThreadState_declare  PyThreadState *__pyx_tstate;
+#define __Pyx_PyThreadState_assign  __pyx_tstate = __Pyx_PyThreadState_Current;
+#define __Pyx_PyErr_Occurred()  __pyx_tstate->curexc_type
+#else
+#define __Pyx_PyThreadState_declare
+#define __Pyx_PyThreadState_assign
+#define __Pyx_PyErr_Occurred()  PyErr_Occurred()
+#endif
+
+/* PyErrFetchRestore.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL)
+#define __Pyx_ErrRestoreWithState(type, value, tb)  __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb)
+#define __Pyx_ErrFetchWithState(type, value, tb)    __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb)
+#define __Pyx_ErrRestore(type, value, tb)  __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb)
+#define __Pyx_ErrFetch(type, value, tb)    __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb)
+static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
+static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
+#if CYTHON_COMPILING_IN_CPYTHON
+#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL))
+#else
+#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc)
+#endif
+#else
+#define __Pyx_PyErr_Clear() PyErr_Clear()
+#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc)
+#define __Pyx_ErrRestoreWithState(type, value, tb)  PyErr_Restore(type, value, tb)
+#define __Pyx_ErrFetchWithState(type, value, tb)  PyErr_Fetch(type, value, tb)
+#define __Pyx_ErrRestoreInState(tstate, type, value, tb)  PyErr_Restore(type, value, tb)
+#define __Pyx_ErrFetchInState(tstate, type, value, tb)  PyErr_Fetch(type, value, tb)
+#define __Pyx_ErrRestore(type, value, tb)  PyErr_Restore(type, value, tb)
+#define __Pyx_ErrFetch(type, value, tb)  PyErr_Fetch(type, value, tb)
+#endif
+
+/* RaiseException.proto */
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
+
+/* PyCFunctionFastCall.proto */
+#if CYTHON_FAST_PYCCALL
+static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs);
+#else
+#define __Pyx_PyCFunction_FastCall(func, args, nargs)  (assert(0), NULL)
+#endif
+
+/* PyFunctionFastCall.proto */
+#if CYTHON_FAST_PYCALL
+#define __Pyx_PyFunction_FastCall(func, args, nargs)\
+    __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL)
+#if 1 || PY_VERSION_HEX < 0x030600B1
+static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs);
+#else
+#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs)
+#endif
+#define __Pyx_BUILD_ASSERT_EXPR(cond)\
+    (sizeof(char [1 - 2*!(cond)]) - 1)
+#ifndef Py_MEMBER_SIZE
+#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member)
+#endif
+#if CYTHON_FAST_PYCALL
+  static size_t __pyx_pyframe_localsplus_offset = 0;
+  #include "frameobject.h"
+#if PY_VERSION_HEX >= 0x030b00a6
+  #ifndef Py_BUILD_CORE
+    #define Py_BUILD_CORE 1
+  #endif
+  #include "internal/pycore_frame.h"
+#endif
+  #define __Pxy_PyFrame_Initialize_Offsets()\
+    ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\
+     (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus)))
+  #define __Pyx_PyFrame_GetLocalsplus(frame)\
+    (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset))
+#endif // CYTHON_FAST_PYCALL
+#endif
+
+/* PyObjectCall2Args.proto */
+static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2);
+
+/* PyObjectCallMethO.proto */
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
+#endif
+
+/* PyObjectCallOneArg.proto */
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
+
+/* IncludeStringH.proto */
+#include <string.h>
+
+/* BytesEquals.proto */
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
+
+/* UnicodeEquals.proto */
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
+
+/* StrEquals.proto */
+#if PY_MAJOR_VERSION >= 3
+#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
+#else
+#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
+#endif
+
+/* DivInt[Py_ssize_t].proto */
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t);
+
+/* UnaryNegOverflows.proto */
+#define UNARY_NEG_WOULD_OVERFLOW(x)\
+        (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))
+
+static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/
+/* GetAttr.proto */
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
+
+/* GetItemInt.proto */
+#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
+    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
+    __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\
+    (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\
+               __Pyx_GetItemInt_Generic(o, to_py_func(i))))
+#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
+    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
+    __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
+    (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+                                                              int wraparound, int boundscheck);
+#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
+    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
+    __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
+    (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+                                                              int wraparound, int boundscheck);
+static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
+                                                     int is_list, int wraparound, int boundscheck);
+
+/* ObjectGetItem.proto */
+#if CYTHON_USE_TYPE_SLOTS
+static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key);
+#else
+#define __Pyx_PyObject_GetItem(obj, key)  PyObject_GetItem(obj, key)
+#endif
+
+/* decode_c_string_utf16.proto */
+static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) {
+    int byteorder = 0;
+    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
+}
+static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) {
+    int byteorder = -1;
+    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
+}
+static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) {
+    int byteorder = 1;
+    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
+}
+
+/* decode_c_string.proto */
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+         const char* encoding, const char* errors,
+         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
+
+/* PyErrExceptionMatches.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err)
+static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err);
+#else
+#define __Pyx_PyErr_ExceptionMatches(err)  PyErr_ExceptionMatches(err)
+#endif
+
+/* GetAttr3.proto */
+static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *);
+
+/* PyDictVersioning.proto */
+#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS
+#define __PYX_DICT_VERSION_INIT  ((PY_UINT64_T) -1)
+#define __PYX_GET_DICT_VERSION(dict)  (((PyDictObject*)(dict))->ma_version_tag)
+#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\
+    (version_var) = __PYX_GET_DICT_VERSION(dict);\
+    (cache_var) = (value);
+#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\
+    static PY_UINT64_T __pyx_dict_version = 0;\
+    static PyObject *__pyx_dict_cached_value = NULL;\
+    if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\
+        (VAR) = __pyx_dict_cached_value;\
+    } else {\
+        (VAR) = __pyx_dict_cached_value = (LOOKUP);\
+        __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\
+    }\
+}
+static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj);
+static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj);
+static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version);
+#else
+#define __PYX_GET_DICT_VERSION(dict)  (0)
+#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)
+#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP)  (VAR) = (LOOKUP);
+#endif
+
+/* GetModuleGlobalName.proto */
+#if CYTHON_USE_DICT_VERSIONS
+#define __Pyx_GetModuleGlobalName(var, name)  do {\
+    static PY_UINT64_T __pyx_dict_version = 0;\
+    static PyObject *__pyx_dict_cached_value = NULL;\
+    (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\
+        (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\
+        __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\
+} while(0)
+#define __Pyx_GetModuleGlobalNameUncached(var, name)  do {\
+    PY_UINT64_T __pyx_dict_version;\
+    PyObject *__pyx_dict_cached_value;\
+    (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\
+} while(0)
+static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value);
+#else
+#define __Pyx_GetModuleGlobalName(var, name)  (var) = __Pyx__GetModuleGlobalName(name)
+#define __Pyx_GetModuleGlobalNameUncached(var, name)  (var) = __Pyx__GetModuleGlobalName(name)
+static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name);
+#endif
+
+/* RaiseTooManyValuesToUnpack.proto */
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
+
+/* RaiseNeedMoreValuesToUnpack.proto */
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
+
+/* RaiseNoneIterError.proto */
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
+
+/* ExtTypeTest.proto */
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
+
+/* GetTopmostException.proto */
+#if CYTHON_USE_EXC_INFO_STACK
+static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate);
+#endif
+
+/* SaveResetException.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_ExceptionSave(type, value, tb)  __Pyx__ExceptionSave(__pyx_tstate, type, value, tb)
+static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
+#define __Pyx_ExceptionReset(type, value, tb)  __Pyx__ExceptionReset(__pyx_tstate, type, value, tb)
+static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
+#else
+#define __Pyx_ExceptionSave(type, value, tb)   PyErr_GetExcInfo(type, value, tb)
+#define __Pyx_ExceptionReset(type, value, tb)  PyErr_SetExcInfo(type, value, tb)
+#endif
+
+/* GetException.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_GetException(type, value, tb)  __Pyx__GetException(__pyx_tstate, type, value, tb)
+static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
+#else
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
+#endif
+
+/* SwapException.proto */
+#if CYTHON_FAST_THREAD_STATE
+#define __Pyx_ExceptionSwap(type, value, tb)  __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb)
+static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
+#else
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
+#endif
+
+/* Import.proto */
+static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
+
+/* FastTypeChecks.proto */
+#if CYTHON_COMPILING_IN_CPYTHON
+#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type)
+static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b);
+static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type);
+static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2);
+#else
+#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
+#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type)
+#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2))
+#endif
+#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception)
+
+static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
+/* ListCompAppend.proto */
+#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
+static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
+    PyListObject* L = (PyListObject*) list;
+    Py_ssize_t len = Py_SIZE(list);
+    if (likely(L->allocated > len)) {
+        Py_INCREF(x);
+        PyList_SET_ITEM(list, len, x);
+        __Pyx_SET_SIZE(list, len + 1);
+        return 0;
+    }
+    return PyList_Append(list, x);
+}
+#else
+#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
+#endif
+
+/* PyIntBinop.proto */
+#if !CYTHON_COMPILING_IN_PYPY
+static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check);
+#else
+#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\
+    (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2))
+#endif
+
+/* ListExtend.proto */
+static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
+#if CYTHON_COMPILING_IN_CPYTHON
+    PyObject* none = _PyList_Extend((PyListObject*)L, v);
+    if (unlikely(!none))
+        return -1;
+    Py_DECREF(none);
+    return 0;
+#else
+    return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
+#endif
+}
+
+/* ListAppend.proto */
+#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
+static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
+    PyListObject* L = (PyListObject*) list;
+    Py_ssize_t len = Py_SIZE(list);
+    if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
+        Py_INCREF(x);
+        PyList_SET_ITEM(list, len, x);
+        __Pyx_SET_SIZE(list, len + 1);
+        return 0;
+    }
+    return PyList_Append(list, x);
+}
+#else
+#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
+#endif
+
+/* DivInt[long].proto */
+static CYTHON_INLINE long __Pyx_div_long(long, long);
+
+/* PySequenceContains.proto */
+static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) {
+    int result = PySequence_Contains(seq, item);
+    return unlikely(result < 0) ? result : (result == (eq == Py_EQ));
+}
+
+/* ImportFrom.proto */
+static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);
+
+/* HasAttr.proto */
+static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *);
+
+/* PyObject_GenericGetAttrNoDict.proto */
+#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name);
+#else
+#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr
+#endif
+
+/* PyObject_GenericGetAttr.proto */
+#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
+static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name);
+#else
+#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr
+#endif
+
+/* SetVTable.proto */
+static int __Pyx_SetVtable(PyObject *dict, void *vtable);
+
+/* PyObjectGetAttrStrNoError.proto */
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name);
+
+/* SetupReduce.proto */
+static int __Pyx_setup_reduce(PyObject* type_obj);
+
+/* CLineInTraceback.proto */
+#ifdef CYTHON_CLINE_IN_TRACEBACK
+#define __Pyx_CLineForTraceback(tstate, c_line)  (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0)
+#else
+static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line);
+#endif
+
+/* CodeObjectCache.proto */
+typedef struct {
+    PyCodeObject* code_object;
+    int code_line;
+} __Pyx_CodeObjectCacheEntry;
+struct __Pyx_CodeObjectCache {
+    int count;
+    int max_count;
+    __Pyx_CodeObjectCacheEntry* entries;
+};
+static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
+static PyCodeObject *__pyx_find_code_object(int code_line);
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
+
+/* AddTraceback.proto */
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+                               int py_line, const char *filename);
+
+#if PY_MAJOR_VERSION < 3
+    static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
+    static void __Pyx_ReleaseBuffer(Py_buffer *view);
+#else
+    #define __Pyx_GetBuffer PyObject_GetBuffer
+    #define __Pyx_ReleaseBuffer PyBuffer_Release
+#endif
+
+
+/* BufferStructDeclare.proto */
+typedef struct {
+  Py_ssize_t shape, strides, suboffsets;
+} __Pyx_Buf_DimInfo;
+typedef struct {
+  size_t refcount;
+  Py_buffer pybuffer;
+} __Pyx_Buffer;
+typedef struct {
+  __Pyx_Buffer *rcbuffer;
+  char *data;
+  __Pyx_Buf_DimInfo diminfo[8];
+} __Pyx_LocalBuf_ND;
+
+/* MemviewSliceIsContig.proto */
+static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim);
+
+/* OverlappingSlices.proto */
+static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
+                                __Pyx_memviewslice *slice2,
+                                int ndim, size_t itemsize);
+
+/* Capsule.proto */
+static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
+
+/* IsLittleEndian.proto */
+static CYTHON_INLINE int __Pyx_Is_Little_Endian(void);
+
+/* BufferFormatCheck.proto */
+static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts);
+static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
+                              __Pyx_BufFmt_StackElem* stack,
+                              __Pyx_TypeInfo* type);
+
+/* TypeInfoCompare.proto */
+static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
+
+/* MemviewSliceValidateAndInit.proto */
+static int __Pyx_ValidateAndInit_memviewslice(
+                int *axes_specs,
+                int c_or_f_flag,
+                int buf_flags,
+                int ndim,
+                __Pyx_TypeInfo *dtype,
+                __Pyx_BufFmt_StackElem stack[],
+                __Pyx_memviewslice *memviewslice,
+                PyObject *original_obj);
+
+/* ObjectToMemviewSlice.proto */
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_int(PyObject *, int writable_flag);
+
+/* ObjectToMemviewSlice.proto */
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_float(PyObject *, int writable_flag);
+
+/* ObjectToMemviewSlice.proto */
+static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_int(PyObject *, int writable_flag);
+
+/* GCCDiagnostics.proto */
+#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6))
+#define __Pyx_HAS_GCC_DIAGNOSTIC
+#endif
+
+/* MemviewSliceCopyTemplate.proto */
+static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+                                 const char *mode, int ndim,
+                                 size_t sizeof_dtype, int contig_flag,
+                                 int dtype_is_object);
+
+/* CIntToPy.proto */
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
+
+/* CIntFromPy.proto */
+static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
+
+/* CIntToPy.proto */
+static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
+
+/* CIntFromPy.proto */
+static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
+
+/* CIntFromPy.proto */
+static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
+
+/* CheckBinaryVersion.proto */
+static int __Pyx_check_binary_version(void);
+
+/* InitStrings.proto */
+static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
+
+static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/
+static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
+static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
+static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
+static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
+
+/* Module declarations from 'cython.view' */
+
+/* Module declarations from 'cython' */
+
+/* Module declarations from 'monotonic_align.core' */
+static PyTypeObject *__pyx_array_type = 0;
+static PyTypeObject *__pyx_MemviewEnum_type = 0;
+static PyTypeObject *__pyx_memoryview_type = 0;
+static PyTypeObject *__pyx_memoryviewslice_type = 0;
+static PyObject *generic = 0;
+static PyObject *strided = 0;
+static PyObject *indirect = 0;
+static PyObject *contiguous = 0;
+static PyObject *indirect_contiguous = 0;
+static int __pyx_memoryview_thread_locks_used;
+static PyThread_type_lock __pyx_memoryview_thread_locks[8];
+static void __pyx_f_15monotonic_align_4core_maximum_path_each(__Pyx_memviewslice, __Pyx_memviewslice, int, int, struct __pyx_opt_args_15monotonic_align_4core_maximum_path_each *__pyx_optional_args); /*proto*/
+static void __pyx_f_15monotonic_align_4core_maximum_path_c(__Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, int __pyx_skip_dispatch); /*proto*/
+static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
+static void *__pyx_align_pointer(void *, size_t); /*proto*/
+static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
+static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
+static PyObject *_unellipsify(PyObject *, int); /*proto*/
+static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
+static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
+static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
+static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
+static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
+static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
+static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
+static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
+static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
+static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
+static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
+static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
+static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
+static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
+static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
+static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
+static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/
+static __Pyx_TypeInfo __Pyx_TypeInfo_int = { "int", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 };
+static __Pyx_TypeInfo __Pyx_TypeInfo_float = { "float", NULL, sizeof(float), { 0 }, 0, 'R', 0, 0 };
+#define __Pyx_MODULE_NAME "monotonic_align.core"
+extern int __pyx_module_is_main_monotonic_align__core;
+int __pyx_module_is_main_monotonic_align__core = 0;
+
+/* Implementation of 'monotonic_align.core' */
+static PyObject *__pyx_builtin_range;
+static PyObject *__pyx_builtin_ValueError;
+static PyObject *__pyx_builtin_MemoryError;
+static PyObject *__pyx_builtin_enumerate;
+static PyObject *__pyx_builtin_TypeError;
+static PyObject *__pyx_builtin_Ellipsis;
+static PyObject *__pyx_builtin_id;
+static PyObject *__pyx_builtin_IndexError;
+static const char __pyx_k_O[] = "O";
+static const char __pyx_k_c[] = "c";
+static const char __pyx_k_id[] = "id";
+static const char __pyx_k_new[] = "__new__";
+static const char __pyx_k_obj[] = "obj";
+static const char __pyx_k_base[] = "base";
+static const char __pyx_k_dict[] = "__dict__";
+static const char __pyx_k_main[] = "__main__";
+static const char __pyx_k_mode[] = "mode";
+static const char __pyx_k_name[] = "name";
+static const char __pyx_k_ndim[] = "ndim";
+static const char __pyx_k_pack[] = "pack";
+static const char __pyx_k_size[] = "size";
+static const char __pyx_k_step[] = "step";
+static const char __pyx_k_stop[] = "stop";
+static const char __pyx_k_t_xs[] = "t_xs";
+static const char __pyx_k_t_ys[] = "t_ys";
+static const char __pyx_k_test[] = "__test__";
+static const char __pyx_k_ASCII[] = "ASCII";
+static const char __pyx_k_class[] = "__class__";
+static const char __pyx_k_error[] = "error";
+static const char __pyx_k_flags[] = "flags";
+static const char __pyx_k_paths[] = "paths";
+static const char __pyx_k_range[] = "range";
+static const char __pyx_k_shape[] = "shape";
+static const char __pyx_k_start[] = "start";
+static const char __pyx_k_encode[] = "encode";
+static const char __pyx_k_format[] = "format";
+static const char __pyx_k_import[] = "__import__";
+static const char __pyx_k_name_2[] = "__name__";
+static const char __pyx_k_pickle[] = "pickle";
+static const char __pyx_k_reduce[] = "__reduce__";
+static const char __pyx_k_struct[] = "struct";
+static const char __pyx_k_unpack[] = "unpack";
+static const char __pyx_k_update[] = "update";
+static const char __pyx_k_values[] = "values";
+static const char __pyx_k_fortran[] = "fortran";
+static const char __pyx_k_memview[] = "memview";
+static const char __pyx_k_Ellipsis[] = "Ellipsis";
+static const char __pyx_k_getstate[] = "__getstate__";
+static const char __pyx_k_itemsize[] = "itemsize";
+static const char __pyx_k_pyx_type[] = "__pyx_type";
+static const char __pyx_k_setstate[] = "__setstate__";
+static const char __pyx_k_TypeError[] = "TypeError";
+static const char __pyx_k_enumerate[] = "enumerate";
+static const char __pyx_k_pyx_state[] = "__pyx_state";
+static const char __pyx_k_reduce_ex[] = "__reduce_ex__";
+static const char __pyx_k_IndexError[] = "IndexError";
+static const char __pyx_k_ValueError[] = "ValueError";
+static const char __pyx_k_pyx_result[] = "__pyx_result";
+static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
+static const char __pyx_k_MemoryError[] = "MemoryError";
+static const char __pyx_k_PickleError[] = "PickleError";
+static const char __pyx_k_pyx_checksum[] = "__pyx_checksum";
+static const char __pyx_k_stringsource[] = "stringsource";
+static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
+static const char __pyx_k_reduce_cython[] = "__reduce_cython__";
+static const char __pyx_k_View_MemoryView[] = "View.MemoryView";
+static const char __pyx_k_allocate_buffer[] = "allocate_buffer";
+static const char __pyx_k_dtype_is_object[] = "dtype_is_object";
+static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError";
+static const char __pyx_k_setstate_cython[] = "__setstate_cython__";
+static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum";
+static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback";
+static const char __pyx_k_strided_and_direct[] = "<strided and direct>";
+static const char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
+static const char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
+static const char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
+static const char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
+static const char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
+static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
+static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
+static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
+static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
+static const char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
+static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
+static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
+static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview";
+static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview";
+static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
+static const char __pyx_k_Incompatible_checksums_0x_x_vs_0[] = "Incompatible checksums (0x%x vs (0xb068931, 0x82a3537, 0x6ae9995) = (name))";
+static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
+static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
+static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
+static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
+static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
+static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__";
+static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
+static PyObject *__pyx_n_s_ASCII;
+static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
+static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
+static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor;
+static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi;
+static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
+static PyObject *__pyx_n_s_Ellipsis;
+static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
+static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0;
+static PyObject *__pyx_n_s_IndexError;
+static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
+static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
+static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
+static PyObject *__pyx_n_s_MemoryError;
+static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
+static PyObject *__pyx_kp_s_MemoryView_of_r_object;
+static PyObject *__pyx_n_b_O;
+static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
+static PyObject *__pyx_n_s_PickleError;
+static PyObject *__pyx_n_s_TypeError;
+static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
+static PyObject *__pyx_n_s_ValueError;
+static PyObject *__pyx_n_s_View_MemoryView;
+static PyObject *__pyx_n_s_allocate_buffer;
+static PyObject *__pyx_n_s_base;
+static PyObject *__pyx_n_s_c;
+static PyObject *__pyx_n_u_c;
+static PyObject *__pyx_n_s_class;
+static PyObject *__pyx_n_s_cline_in_traceback;
+static PyObject *__pyx_kp_s_contiguous_and_direct;
+static PyObject *__pyx_kp_s_contiguous_and_indirect;
+static PyObject *__pyx_n_s_dict;
+static PyObject *__pyx_n_s_dtype_is_object;
+static PyObject *__pyx_n_s_encode;
+static PyObject *__pyx_n_s_enumerate;
+static PyObject *__pyx_n_s_error;
+static PyObject *__pyx_n_s_flags;
+static PyObject *__pyx_n_s_format;
+static PyObject *__pyx_n_s_fortran;
+static PyObject *__pyx_n_u_fortran;
+static PyObject *__pyx_n_s_getstate;
+static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
+static PyObject *__pyx_n_s_id;
+static PyObject *__pyx_n_s_import;
+static PyObject *__pyx_n_s_itemsize;
+static PyObject *__pyx_kp_s_itemsize_0_for_cython_array;
+static PyObject *__pyx_n_s_main;
+static PyObject *__pyx_n_s_memview;
+static PyObject *__pyx_n_s_mode;
+static PyObject *__pyx_n_s_name;
+static PyObject *__pyx_n_s_name_2;
+static PyObject *__pyx_n_s_ndim;
+static PyObject *__pyx_n_s_new;
+static PyObject *__pyx_kp_s_no_default___reduce___due_to_non;
+static PyObject *__pyx_n_s_obj;
+static PyObject *__pyx_n_s_pack;
+static PyObject *__pyx_n_s_paths;
+static PyObject *__pyx_n_s_pickle;
+static PyObject *__pyx_n_s_pyx_PickleError;
+static PyObject *__pyx_n_s_pyx_checksum;
+static PyObject *__pyx_n_s_pyx_getbuffer;
+static PyObject *__pyx_n_s_pyx_result;
+static PyObject *__pyx_n_s_pyx_state;
+static PyObject *__pyx_n_s_pyx_type;
+static PyObject *__pyx_n_s_pyx_unpickle_Enum;
+static PyObject *__pyx_n_s_pyx_vtable;
+static PyObject *__pyx_n_s_range;
+static PyObject *__pyx_n_s_reduce;
+static PyObject *__pyx_n_s_reduce_cython;
+static PyObject *__pyx_n_s_reduce_ex;
+static PyObject *__pyx_n_s_setstate;
+static PyObject *__pyx_n_s_setstate_cython;
+static PyObject *__pyx_n_s_shape;
+static PyObject *__pyx_n_s_size;
+static PyObject *__pyx_n_s_start;
+static PyObject *__pyx_n_s_step;
+static PyObject *__pyx_n_s_stop;
+static PyObject *__pyx_kp_s_strided_and_direct;
+static PyObject *__pyx_kp_s_strided_and_direct_or_indirect;
+static PyObject *__pyx_kp_s_strided_and_indirect;
+static PyObject *__pyx_kp_s_stringsource;
+static PyObject *__pyx_n_s_struct;
+static PyObject *__pyx_n_s_t_xs;
+static PyObject *__pyx_n_s_t_ys;
+static PyObject *__pyx_n_s_test;
+static PyObject *__pyx_kp_s_unable_to_allocate_array_data;
+static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str;
+static PyObject *__pyx_n_s_unpack;
+static PyObject *__pyx_n_s_update;
+static PyObject *__pyx_n_s_values;
+static PyObject *__pyx_pf_15monotonic_align_4core_maximum_path_c(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_paths, __Pyx_memviewslice __pyx_v_values, __Pyx_memviewslice __pyx_v_t_ys, __Pyx_memviewslice __pyx_v_t_xs); /* proto */
+static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
+static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
+static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
+static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
+static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
+static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
+static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
+static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
+static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
+static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
+static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
+static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
+static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
+static PyObject *__pyx_int_0;
+static PyObject *__pyx_int_1;
+static PyObject *__pyx_int_112105877;
+static PyObject *__pyx_int_136983863;
+static PyObject *__pyx_int_184977713;
+static PyObject *__pyx_int_neg_1;
+static float __pyx_k_;
+static PyObject *__pyx_tuple__2;
+static PyObject *__pyx_tuple__3;
+static PyObject *__pyx_tuple__4;
+static PyObject *__pyx_tuple__5;
+static PyObject *__pyx_tuple__6;
+static PyObject *__pyx_tuple__7;
+static PyObject *__pyx_tuple__8;
+static PyObject *__pyx_tuple__9;
+static PyObject *__pyx_slice__16;
+static PyObject *__pyx_tuple__10;
+static PyObject *__pyx_tuple__11;
+static PyObject *__pyx_tuple__12;
+static PyObject *__pyx_tuple__13;
+static PyObject *__pyx_tuple__14;
+static PyObject *__pyx_tuple__15;
+static PyObject *__pyx_tuple__17;
+static PyObject *__pyx_tuple__18;
+static PyObject *__pyx_tuple__19;
+static PyObject *__pyx_tuple__20;
+static PyObject *__pyx_tuple__21;
+static PyObject *__pyx_tuple__22;
+static PyObject *__pyx_tuple__23;
+static PyObject *__pyx_tuple__24;
+static PyObject *__pyx_tuple__25;
+static PyObject *__pyx_tuple__26;
+static PyObject *__pyx_codeobj__27;
+/* Late includes */
+
+/* "monotonic_align/core.pyx":7
+ * @cython.boundscheck(False)
+ * @cython.wraparound(False)
+ * cdef void maximum_path_each(int[:,::1] path, float[:,::1] value, int t_y, int t_x, float max_neg_val=-1e9) nogil:             # <<<<<<<<<<<<<<
+ *   cdef int x
+ *   cdef int y
+ */
+
+static void __pyx_f_15monotonic_align_4core_maximum_path_each(__Pyx_memviewslice __pyx_v_path, __Pyx_memviewslice __pyx_v_value, int __pyx_v_t_y, int __pyx_v_t_x, struct __pyx_opt_args_15monotonic_align_4core_maximum_path_each *__pyx_optional_args) {
+  float __pyx_v_max_neg_val = __pyx_k_;
+  int __pyx_v_x;
+  int __pyx_v_y;
+  float __pyx_v_v_prev;
+  float __pyx_v_v_cur;
+  int __pyx_v_index;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  long __pyx_t_4;
+  int __pyx_t_5;
+  long __pyx_t_6;
+  long __pyx_t_7;
+  int __pyx_t_8;
+  Py_ssize_t __pyx_t_9;
+  Py_ssize_t __pyx_t_10;
+  float __pyx_t_11;
+  float __pyx_t_12;
+  float __pyx_t_13;
+  int __pyx_t_14;
+  Py_ssize_t __pyx_t_15;
+  Py_ssize_t __pyx_t_16;
+  if (__pyx_optional_args) {
+    if (__pyx_optional_args->__pyx_n > 0) {
+      __pyx_v_max_neg_val = __pyx_optional_args->max_neg_val;
+    }
+  }
+
+  /* "monotonic_align/core.pyx":13
+ *   cdef float v_cur
+ *   cdef float tmp
+ *   cdef int index = t_x - 1             # <<<<<<<<<<<<<<
+ * 
+ *   for y in range(t_y):
+ */
+  __pyx_v_index = (__pyx_v_t_x - 1);
+
+  /* "monotonic_align/core.pyx":15
+ *   cdef int index = t_x - 1
+ * 
+ *   for y in range(t_y):             # <<<<<<<<<<<<<<
+ *     for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
+ *       if x == y:
+ */
+  __pyx_t_1 = __pyx_v_t_y;
+  __pyx_t_2 = __pyx_t_1;
+  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+    __pyx_v_y = __pyx_t_3;
+
+    /* "monotonic_align/core.pyx":16
+ * 
+ *   for y in range(t_y):
+ *     for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):             # <<<<<<<<<<<<<<
+ *       if x == y:
+ *         v_cur = max_neg_val
+ */
+    __pyx_t_4 = (__pyx_v_y + 1);
+    __pyx_t_5 = __pyx_v_t_x;
+    if (((__pyx_t_4 < __pyx_t_5) != 0)) {
+      __pyx_t_6 = __pyx_t_4;
+    } else {
+      __pyx_t_6 = __pyx_t_5;
+    }
+    __pyx_t_4 = __pyx_t_6;
+    __pyx_t_5 = ((__pyx_v_t_x + __pyx_v_y) - __pyx_v_t_y);
+    __pyx_t_6 = 0;
+    if (((__pyx_t_5 > __pyx_t_6) != 0)) {
+      __pyx_t_7 = __pyx_t_5;
+    } else {
+      __pyx_t_7 = __pyx_t_6;
+    }
+    __pyx_t_6 = __pyx_t_4;
+    for (__pyx_t_5 = __pyx_t_7; __pyx_t_5 < __pyx_t_6; __pyx_t_5+=1) {
+      __pyx_v_x = __pyx_t_5;
+
+      /* "monotonic_align/core.pyx":17
+ *   for y in range(t_y):
+ *     for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
+ *       if x == y:             # <<<<<<<<<<<<<<
+ *         v_cur = max_neg_val
+ *       else:
+ */
+      __pyx_t_8 = ((__pyx_v_x == __pyx_v_y) != 0);
+      if (__pyx_t_8) {
+
+        /* "monotonic_align/core.pyx":18
+ *     for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
+ *       if x == y:
+ *         v_cur = max_neg_val             # <<<<<<<<<<<<<<
+ *       else:
+ *         v_cur = value[y-1, x]
+ */
+        __pyx_v_v_cur = __pyx_v_max_neg_val;
+
+        /* "monotonic_align/core.pyx":17
+ *   for y in range(t_y):
+ *     for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
+ *       if x == y:             # <<<<<<<<<<<<<<
+ *         v_cur = max_neg_val
+ *       else:
+ */
+        goto __pyx_L7;
+      }
+
+      /* "monotonic_align/core.pyx":20
+ *         v_cur = max_neg_val
+ *       else:
+ *         v_cur = value[y-1, x]             # <<<<<<<<<<<<<<
+ *       if x == 0:
+ *         if y == 0:
+ */
+      /*else*/ {
+        __pyx_t_9 = (__pyx_v_y - 1);
+        __pyx_t_10 = __pyx_v_x;
+        __pyx_v_v_cur = (*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_value.data + __pyx_t_9 * __pyx_v_value.strides[0]) )) + __pyx_t_10)) )));
+      }
+      __pyx_L7:;
+
+      /* "monotonic_align/core.pyx":21
+ *       else:
+ *         v_cur = value[y-1, x]
+ *       if x == 0:             # <<<<<<<<<<<<<<
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+      __pyx_t_8 = ((__pyx_v_x == 0) != 0);
+      if (__pyx_t_8) {
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+          /* "monotonic_align/core.pyx":23
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+ *         if y == 0:
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+
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+ *           v_prev = 0.
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+          goto __pyx_L9;
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+
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+ *         else:
+ *           v_prev = max_neg_val             # <<<<<<<<<<<<<<
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+        __pyx_L9:;
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+        /* "monotonic_align/core.pyx":21
+ *       else:
+ *         v_cur = value[y-1, x]
+ *       if x == 0:             # <<<<<<<<<<<<<<
+ *         if y == 0:
+ *           v_prev = 0.
+ */
+        goto __pyx_L8;
+      }
+
+      /* "monotonic_align/core.pyx":27
+ *           v_prev = max_neg_val
+ *       else:
+ *         v_prev = value[y-1, x-1]             # <<<<<<<<<<<<<<
+ *       value[y, x] += max(v_prev, v_cur)
+ * 
+ */
+      /*else*/ {
+        __pyx_t_10 = (__pyx_v_y - 1);
+        __pyx_t_9 = (__pyx_v_x - 1);
+        __pyx_v_v_prev = (*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_value.data + __pyx_t_10 * __pyx_v_value.strides[0]) )) + __pyx_t_9)) )));
+      }
+      __pyx_L8:;
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+      /* "monotonic_align/core.pyx":28
+ *       else:
+ *         v_prev = value[y-1, x-1]
+ *       value[y, x] += max(v_prev, v_cur)             # <<<<<<<<<<<<<<
+ * 
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+ */
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+      __pyx_t_12 = __pyx_v_v_prev;
+      if (((__pyx_t_11 > __pyx_t_12) != 0)) {
+        __pyx_t_13 = __pyx_t_11;
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+      __pyx_t_9 = __pyx_v_y;
+      __pyx_t_10 = __pyx_v_x;
+      *((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_value.data + __pyx_t_9 * __pyx_v_value.strides[0]) )) + __pyx_t_10)) )) += __pyx_t_13;
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+    /* "monotonic_align/core.pyx":31
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+    __pyx_t_9 = __pyx_v_index;
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+    if (__pyx_t_14) {
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+      goto __pyx_L13_bool_binop_done;
+    }
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+    if (!__pyx_t_14) {
+    } else {
+      __pyx_t_8 = __pyx_t_14;
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+    __pyx_t_15 = (__pyx_v_y - 1);
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+    __pyx_t_8 = __pyx_t_14;
+    __pyx_L13_bool_binop_done:;
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+      /* "monotonic_align/core.pyx":33
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+ * 
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+  }
+
+  /* "monotonic_align/core.pyx":7
+ * @cython.boundscheck(False)
+ * @cython.wraparound(False)
+ * cdef void maximum_path_each(int[:,::1] path, float[:,::1] value, int t_y, int t_x, float max_neg_val=-1e9) nogil:             # <<<<<<<<<<<<<<
+ *   cdef int x
+ *   cdef int y
+ */
+
+  /* function exit code */
+}
+
+/* "monotonic_align/core.pyx":38
+ * @cython.boundscheck(False)
+ * @cython.wraparound(False)
+ * cpdef void maximum_path_c(int[:,:,::1] paths, float[:,:,::1] values, int[::1] t_ys, int[::1] t_xs) nogil:             # <<<<<<<<<<<<<<
+ *   cdef int b = paths.shape[0]
+ *   cdef int i
+ */
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+static PyObject *__pyx_pw_15monotonic_align_4core_1maximum_path_c(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
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+  CYTHON_UNUSED int __pyx_v_b;
+  int __pyx_v_i;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
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+  __Pyx_memviewslice __pyx_t_5 = { 0, 0, { 0 }, { 0 }, { 0 } };
+  Py_ssize_t __pyx_t_6;
+  Py_ssize_t __pyx_t_7;
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+  /* "monotonic_align/core.pyx":39
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+ *   cdef int b = paths.shape[0]             # <<<<<<<<<<<<<<
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+      PyThreadState *_save;
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+}
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+__pyx_t_6 = __pyx_v_i;
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+  /* function exit code */
+}
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+      __pyx_t_11 = __pyx_memoryview_slice_memviewslice(__pyx_v_p_dst, (__pyx_v_p_src->shape[__pyx_v_dim]), (__pyx_v_p_src->strides[__pyx_v_dim]), (__pyx_v_p_src->suboffsets[__pyx_v_dim]), __pyx_v_dim, __pyx_v_new_ndim, __pyx_v_p_suboffset_dim, __pyx_v_start, __pyx_v_stop, __pyx_v_step, __pyx_v_have_start, __pyx_v_have_stop, __pyx_v_have_step, 1); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(1, 770, __pyx_L1_error)
+
+      /* "View.MemoryView":776
+ *                 have_start, have_stop, have_step,
+ *                 True)
+ *             new_ndim += 1             # <<<<<<<<<<<<<<
+ * 
+ *     if isinstance(memview, _memoryviewslice):
+ */
+      __pyx_v_new_ndim = (__pyx_v_new_ndim + 1);
+    }
+    __pyx_L6:;
+
+    /* "View.MemoryView":748
+ *     cdef bint have_start, have_stop, have_step
+ * 
+ *     for dim, index in enumerate(indices):             # <<<<<<<<<<<<<<
+ *         if PyIndex_Check(index):
+ *             slice_memviewslice(
+ */
+  }
+  __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
+
+  /* "View.MemoryView":778
+ *             new_ndim += 1
+ * 
+ *     if isinstance(memview, _memoryviewslice):             # <<<<<<<<<<<<<<
+ *         return memoryview_fromslice(dst, new_ndim,
+ *                                     memviewsliceobj.to_object_func,
+ */
+  __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); 
+  __pyx_t_2 = (__pyx_t_1 != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":779
+ * 
+ *     if isinstance(memview, _memoryviewslice):
+ *         return memoryview_fromslice(dst, new_ndim,             # <<<<<<<<<<<<<<
+ *                                     memviewsliceobj.to_object_func,
+ *                                     memviewsliceobj.to_dtype_func,
+ */
+    __Pyx_XDECREF(((PyObject *)__pyx_r));
+
+    /* "View.MemoryView":780
+ *     if isinstance(memview, _memoryviewslice):
+ *         return memoryview_fromslice(dst, new_ndim,
+ *                                     memviewsliceobj.to_object_func,             # <<<<<<<<<<<<<<
+ *                                     memviewsliceobj.to_dtype_func,
+ *                                     memview.dtype_is_object)
+ */
+    if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(1, 780, __pyx_L1_error) }
+
+    /* "View.MemoryView":781
+ *         return memoryview_fromslice(dst, new_ndim,
+ *                                     memviewsliceobj.to_object_func,
+ *                                     memviewsliceobj.to_dtype_func,             # <<<<<<<<<<<<<<
+ *                                     memview.dtype_is_object)
+ *     else:
+ */
+    if (unlikely(!__pyx_v_memviewsliceobj)) { __Pyx_RaiseUnboundLocalError("memviewsliceobj"); __PYX_ERR(1, 781, __pyx_L1_error) }
+
+    /* "View.MemoryView":779
+ * 
+ *     if isinstance(memview, _memoryviewslice):
+ *         return memoryview_fromslice(dst, new_ndim,             # <<<<<<<<<<<<<<
+ *                                     memviewsliceobj.to_object_func,
+ *                                     memviewsliceobj.to_dtype_func,
+ */
+    __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, __pyx_v_memviewsliceobj->to_object_func, __pyx_v_memviewsliceobj->to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) __PYX_ERR(1, 779, __pyx_L1_error)
+    __Pyx_GOTREF(__pyx_t_3);
+    if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(1, 779, __pyx_L1_error)
+    __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3);
+    __pyx_t_3 = 0;
+    goto __pyx_L0;
+
+    /* "View.MemoryView":778
+ *             new_ndim += 1
+ * 
+ *     if isinstance(memview, _memoryviewslice):             # <<<<<<<<<<<<<<
+ *         return memoryview_fromslice(dst, new_ndim,
+ *                                     memviewsliceobj.to_object_func,
+ */
+  }
+
+  /* "View.MemoryView":784
+ *                                     memview.dtype_is_object)
+ *     else:
+ *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,             # <<<<<<<<<<<<<<
+ *                                     memview.dtype_is_object)
+ * 
+ */
+  /*else*/ {
+    __Pyx_XDECREF(((PyObject *)__pyx_r));
+
+    /* "View.MemoryView":785
+ *     else:
+ *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,
+ *                                     memview.dtype_is_object)             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+    __pyx_t_3 = __pyx_memoryview_fromslice(__pyx_v_dst, __pyx_v_new_ndim, NULL, NULL, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_3)) __PYX_ERR(1, 784, __pyx_L1_error)
+    __Pyx_GOTREF(__pyx_t_3);
+
+    /* "View.MemoryView":784
+ *                                     memview.dtype_is_object)
+ *     else:
+ *         return memoryview_fromslice(dst, new_ndim, NULL, NULL,             # <<<<<<<<<<<<<<
+ *                                     memview.dtype_is_object)
+ * 
+ */
+    if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(1, 784, __pyx_L1_error)
+    __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3);
+    __pyx_t_3 = 0;
+    goto __pyx_L0;
+  }
+
+  /* "View.MemoryView":712
+ * 
+ * @cname('__pyx_memview_slice')
+ * cdef memoryview memview_slice(memoryview memview, object indices):             # <<<<<<<<<<<<<<
+ *     cdef int new_ndim = 0, suboffset_dim = -1, dim
+ *     cdef bint negative_step
+ */
+
+  /* function exit code */
+  __pyx_L1_error:;
+  __Pyx_XDECREF(__pyx_t_3);
+  __Pyx_XDECREF(__pyx_t_9);
+  __Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename);
+  __pyx_r = 0;
+  __pyx_L0:;
+  __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj);
+  __Pyx_XDECREF(__pyx_v_index);
+  __Pyx_XGIVEREF((PyObject *)__pyx_r);
+  __Pyx_RefNannyFinishContext();
+  return __pyx_r;
+}
+
+/* "View.MemoryView":809
+ * 
+ * @cname('__pyx_memoryview_slice_memviewslice')
+ * cdef int slice_memviewslice(             # <<<<<<<<<<<<<<
+ *         __Pyx_memviewslice *dst,
+ *         Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
+ */
+
+static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) {
+  Py_ssize_t __pyx_v_new_shape;
+  int __pyx_v_negative_step;
+  int __pyx_r;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  int __pyx_lineno = 0;
+  const char *__pyx_filename = NULL;
+  int __pyx_clineno = 0;
+
+  /* "View.MemoryView":829
+ *     cdef bint negative_step
+ * 
+ *     if not is_slice:             # <<<<<<<<<<<<<<
+ * 
+ *         if start < 0:
+ */
+  __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0);
+  if (__pyx_t_1) {
+
+    /* "View.MemoryView":831
+ *     if not is_slice:
+ * 
+ *         if start < 0:             # <<<<<<<<<<<<<<
+ *             start += shape
+ *         if not 0 <= start < shape:
+ */
+    __pyx_t_1 = ((__pyx_v_start < 0) != 0);
+    if (__pyx_t_1) {
+
+      /* "View.MemoryView":832
+ * 
+ *         if start < 0:
+ *             start += shape             # <<<<<<<<<<<<<<
+ *         if not 0 <= start < shape:
+ *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
+ */
+      __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
+
+      /* "View.MemoryView":831
+ *     if not is_slice:
+ * 
+ *         if start < 0:             # <<<<<<<<<<<<<<
+ *             start += shape
+ *         if not 0 <= start < shape:
+ */
+    }
+
+    /* "View.MemoryView":833
+ *         if start < 0:
+ *             start += shape
+ *         if not 0 <= start < shape:             # <<<<<<<<<<<<<<
+ *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
+ *     else:
+ */
+    __pyx_t_1 = (0 <= __pyx_v_start);
+    if (__pyx_t_1) {
+      __pyx_t_1 = (__pyx_v_start < __pyx_v_shape);
+    }
+    __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":834
+ *             start += shape
+ *         if not 0 <= start < shape:
+ *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)             # <<<<<<<<<<<<<<
+ *     else:
+ * 
+ */
+      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 834, __pyx_L1_error)
+
+      /* "View.MemoryView":833
+ *         if start < 0:
+ *             start += shape
+ *         if not 0 <= start < shape:             # <<<<<<<<<<<<<<
+ *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
+ *     else:
+ */
+    }
+
+    /* "View.MemoryView":829
+ *     cdef bint negative_step
+ * 
+ *     if not is_slice:             # <<<<<<<<<<<<<<
+ * 
+ *         if start < 0:
+ */
+    goto __pyx_L3;
+  }
+
+  /* "View.MemoryView":837
+ *     else:
+ * 
+ *         negative_step = have_step != 0 and step < 0             # <<<<<<<<<<<<<<
+ * 
+ *         if have_step and step == 0:
+ */
+  /*else*/ {
+    __pyx_t_1 = ((__pyx_v_have_step != 0) != 0);
+    if (__pyx_t_1) {
+    } else {
+      __pyx_t_2 = __pyx_t_1;
+      goto __pyx_L6_bool_binop_done;
+    }
+    __pyx_t_1 = ((__pyx_v_step < 0) != 0);
+    __pyx_t_2 = __pyx_t_1;
+    __pyx_L6_bool_binop_done:;
+    __pyx_v_negative_step = __pyx_t_2;
+
+    /* "View.MemoryView":839
+ *         negative_step = have_step != 0 and step < 0
+ * 
+ *         if have_step and step == 0:             # <<<<<<<<<<<<<<
+ *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
+ * 
+ */
+    __pyx_t_1 = (__pyx_v_have_step != 0);
+    if (__pyx_t_1) {
+    } else {
+      __pyx_t_2 = __pyx_t_1;
+      goto __pyx_L9_bool_binop_done;
+    }
+    __pyx_t_1 = ((__pyx_v_step == 0) != 0);
+    __pyx_t_2 = __pyx_t_1;
+    __pyx_L9_bool_binop_done:;
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":840
+ * 
+ *         if have_step and step == 0:
+ *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 840, __pyx_L1_error)
+
+      /* "View.MemoryView":839
+ *         negative_step = have_step != 0 and step < 0
+ * 
+ *         if have_step and step == 0:             # <<<<<<<<<<<<<<
+ *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
+ * 
+ */
+    }
+
+    /* "View.MemoryView":843
+ * 
+ * 
+ *         if have_start:             # <<<<<<<<<<<<<<
+ *             if start < 0:
+ *                 start += shape
+ */
+    __pyx_t_2 = (__pyx_v_have_start != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":844
+ * 
+ *         if have_start:
+ *             if start < 0:             # <<<<<<<<<<<<<<
+ *                 start += shape
+ *                 if start < 0:
+ */
+      __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":845
+ *         if have_start:
+ *             if start < 0:
+ *                 start += shape             # <<<<<<<<<<<<<<
+ *                 if start < 0:
+ *                     start = 0
+ */
+        __pyx_v_start = (__pyx_v_start + __pyx_v_shape);
+
+        /* "View.MemoryView":846
+ *             if start < 0:
+ *                 start += shape
+ *                 if start < 0:             # <<<<<<<<<<<<<<
+ *                     start = 0
+ *             elif start >= shape:
+ */
+        __pyx_t_2 = ((__pyx_v_start < 0) != 0);
+        if (__pyx_t_2) {
+
+          /* "View.MemoryView":847
+ *                 start += shape
+ *                 if start < 0:
+ *                     start = 0             # <<<<<<<<<<<<<<
+ *             elif start >= shape:
+ *                 if negative_step:
+ */
+          __pyx_v_start = 0;
+
+          /* "View.MemoryView":846
+ *             if start < 0:
+ *                 start += shape
+ *                 if start < 0:             # <<<<<<<<<<<<<<
+ *                     start = 0
+ *             elif start >= shape:
+ */
+        }
+
+        /* "View.MemoryView":844
+ * 
+ *         if have_start:
+ *             if start < 0:             # <<<<<<<<<<<<<<
+ *                 start += shape
+ *                 if start < 0:
+ */
+        goto __pyx_L12;
+      }
+
+      /* "View.MemoryView":848
+ *                 if start < 0:
+ *                     start = 0
+ *             elif start >= shape:             # <<<<<<<<<<<<<<
+ *                 if negative_step:
+ *                     start = shape - 1
+ */
+      __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":849
+ *                     start = 0
+ *             elif start >= shape:
+ *                 if negative_step:             # <<<<<<<<<<<<<<
+ *                     start = shape - 1
+ *                 else:
+ */
+        __pyx_t_2 = (__pyx_v_negative_step != 0);
+        if (__pyx_t_2) {
+
+          /* "View.MemoryView":850
+ *             elif start >= shape:
+ *                 if negative_step:
+ *                     start = shape - 1             # <<<<<<<<<<<<<<
+ *                 else:
+ *                     start = shape
+ */
+          __pyx_v_start = (__pyx_v_shape - 1);
+
+          /* "View.MemoryView":849
+ *                     start = 0
+ *             elif start >= shape:
+ *                 if negative_step:             # <<<<<<<<<<<<<<
+ *                     start = shape - 1
+ *                 else:
+ */
+          goto __pyx_L14;
+        }
+
+        /* "View.MemoryView":852
+ *                     start = shape - 1
+ *                 else:
+ *                     start = shape             # <<<<<<<<<<<<<<
+ *         else:
+ *             if negative_step:
+ */
+        /*else*/ {
+          __pyx_v_start = __pyx_v_shape;
+        }
+        __pyx_L14:;
+
+        /* "View.MemoryView":848
+ *                 if start < 0:
+ *                     start = 0
+ *             elif start >= shape:             # <<<<<<<<<<<<<<
+ *                 if negative_step:
+ *                     start = shape - 1
+ */
+      }
+      __pyx_L12:;
+
+      /* "View.MemoryView":843
+ * 
+ * 
+ *         if have_start:             # <<<<<<<<<<<<<<
+ *             if start < 0:
+ *                 start += shape
+ */
+      goto __pyx_L11;
+    }
+
+    /* "View.MemoryView":854
+ *                     start = shape
+ *         else:
+ *             if negative_step:             # <<<<<<<<<<<<<<
+ *                 start = shape - 1
+ *             else:
+ */
+    /*else*/ {
+      __pyx_t_2 = (__pyx_v_negative_step != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":855
+ *         else:
+ *             if negative_step:
+ *                 start = shape - 1             # <<<<<<<<<<<<<<
+ *             else:
+ *                 start = 0
+ */
+        __pyx_v_start = (__pyx_v_shape - 1);
+
+        /* "View.MemoryView":854
+ *                     start = shape
+ *         else:
+ *             if negative_step:             # <<<<<<<<<<<<<<
+ *                 start = shape - 1
+ *             else:
+ */
+        goto __pyx_L15;
+      }
+
+      /* "View.MemoryView":857
+ *                 start = shape - 1
+ *             else:
+ *                 start = 0             # <<<<<<<<<<<<<<
+ * 
+ *         if have_stop:
+ */
+      /*else*/ {
+        __pyx_v_start = 0;
+      }
+      __pyx_L15:;
+    }
+    __pyx_L11:;
+
+    /* "View.MemoryView":859
+ *                 start = 0
+ * 
+ *         if have_stop:             # <<<<<<<<<<<<<<
+ *             if stop < 0:
+ *                 stop += shape
+ */
+    __pyx_t_2 = (__pyx_v_have_stop != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":860
+ * 
+ *         if have_stop:
+ *             if stop < 0:             # <<<<<<<<<<<<<<
+ *                 stop += shape
+ *                 if stop < 0:
+ */
+      __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":861
+ *         if have_stop:
+ *             if stop < 0:
+ *                 stop += shape             # <<<<<<<<<<<<<<
+ *                 if stop < 0:
+ *                     stop = 0
+ */
+        __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape);
+
+        /* "View.MemoryView":862
+ *             if stop < 0:
+ *                 stop += shape
+ *                 if stop < 0:             # <<<<<<<<<<<<<<
+ *                     stop = 0
+ *             elif stop > shape:
+ */
+        __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
+        if (__pyx_t_2) {
+
+          /* "View.MemoryView":863
+ *                 stop += shape
+ *                 if stop < 0:
+ *                     stop = 0             # <<<<<<<<<<<<<<
+ *             elif stop > shape:
+ *                 stop = shape
+ */
+          __pyx_v_stop = 0;
+
+          /* "View.MemoryView":862
+ *             if stop < 0:
+ *                 stop += shape
+ *                 if stop < 0:             # <<<<<<<<<<<<<<
+ *                     stop = 0
+ *             elif stop > shape:
+ */
+        }
+
+        /* "View.MemoryView":860
+ * 
+ *         if have_stop:
+ *             if stop < 0:             # <<<<<<<<<<<<<<
+ *                 stop += shape
+ *                 if stop < 0:
+ */
+        goto __pyx_L17;
+      }
+
+      /* "View.MemoryView":864
+ *                 if stop < 0:
+ *                     stop = 0
+ *             elif stop > shape:             # <<<<<<<<<<<<<<
+ *                 stop = shape
+ *         else:
+ */
+      __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":865
+ *                     stop = 0
+ *             elif stop > shape:
+ *                 stop = shape             # <<<<<<<<<<<<<<
+ *         else:
+ *             if negative_step:
+ */
+        __pyx_v_stop = __pyx_v_shape;
+
+        /* "View.MemoryView":864
+ *                 if stop < 0:
+ *                     stop = 0
+ *             elif stop > shape:             # <<<<<<<<<<<<<<
+ *                 stop = shape
+ *         else:
+ */
+      }
+      __pyx_L17:;
+
+      /* "View.MemoryView":859
+ *                 start = 0
+ * 
+ *         if have_stop:             # <<<<<<<<<<<<<<
+ *             if stop < 0:
+ *                 stop += shape
+ */
+      goto __pyx_L16;
+    }
+
+    /* "View.MemoryView":867
+ *                 stop = shape
+ *         else:
+ *             if negative_step:             # <<<<<<<<<<<<<<
+ *                 stop = -1
+ *             else:
+ */
+    /*else*/ {
+      __pyx_t_2 = (__pyx_v_negative_step != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":868
+ *         else:
+ *             if negative_step:
+ *                 stop = -1             # <<<<<<<<<<<<<<
+ *             else:
+ *                 stop = shape
+ */
+        __pyx_v_stop = -1L;
+
+        /* "View.MemoryView":867
+ *                 stop = shape
+ *         else:
+ *             if negative_step:             # <<<<<<<<<<<<<<
+ *                 stop = -1
+ *             else:
+ */
+        goto __pyx_L19;
+      }
+
+      /* "View.MemoryView":870
+ *                 stop = -1
+ *             else:
+ *                 stop = shape             # <<<<<<<<<<<<<<
+ * 
+ *         if not have_step:
+ */
+      /*else*/ {
+        __pyx_v_stop = __pyx_v_shape;
+      }
+      __pyx_L19:;
+    }
+    __pyx_L16:;
+
+    /* "View.MemoryView":872
+ *                 stop = shape
+ * 
+ *         if not have_step:             # <<<<<<<<<<<<<<
+ *             step = 1
+ * 
+ */
+    __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":873
+ * 
+ *         if not have_step:
+ *             step = 1             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+      __pyx_v_step = 1;
+
+      /* "View.MemoryView":872
+ *                 stop = shape
+ * 
+ *         if not have_step:             # <<<<<<<<<<<<<<
+ *             step = 1
+ * 
+ */
+    }
+
+    /* "View.MemoryView":877
+ * 
+ *         with cython.cdivision(True):
+ *             new_shape = (stop - start) // step             # <<<<<<<<<<<<<<
+ * 
+ *             if (stop - start) - step * new_shape:
+ */
+    __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step);
+
+    /* "View.MemoryView":879
+ *             new_shape = (stop - start) // step
+ * 
+ *             if (stop - start) - step * new_shape:             # <<<<<<<<<<<<<<
+ *                 new_shape += 1
+ * 
+ */
+    __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":880
+ * 
+ *             if (stop - start) - step * new_shape:
+ *                 new_shape += 1             # <<<<<<<<<<<<<<
+ * 
+ *         if new_shape < 0:
+ */
+      __pyx_v_new_shape = (__pyx_v_new_shape + 1);
+
+      /* "View.MemoryView":879
+ *             new_shape = (stop - start) // step
+ * 
+ *             if (stop - start) - step * new_shape:             # <<<<<<<<<<<<<<
+ *                 new_shape += 1
+ * 
+ */
+    }
+
+    /* "View.MemoryView":882
+ *                 new_shape += 1
+ * 
+ *         if new_shape < 0:             # <<<<<<<<<<<<<<
+ *             new_shape = 0
+ * 
+ */
+    __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":883
+ * 
+ *         if new_shape < 0:
+ *             new_shape = 0             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+      __pyx_v_new_shape = 0;
+
+      /* "View.MemoryView":882
+ *                 new_shape += 1
+ * 
+ *         if new_shape < 0:             # <<<<<<<<<<<<<<
+ *             new_shape = 0
+ * 
+ */
+    }
+
+    /* "View.MemoryView":886
+ * 
+ * 
+ *         dst.strides[new_ndim] = stride * step             # <<<<<<<<<<<<<<
+ *         dst.shape[new_ndim] = new_shape
+ *         dst.suboffsets[new_ndim] = suboffset
+ */
+    (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step);
+
+    /* "View.MemoryView":887
+ * 
+ *         dst.strides[new_ndim] = stride * step
+ *         dst.shape[new_ndim] = new_shape             # <<<<<<<<<<<<<<
+ *         dst.suboffsets[new_ndim] = suboffset
+ * 
+ */
+    (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape;
+
+    /* "View.MemoryView":888
+ *         dst.strides[new_ndim] = stride * step
+ *         dst.shape[new_ndim] = new_shape
+ *         dst.suboffsets[new_ndim] = suboffset             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+    (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset;
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+  __pyx_L3:;
+
+  /* "View.MemoryView":891
+ * 
+ * 
+ *     if suboffset_dim[0] < 0:             # <<<<<<<<<<<<<<
+ *         dst.data += start * stride
+ *     else:
+ */
+  __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":892
+ * 
+ *     if suboffset_dim[0] < 0:
+ *         dst.data += start * stride             # <<<<<<<<<<<<<<
+ *     else:
+ *         dst.suboffsets[suboffset_dim[0]] += start * stride
+ */
+    __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride));
+
+    /* "View.MemoryView":891
+ * 
+ * 
+ *     if suboffset_dim[0] < 0:             # <<<<<<<<<<<<<<
+ *         dst.data += start * stride
+ *     else:
+ */
+    goto __pyx_L23;
+  }
+
+  /* "View.MemoryView":894
+ *         dst.data += start * stride
+ *     else:
+ *         dst.suboffsets[suboffset_dim[0]] += start * stride             # <<<<<<<<<<<<<<
+ * 
+ *     if suboffset >= 0:
+ */
+  /*else*/ {
+    __pyx_t_3 = (__pyx_v_suboffset_dim[0]);
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+ * 
+ *     if suboffset >= 0:             # <<<<<<<<<<<<<<
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+ */
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+  if (__pyx_t_2) {
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+    /* "View.MemoryView":897
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+ *     if suboffset >= 0:
+ *         if not is_slice:             # <<<<<<<<<<<<<<
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+ *                 dst.data = (<char **> dst.data)[0] + suboffset
+ */
+    __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0);
+    if (__pyx_t_2) {
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+      /* "View.MemoryView":898
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+ *         if not is_slice:
+ *             if new_ndim == 0:             # <<<<<<<<<<<<<<
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+ */
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+
+        /* "View.MemoryView":899
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+        /* "View.MemoryView":898
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+ *             else:
+ */
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+      }
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+        /* "View.MemoryView":902
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+        __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 901, __pyx_L1_error)
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+ */
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+ * @cname('__pyx_memoryview_slice_memviewslice')
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+ */
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+static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, Py_ssize_t __pyx_v_index, Py_ssize_t __pyx_v_dim) {
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+ */
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+ */
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+ */
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+ */
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+  /* "View.MemoryView":1118
+ * 
+ * @cname('__pyx_get_best_slice_order')
+ * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil:             # <<<<<<<<<<<<<<
+ *     """
+ *     Figure out the best memory access order for a given slice.
+ */
+
+  /* function exit code */
+  __pyx_L0:;
+  return __pyx_r;
+}
+
+/* "View.MemoryView":1142
+ * 
+ * @cython.cdivision(True)
+ * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
+ *                                    char *dst_data, Py_ssize_t *dst_strides,
+ *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
+  CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+  CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
+  Py_ssize_t __pyx_v_dst_extent;
+  Py_ssize_t __pyx_v_src_stride;
+  Py_ssize_t __pyx_v_dst_stride;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  Py_ssize_t __pyx_t_4;
+  Py_ssize_t __pyx_t_5;
+  Py_ssize_t __pyx_t_6;
+
+  /* "View.MemoryView":1149
+ * 
+ *     cdef Py_ssize_t i
+ *     cdef Py_ssize_t src_extent = src_shape[0]             # <<<<<<<<<<<<<<
+ *     cdef Py_ssize_t dst_extent = dst_shape[0]
+ *     cdef Py_ssize_t src_stride = src_strides[0]
+ */
+  __pyx_v_src_extent = (__pyx_v_src_shape[0]);
+
+  /* "View.MemoryView":1150
+ *     cdef Py_ssize_t i
+ *     cdef Py_ssize_t src_extent = src_shape[0]
+ *     cdef Py_ssize_t dst_extent = dst_shape[0]             # <<<<<<<<<<<<<<
+ *     cdef Py_ssize_t src_stride = src_strides[0]
+ *     cdef Py_ssize_t dst_stride = dst_strides[0]
+ */
+  __pyx_v_dst_extent = (__pyx_v_dst_shape[0]);
+
+  /* "View.MemoryView":1151
+ *     cdef Py_ssize_t src_extent = src_shape[0]
+ *     cdef Py_ssize_t dst_extent = dst_shape[0]
+ *     cdef Py_ssize_t src_stride = src_strides[0]             # <<<<<<<<<<<<<<
+ *     cdef Py_ssize_t dst_stride = dst_strides[0]
+ * 
+ */
+  __pyx_v_src_stride = (__pyx_v_src_strides[0]);
+
+  /* "View.MemoryView":1152
+ *     cdef Py_ssize_t dst_extent = dst_shape[0]
+ *     cdef Py_ssize_t src_stride = src_strides[0]
+ *     cdef Py_ssize_t dst_stride = dst_strides[0]             # <<<<<<<<<<<<<<
+ * 
+ *     if ndim == 1:
+ */
+  __pyx_v_dst_stride = (__pyx_v_dst_strides[0]);
+
+  /* "View.MemoryView":1154
+ *     cdef Py_ssize_t dst_stride = dst_strides[0]
+ * 
+ *     if ndim == 1:             # <<<<<<<<<<<<<<
+ *        if (src_stride > 0 and dst_stride > 0 and
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ */
+  __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
+  if (__pyx_t_1) {
+
+    /* "View.MemoryView":1155
+ * 
+ *     if ndim == 1:
+ *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)
+ */
+    __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
+    if (__pyx_t_2) {
+    } else {
+      __pyx_t_1 = __pyx_t_2;
+      goto __pyx_L5_bool_binop_done;
+    }
+    __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
+    if (__pyx_t_2) {
+    } else {
+      __pyx_t_1 = __pyx_t_2;
+      goto __pyx_L5_bool_binop_done;
+    }
+
+    /* "View.MemoryView":1156
+ *     if ndim == 1:
+ *        if (src_stride > 0 and dst_stride > 0 and
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):             # <<<<<<<<<<<<<<
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)
+ *        else:
+ */
+    __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize);
+    if (__pyx_t_2) {
+      __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride));
+    }
+    __pyx_t_3 = (__pyx_t_2 != 0);
+    __pyx_t_1 = __pyx_t_3;
+    __pyx_L5_bool_binop_done:;
+
+    /* "View.MemoryView":1155
+ * 
+ *     if ndim == 1:
+ *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)
+ */
+    if (__pyx_t_1) {
+
+      /* "View.MemoryView":1157
+ *        if (src_stride > 0 and dst_stride > 0 and
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)             # <<<<<<<<<<<<<<
+ *        else:
+ *            for i in range(dst_extent):
+ */
+      (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)));
+
+      /* "View.MemoryView":1155
+ * 
+ *     if ndim == 1:
+ *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)
+ */
+      goto __pyx_L4;
+    }
+
+    /* "View.MemoryView":1159
+ *            memcpy(dst_data, src_data, itemsize * dst_extent)
+ *        else:
+ *            for i in range(dst_extent):             # <<<<<<<<<<<<<<
+ *                memcpy(dst_data, src_data, itemsize)
+ *                src_data += src_stride
+ */
+    /*else*/ {
+      __pyx_t_4 = __pyx_v_dst_extent;
+      __pyx_t_5 = __pyx_t_4;
+      for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
+        __pyx_v_i = __pyx_t_6;
+
+        /* "View.MemoryView":1160
+ *        else:
+ *            for i in range(dst_extent):
+ *                memcpy(dst_data, src_data, itemsize)             # <<<<<<<<<<<<<<
+ *                src_data += src_stride
+ *                dst_data += dst_stride
+ */
+        (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize));
+
+        /* "View.MemoryView":1161
+ *            for i in range(dst_extent):
+ *                memcpy(dst_data, src_data, itemsize)
+ *                src_data += src_stride             # <<<<<<<<<<<<<<
+ *                dst_data += dst_stride
+ *     else:
+ */
+        __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+        /* "View.MemoryView":1162
+ *                memcpy(dst_data, src_data, itemsize)
+ *                src_data += src_stride
+ *                dst_data += dst_stride             # <<<<<<<<<<<<<<
+ *     else:
+ *         for i in range(dst_extent):
+ */
+        __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+      }
+    }
+    __pyx_L4:;
+
+    /* "View.MemoryView":1154
+ *     cdef Py_ssize_t dst_stride = dst_strides[0]
+ * 
+ *     if ndim == 1:             # <<<<<<<<<<<<<<
+ *        if (src_stride > 0 and dst_stride > 0 and
+ *            <size_t> src_stride == itemsize == <size_t> dst_stride):
+ */
+    goto __pyx_L3;
+  }
+
+  /* "View.MemoryView":1164
+ *                dst_data += dst_stride
+ *     else:
+ *         for i in range(dst_extent):             # <<<<<<<<<<<<<<
+ *             _copy_strided_to_strided(src_data, src_strides + 1,
+ *                                      dst_data, dst_strides + 1,
+ */
+  /*else*/ {
+    __pyx_t_4 = __pyx_v_dst_extent;
+    __pyx_t_5 = __pyx_t_4;
+    for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
+      __pyx_v_i = __pyx_t_6;
+
+      /* "View.MemoryView":1165
+ *     else:
+ *         for i in range(dst_extent):
+ *             _copy_strided_to_strided(src_data, src_strides + 1,             # <<<<<<<<<<<<<<
+ *                                      dst_data, dst_strides + 1,
+ *                                      src_shape + 1, dst_shape + 1,
+ */
+      _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);
+
+      /* "View.MemoryView":1169
+ *                                      src_shape + 1, dst_shape + 1,
+ *                                      ndim - 1, itemsize)
+ *             src_data += src_stride             # <<<<<<<<<<<<<<
+ *             dst_data += dst_stride
+ * 
+ */
+      __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
+
+      /* "View.MemoryView":1170
+ *                                      ndim - 1, itemsize)
+ *             src_data += src_stride
+ *             dst_data += dst_stride             # <<<<<<<<<<<<<<
+ * 
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
+ */
+      __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
+    }
+  }
+  __pyx_L3:;
+
+  /* "View.MemoryView":1142
+ * 
+ * @cython.cdivision(True)
+ * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
+ *                                    char *dst_data, Py_ssize_t *dst_strides,
+ *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
+ */
+
+  /* function exit code */
+}
+
+/* "View.MemoryView":1172
+ *             dst_data += dst_stride
+ * 
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
+ *                                   __Pyx_memviewslice *dst,
+ *                                   int ndim, size_t itemsize) nogil:
+ */
+
+static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
+
+  /* "View.MemoryView":1175
+ *                                   __Pyx_memviewslice *dst,
+ *                                   int ndim, size_t itemsize) nogil:
+ *     _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides,             # <<<<<<<<<<<<<<
+ *                              src.shape, dst.shape, ndim, itemsize)
+ * 
+ */
+  _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);
+
+  /* "View.MemoryView":1172
+ *             dst_data += dst_stride
+ * 
+ * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
+ *                                   __Pyx_memviewslice *dst,
+ *                                   int ndim, size_t itemsize) nogil:
+ */
+
+  /* function exit code */
+}
+
+/* "View.MemoryView":1179
+ * 
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
+ *     "Return the size of the memory occupied by the slice in number of bytes"
+ *     cdef Py_ssize_t shape, size = src.memview.view.itemsize
+ */
+
+static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
+  Py_ssize_t __pyx_v_shape;
+  Py_ssize_t __pyx_v_size;
+  Py_ssize_t __pyx_r;
+  Py_ssize_t __pyx_t_1;
+  Py_ssize_t *__pyx_t_2;
+  Py_ssize_t *__pyx_t_3;
+  Py_ssize_t *__pyx_t_4;
+
+  /* "View.MemoryView":1181
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:
+ *     "Return the size of the memory occupied by the slice in number of bytes"
+ *     cdef Py_ssize_t shape, size = src.memview.view.itemsize             # <<<<<<<<<<<<<<
+ * 
+ *     for shape in src.shape[:ndim]:
+ */
+  __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
+  __pyx_v_size = __pyx_t_1;
+
+  /* "View.MemoryView":1183
+ *     cdef Py_ssize_t shape, size = src.memview.view.itemsize
+ * 
+ *     for shape in src.shape[:ndim]:             # <<<<<<<<<<<<<<
+ *         size *= shape
+ * 
+ */
+  __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim);
+  for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) {
+    __pyx_t_2 = __pyx_t_4;
+    __pyx_v_shape = (__pyx_t_2[0]);
+
+    /* "View.MemoryView":1184
+ * 
+ *     for shape in src.shape[:ndim]:
+ *         size *= shape             # <<<<<<<<<<<<<<
+ * 
+ *     return size
+ */
+    __pyx_v_size = (__pyx_v_size * __pyx_v_shape);
+  }
+
+  /* "View.MemoryView":1186
+ *         size *= shape
+ * 
+ *     return size             # <<<<<<<<<<<<<<
+ * 
+ * @cname('__pyx_fill_contig_strides_array')
+ */
+  __pyx_r = __pyx_v_size;
+  goto __pyx_L0;
+
+  /* "View.MemoryView":1179
+ * 
+ * @cname('__pyx_memoryview_slice_get_size')
+ * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
+ *     "Return the size of the memory occupied by the slice in number of bytes"
+ *     cdef Py_ssize_t shape, size = src.memview.view.itemsize
+ */
+
+  /* function exit code */
+  __pyx_L0:;
+  return __pyx_r;
+}
+
+/* "View.MemoryView":1189
+ * 
+ * @cname('__pyx_fill_contig_strides_array')
+ * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
+ *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
+ *                 int ndim, char order) nogil:
+ */
+
+static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
+  int __pyx_v_idx;
+  Py_ssize_t __pyx_r;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  int __pyx_t_4;
+
+  /* "View.MemoryView":1198
+ *     cdef int idx
+ * 
+ *     if order == 'F':             # <<<<<<<<<<<<<<
+ *         for idx in range(ndim):
+ *             strides[idx] = stride
+ */
+  __pyx_t_1 = ((__pyx_v_order == 'F') != 0);
+  if (__pyx_t_1) {
+
+    /* "View.MemoryView":1199
+ * 
+ *     if order == 'F':
+ *         for idx in range(ndim):             # <<<<<<<<<<<<<<
+ *             strides[idx] = stride
+ *             stride *= shape[idx]
+ */
+    __pyx_t_2 = __pyx_v_ndim;
+    __pyx_t_3 = __pyx_t_2;
+    for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
+      __pyx_v_idx = __pyx_t_4;
+
+      /* "View.MemoryView":1200
+ *     if order == 'F':
+ *         for idx in range(ndim):
+ *             strides[idx] = stride             # <<<<<<<<<<<<<<
+ *             stride *= shape[idx]
+ *     else:
+ */
+      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
+
+      /* "View.MemoryView":1201
+ *         for idx in range(ndim):
+ *             strides[idx] = stride
+ *             stride *= shape[idx]             # <<<<<<<<<<<<<<
+ *     else:
+ *         for idx in range(ndim - 1, -1, -1):
+ */
+      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
+    }
+
+    /* "View.MemoryView":1198
+ *     cdef int idx
+ * 
+ *     if order == 'F':             # <<<<<<<<<<<<<<
+ *         for idx in range(ndim):
+ *             strides[idx] = stride
+ */
+    goto __pyx_L3;
+  }
+
+  /* "View.MemoryView":1203
+ *             stride *= shape[idx]
+ *     else:
+ *         for idx in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
+ *             strides[idx] = stride
+ *             stride *= shape[idx]
+ */
+  /*else*/ {
+    for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) {
+      __pyx_v_idx = __pyx_t_2;
+
+      /* "View.MemoryView":1204
+ *     else:
+ *         for idx in range(ndim - 1, -1, -1):
+ *             strides[idx] = stride             # <<<<<<<<<<<<<<
+ *             stride *= shape[idx]
+ * 
+ */
+      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
+
+      /* "View.MemoryView":1205
+ *         for idx in range(ndim - 1, -1, -1):
+ *             strides[idx] = stride
+ *             stride *= shape[idx]             # <<<<<<<<<<<<<<
+ * 
+ *     return stride
+ */
+      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
+    }
+  }
+  __pyx_L3:;
+
+  /* "View.MemoryView":1207
+ *             stride *= shape[idx]
+ * 
+ *     return stride             # <<<<<<<<<<<<<<
+ * 
+ * @cname('__pyx_memoryview_copy_data_to_temp')
+ */
+  __pyx_r = __pyx_v_stride;
+  goto __pyx_L0;
+
+  /* "View.MemoryView":1189
+ * 
+ * @cname('__pyx_fill_contig_strides_array')
+ * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
+ *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
+ *                 int ndim, char order) nogil:
+ */
+
+  /* function exit code */
+  __pyx_L0:;
+  return __pyx_r;
+}
+
+/* "View.MemoryView":1210
+ * 
+ * @cname('__pyx_memoryview_copy_data_to_temp')
+ * cdef void *copy_data_to_temp(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
+ *                              __Pyx_memviewslice *tmpslice,
+ *                              char order,
+ */
+
+static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) {
+  int __pyx_v_i;
+  void *__pyx_v_result;
+  size_t __pyx_v_itemsize;
+  size_t __pyx_v_size;
+  void *__pyx_r;
+  Py_ssize_t __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  struct __pyx_memoryview_obj *__pyx_t_4;
+  int __pyx_t_5;
+  int __pyx_t_6;
+  int __pyx_lineno = 0;
+  const char *__pyx_filename = NULL;
+  int __pyx_clineno = 0;
+
+  /* "View.MemoryView":1221
+ *     cdef void *result
+ * 
+ *     cdef size_t itemsize = src.memview.view.itemsize             # <<<<<<<<<<<<<<
+ *     cdef size_t size = slice_get_size(src, ndim)
+ * 
+ */
+  __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
+  __pyx_v_itemsize = __pyx_t_1;
+
+  /* "View.MemoryView":1222
+ * 
+ *     cdef size_t itemsize = src.memview.view.itemsize
+ *     cdef size_t size = slice_get_size(src, ndim)             # <<<<<<<<<<<<<<
+ * 
+ *     result = malloc(size)
+ */
+  __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim);
+
+  /* "View.MemoryView":1224
+ *     cdef size_t size = slice_get_size(src, ndim)
+ * 
+ *     result = malloc(size)             # <<<<<<<<<<<<<<
+ *     if not result:
+ *         _err(MemoryError, NULL)
+ */
+  __pyx_v_result = malloc(__pyx_v_size);
+
+  /* "View.MemoryView":1225
+ * 
+ *     result = malloc(size)
+ *     if not result:             # <<<<<<<<<<<<<<
+ *         _err(MemoryError, NULL)
+ * 
+ */
+  __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":1226
+ *     result = malloc(size)
+ *     if not result:
+ *         _err(MemoryError, NULL)             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
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+ */
+
+static int __pyx_memoryview_copy_contents(__Pyx_memviewslice __pyx_v_src, __Pyx_memviewslice __pyx_v_dst, int __pyx_v_src_ndim, int __pyx_v_dst_ndim, int __pyx_v_dtype_is_object) {
+  void *__pyx_v_tmpdata;
+  size_t __pyx_v_itemsize;
+  int __pyx_v_i;
+  char __pyx_v_order;
+  int __pyx_v_broadcasting;
+  int __pyx_v_direct_copy;
+  __Pyx_memviewslice __pyx_v_tmp;
+  int __pyx_v_ndim;
+  int __pyx_r;
+  Py_ssize_t __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+  int __pyx_t_4;
+  int __pyx_t_5;
+  int __pyx_t_6;
+  void *__pyx_t_7;
+  int __pyx_t_8;
+  int __pyx_lineno = 0;
+  const char *__pyx_filename = NULL;
+  int __pyx_clineno = 0;
+
+  /* "View.MemoryView":1278
+ *     Check for overlapping memory and verify the shapes.
+ *     """
+ *     cdef void *tmpdata = NULL             # <<<<<<<<<<<<<<
+ *     cdef size_t itemsize = src.memview.view.itemsize
+ *     cdef int i
+ */
+  __pyx_v_tmpdata = NULL;
+
+  /* "View.MemoryView":1279
+ *     """
+ *     cdef void *tmpdata = NULL
+ *     cdef size_t itemsize = src.memview.view.itemsize             # <<<<<<<<<<<<<<
+ *     cdef int i
+ *     cdef char order = get_best_order(&src, src_ndim)
+ */
+  __pyx_t_1 = __pyx_v_src.memview->view.itemsize;
+  __pyx_v_itemsize = __pyx_t_1;
+
+  /* "View.MemoryView":1281
+ *     cdef size_t itemsize = src.memview.view.itemsize
+ *     cdef int i
+ *     cdef char order = get_best_order(&src, src_ndim)             # <<<<<<<<<<<<<<
+ *     cdef bint broadcasting = False
+ *     cdef bint direct_copy = False
+ */
+  __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_src), __pyx_v_src_ndim);
+
+  /* "View.MemoryView":1282
+ *     cdef int i
+ *     cdef char order = get_best_order(&src, src_ndim)
+ *     cdef bint broadcasting = False             # <<<<<<<<<<<<<<
+ *     cdef bint direct_copy = False
+ *     cdef __Pyx_memviewslice tmp
+ */
+  __pyx_v_broadcasting = 0;
+
+  /* "View.MemoryView":1283
+ *     cdef char order = get_best_order(&src, src_ndim)
+ *     cdef bint broadcasting = False
+ *     cdef bint direct_copy = False             # <<<<<<<<<<<<<<
+ *     cdef __Pyx_memviewslice tmp
+ * 
+ */
+  __pyx_v_direct_copy = 0;
+
+  /* "View.MemoryView":1286
+ *     cdef __Pyx_memviewslice tmp
+ * 
+ *     if src_ndim < dst_ndim:             # <<<<<<<<<<<<<<
+ *         broadcast_leading(&src, src_ndim, dst_ndim)
+ *     elif dst_ndim < src_ndim:
+ */
+  __pyx_t_2 = ((__pyx_v_src_ndim < __pyx_v_dst_ndim) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":1287
+ * 
+ *     if src_ndim < dst_ndim:
+ *         broadcast_leading(&src, src_ndim, dst_ndim)             # <<<<<<<<<<<<<<
+ *     elif dst_ndim < src_ndim:
+ *         broadcast_leading(&dst, dst_ndim, src_ndim)
+ */
+    __pyx_memoryview_broadcast_leading((&__pyx_v_src), __pyx_v_src_ndim, __pyx_v_dst_ndim);
+
+    /* "View.MemoryView":1286
+ *     cdef __Pyx_memviewslice tmp
+ * 
+ *     if src_ndim < dst_ndim:             # <<<<<<<<<<<<<<
+ *         broadcast_leading(&src, src_ndim, dst_ndim)
+ *     elif dst_ndim < src_ndim:
+ */
+    goto __pyx_L3;
+  }
+
+  /* "View.MemoryView":1288
+ *     if src_ndim < dst_ndim:
+ *         broadcast_leading(&src, src_ndim, dst_ndim)
+ *     elif dst_ndim < src_ndim:             # <<<<<<<<<<<<<<
+ *         broadcast_leading(&dst, dst_ndim, src_ndim)
+ * 
+ */
+  __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":1289
+ *         broadcast_leading(&src, src_ndim, dst_ndim)
+ *     elif dst_ndim < src_ndim:
+ *         broadcast_leading(&dst, dst_ndim, src_ndim)             # <<<<<<<<<<<<<<
+ * 
+ *     cdef int ndim = max(src_ndim, dst_ndim)
+ */
+    __pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim);
+
+    /* "View.MemoryView":1288
+ *     if src_ndim < dst_ndim:
+ *         broadcast_leading(&src, src_ndim, dst_ndim)
+ *     elif dst_ndim < src_ndim:             # <<<<<<<<<<<<<<
+ *         broadcast_leading(&dst, dst_ndim, src_ndim)
+ * 
+ */
+  }
+  __pyx_L3:;
+
+  /* "View.MemoryView":1291
+ *         broadcast_leading(&dst, dst_ndim, src_ndim)
+ * 
+ *     cdef int ndim = max(src_ndim, dst_ndim)             # <<<<<<<<<<<<<<
+ * 
+ *     for i in range(ndim):
+ */
+  __pyx_t_3 = __pyx_v_dst_ndim;
+  __pyx_t_4 = __pyx_v_src_ndim;
+  if (((__pyx_t_3 > __pyx_t_4) != 0)) {
+    __pyx_t_5 = __pyx_t_3;
+  } else {
+    __pyx_t_5 = __pyx_t_4;
+  }
+  __pyx_v_ndim = __pyx_t_5;
+
+  /* "View.MemoryView":1293
+ *     cdef int ndim = max(src_ndim, dst_ndim)
+ * 
+ *     for i in range(ndim):             # <<<<<<<<<<<<<<
+ *         if src.shape[i] != dst.shape[i]:
+ *             if src.shape[i] == 1:
+ */
+  __pyx_t_5 = __pyx_v_ndim;
+  __pyx_t_3 = __pyx_t_5;
+  for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
+    __pyx_v_i = __pyx_t_4;
+
+    /* "View.MemoryView":1294
+ * 
+ *     for i in range(ndim):
+ *         if src.shape[i] != dst.shape[i]:             # <<<<<<<<<<<<<<
+ *             if src.shape[i] == 1:
+ *                 broadcasting = True
+ */
+    __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1295
+ *     for i in range(ndim):
+ *         if src.shape[i] != dst.shape[i]:
+ *             if src.shape[i] == 1:             # <<<<<<<<<<<<<<
+ *                 broadcasting = True
+ *                 src.strides[i] = 0
+ */
+      __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0);
+      if (__pyx_t_2) {
+
+        /* "View.MemoryView":1296
+ *         if src.shape[i] != dst.shape[i]:
+ *             if src.shape[i] == 1:
+ *                 broadcasting = True             # <<<<<<<<<<<<<<
+ *                 src.strides[i] = 0
+ *             else:
+ */
+        __pyx_v_broadcasting = 1;
+
+        /* "View.MemoryView":1297
+ *             if src.shape[i] == 1:
+ *                 broadcasting = True
+ *                 src.strides[i] = 0             # <<<<<<<<<<<<<<
+ *             else:
+ *                 _err_extents(i, dst.shape[i], src.shape[i])
+ */
+        (__pyx_v_src.strides[__pyx_v_i]) = 0;
+
+        /* "View.MemoryView":1295
+ *     for i in range(ndim):
+ *         if src.shape[i] != dst.shape[i]:
+ *             if src.shape[i] == 1:             # <<<<<<<<<<<<<<
+ *                 broadcasting = True
+ *                 src.strides[i] = 0
+ */
+        goto __pyx_L7;
+      }
+
+      /* "View.MemoryView":1299
+ *                 src.strides[i] = 0
+ *             else:
+ *                 _err_extents(i, dst.shape[i], src.shape[i])             # <<<<<<<<<<<<<<
+ * 
+ *         if src.suboffsets[i] >= 0:
+ */
+      /*else*/ {
+        __pyx_t_6 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(1, 1299, __pyx_L1_error)
+      }
+      __pyx_L7:;
+
+      /* "View.MemoryView":1294
+ * 
+ *     for i in range(ndim):
+ *         if src.shape[i] != dst.shape[i]:             # <<<<<<<<<<<<<<
+ *             if src.shape[i] == 1:
+ *                 broadcasting = True
+ */
+    }
+
+    /* "View.MemoryView":1301
+ *                 _err_extents(i, dst.shape[i], src.shape[i])
+ * 
+ *         if src.suboffsets[i] >= 0:             # <<<<<<<<<<<<<<
+ *             _err_dim(ValueError, "Dimension %d is not direct", i)
+ * 
+ */
+    __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1302
+ * 
+ *         if src.suboffsets[i] >= 0:
+ *             _err_dim(ValueError, "Dimension %d is not direct", i)             # <<<<<<<<<<<<<<
+ * 
+ *     if slices_overlap(&src, &dst, ndim, itemsize):
+ */
+      __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(1, 1302, __pyx_L1_error)
+
+      /* "View.MemoryView":1301
+ *                 _err_extents(i, dst.shape[i], src.shape[i])
+ * 
+ *         if src.suboffsets[i] >= 0:             # <<<<<<<<<<<<<<
+ *             _err_dim(ValueError, "Dimension %d is not direct", i)
+ * 
+ */
+    }
+  }
+
+  /* "View.MemoryView":1304
+ *             _err_dim(ValueError, "Dimension %d is not direct", i)
+ * 
+ *     if slices_overlap(&src, &dst, ndim, itemsize):             # <<<<<<<<<<<<<<
+ * 
+ *         if not slice_is_contig(src, order, ndim):
+ */
+  __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":1306
+ *     if slices_overlap(&src, &dst, ndim, itemsize):
+ * 
+ *         if not slice_is_contig(src, order, ndim):             # <<<<<<<<<<<<<<
+ *             order = get_best_order(&dst, ndim)
+ * 
+ */
+    __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1307
+ * 
+ *         if not slice_is_contig(src, order, ndim):
+ *             order = get_best_order(&dst, ndim)             # <<<<<<<<<<<<<<
+ * 
+ *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ */
+      __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim);
+
+      /* "View.MemoryView":1306
+ *     if slices_overlap(&src, &dst, ndim, itemsize):
+ * 
+ *         if not slice_is_contig(src, order, ndim):             # <<<<<<<<<<<<<<
+ *             order = get_best_order(&dst, ndim)
+ * 
+ */
+    }
+
+    /* "View.MemoryView":1309
+ *             order = get_best_order(&dst, ndim)
+ * 
+ *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)             # <<<<<<<<<<<<<<
+ *         src = tmp
+ * 
+ */
+    __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(1, 1309, __pyx_L1_error)
+    __pyx_v_tmpdata = __pyx_t_7;
+
+    /* "View.MemoryView":1310
+ * 
+ *         tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
+ *         src = tmp             # <<<<<<<<<<<<<<
+ * 
+ *     if not broadcasting:
+ */
+    __pyx_v_src = __pyx_v_tmp;
+
+    /* "View.MemoryView":1304
+ *             _err_dim(ValueError, "Dimension %d is not direct", i)
+ * 
+ *     if slices_overlap(&src, &dst, ndim, itemsize):             # <<<<<<<<<<<<<<
+ * 
+ *         if not slice_is_contig(src, order, ndim):
+ */
+  }
+
+  /* "View.MemoryView":1312
+ *         src = tmp
+ * 
+ *     if not broadcasting:             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0);
+  if (__pyx_t_2) {
+
+    /* "View.MemoryView":1315
+ * 
+ * 
+ *         if slice_is_contig(src, 'C', ndim):             # <<<<<<<<<<<<<<
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)
+ *         elif slice_is_contig(src, 'F', ndim):
+ */
+    __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1316
+ * 
+ *         if slice_is_contig(src, 'C', ndim):
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)             # <<<<<<<<<<<<<<
+ *         elif slice_is_contig(src, 'F', ndim):
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)
+ */
+      __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim);
+
+      /* "View.MemoryView":1315
+ * 
+ * 
+ *         if slice_is_contig(src, 'C', ndim):             # <<<<<<<<<<<<<<
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)
+ *         elif slice_is_contig(src, 'F', ndim):
+ */
+      goto __pyx_L12;
+    }
+
+    /* "View.MemoryView":1317
+ *         if slice_is_contig(src, 'C', ndim):
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)
+ *         elif slice_is_contig(src, 'F', ndim):             # <<<<<<<<<<<<<<
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)
+ * 
+ */
+    __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1318
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)
+ *         elif slice_is_contig(src, 'F', ndim):
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)             # <<<<<<<<<<<<<<
+ * 
+ *         if direct_copy:
+ */
+      __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim);
+
+      /* "View.MemoryView":1317
+ *         if slice_is_contig(src, 'C', ndim):
+ *             direct_copy = slice_is_contig(dst, 'C', ndim)
+ *         elif slice_is_contig(src, 'F', ndim):             # <<<<<<<<<<<<<<
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)
+ * 
+ */
+    }
+    __pyx_L12:;
+
+    /* "View.MemoryView":1320
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)
+ * 
+ *         if direct_copy:             # <<<<<<<<<<<<<<
+ * 
+ *             refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+    __pyx_t_2 = (__pyx_v_direct_copy != 0);
+    if (__pyx_t_2) {
+
+      /* "View.MemoryView":1322
+ *         if direct_copy:
+ * 
+ *             refcount_copying(&dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
+ *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ *             refcount_copying(&dst, dtype_is_object, ndim, True)
+ */
+      __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+      /* "View.MemoryView":1323
+ * 
+ *             refcount_copying(&dst, dtype_is_object, ndim, False)
+ *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))             # <<<<<<<<<<<<<<
+ *             refcount_copying(&dst, dtype_is_object, ndim, True)
+ *             free(tmpdata)
+ */
+      (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)));
+
+      /* "View.MemoryView":1324
+ *             refcount_copying(&dst, dtype_is_object, ndim, False)
+ *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ *             refcount_copying(&dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
+ *             free(tmpdata)
+ *             return 0
+ */
+      __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+      /* "View.MemoryView":1325
+ *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
+ *             refcount_copying(&dst, dtype_is_object, ndim, True)
+ *             free(tmpdata)             # <<<<<<<<<<<<<<
+ *             return 0
+ * 
+ */
+      free(__pyx_v_tmpdata);
+
+      /* "View.MemoryView":1326
+ *             refcount_copying(&dst, dtype_is_object, ndim, True)
+ *             free(tmpdata)
+ *             return 0             # <<<<<<<<<<<<<<
+ * 
+ *     if order == 'F' == get_best_order(&dst, ndim):
+ */
+      __pyx_r = 0;
+      goto __pyx_L0;
+
+      /* "View.MemoryView":1320
+ *             direct_copy = slice_is_contig(dst, 'F', ndim)
+ * 
+ *         if direct_copy:             # <<<<<<<<<<<<<<
+ * 
+ *             refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+    }
+
+    /* "View.MemoryView":1312
+ *         src = tmp
+ * 
+ *     if not broadcasting:             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  }
+
+  /* "View.MemoryView":1328
+ *             return 0
+ * 
+ *     if order == 'F' == get_best_order(&dst, ndim):             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  __pyx_t_2 = (__pyx_v_order == 'F');
+  if (__pyx_t_2) {
+    __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim));
+  }
+  __pyx_t_8 = (__pyx_t_2 != 0);
+  if (__pyx_t_8) {
+
+    /* "View.MemoryView":1331
+ * 
+ * 
+ *         transpose_memslice(&src)             # <<<<<<<<<<<<<<
+ *         transpose_memslice(&dst)
+ * 
+ */
+    __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(1, 1331, __pyx_L1_error)
+
+    /* "View.MemoryView":1332
+ * 
+ *         transpose_memslice(&src)
+ *         transpose_memslice(&dst)             # <<<<<<<<<<<<<<
+ * 
+ *     refcount_copying(&dst, dtype_is_object, ndim, False)
+ */
+    __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(1, 1332, __pyx_L1_error)
+
+    /* "View.MemoryView":1328
+ *             return 0
+ * 
+ *     if order == 'F' == get_best_order(&dst, ndim):             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  }
+
+  /* "View.MemoryView":1334
+ *         transpose_memslice(&dst)
+ * 
+ *     refcount_copying(&dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
+ *     copy_strided_to_strided(&src, &dst, ndim, itemsize)
+ *     refcount_copying(&dst, dtype_is_object, ndim, True)
+ */
+  __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+  /* "View.MemoryView":1335
+ * 
+ *     refcount_copying(&dst, dtype_is_object, ndim, False)
+ *     copy_strided_to_strided(&src, &dst, ndim, itemsize)             # <<<<<<<<<<<<<<
+ *     refcount_copying(&dst, dtype_is_object, ndim, True)
+ * 
+ */
+  copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize);
+
+  /* "View.MemoryView":1336
+ *     refcount_copying(&dst, dtype_is_object, ndim, False)
+ *     copy_strided_to_strided(&src, &dst, ndim, itemsize)
+ *     refcount_copying(&dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
+ * 
+ *     free(tmpdata)
+ */
+  __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+  /* "View.MemoryView":1338
+ *     refcount_copying(&dst, dtype_is_object, ndim, True)
+ * 
+ *     free(tmpdata)             # <<<<<<<<<<<<<<
+ *     return 0
+ * 
+ */
+  free(__pyx_v_tmpdata);
+
+  /* "View.MemoryView":1339
+ * 
+ *     free(tmpdata)
+ *     return 0             # <<<<<<<<<<<<<<
+ * 
+ * @cname('__pyx_memoryview_broadcast_leading')
+ */
+  __pyx_r = 0;
+  goto __pyx_L0;
+
+  /* "View.MemoryView":1270
+ * 
+ * @cname('__pyx_memoryview_copy_contents')
+ * cdef int memoryview_copy_contents(__Pyx_memviewslice src,             # <<<<<<<<<<<<<<
+ *                                   __Pyx_memviewslice dst,
+ *                                   int src_ndim, int dst_ndim,
+ */
+
+  /* function exit code */
+  __pyx_L1_error:;
+  {
+    #ifdef WITH_THREAD
+    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
+    #endif
+    __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename);
+    #ifdef WITH_THREAD
+    __Pyx_PyGILState_Release(__pyx_gilstate_save);
+    #endif
+  }
+  __pyx_r = -1;
+  __pyx_L0:;
+  return __pyx_r;
+}
+
+/* "View.MemoryView":1342
+ * 
+ * @cname('__pyx_memoryview_broadcast_leading')
+ * cdef void broadcast_leading(__Pyx_memviewslice *mslice,             # <<<<<<<<<<<<<<
+ *                             int ndim,
+ *                             int ndim_other) nogil:
+ */
+
+static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) {
+  int __pyx_v_i;
+  int __pyx_v_offset;
+  int __pyx_t_1;
+  int __pyx_t_2;
+  int __pyx_t_3;
+
+  /* "View.MemoryView":1346
+ *                             int ndim_other) nogil:
+ *     cdef int i
+ *     cdef int offset = ndim_other - ndim             # <<<<<<<<<<<<<<
+ * 
+ *     for i in range(ndim - 1, -1, -1):
+ */
+  __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim);
+
+  /* "View.MemoryView":1348
+ *     cdef int offset = ndim_other - ndim
+ * 
+ *     for i in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
+ *         mslice.shape[i + offset] = mslice.shape[i]
+ *         mslice.strides[i + offset] = mslice.strides[i]
+ */
+  for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) {
+    __pyx_v_i = __pyx_t_1;
+
+    /* "View.MemoryView":1349
+ * 
+ *     for i in range(ndim - 1, -1, -1):
+ *         mslice.shape[i + offset] = mslice.shape[i]             # <<<<<<<<<<<<<<
+ *         mslice.strides[i + offset] = mslice.strides[i]
+ *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
+ */
+    (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]);
+
+    /* "View.MemoryView":1350
+ *     for i in range(ndim - 1, -1, -1):
+ *         mslice.shape[i + offset] = mslice.shape[i]
+ *         mslice.strides[i + offset] = mslice.strides[i]             # <<<<<<<<<<<<<<
+ *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
+ * 
+ */
+    (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]);
+
+    /* "View.MemoryView":1351
+ *         mslice.shape[i + offset] = mslice.shape[i]
+ *         mslice.strides[i + offset] = mslice.strides[i]
+ *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]             # <<<<<<<<<<<<<<
+ * 
+ *     for i in range(offset):
+ */
+    (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]);
+  }
+
+  /* "View.MemoryView":1353
+ *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
+ * 
+ *     for i in range(offset):             # <<<<<<<<<<<<<<
+ *         mslice.shape[i] = 1
+ *         mslice.strides[i] = mslice.strides[0]
+ */
+  __pyx_t_1 = __pyx_v_offset;
+  __pyx_t_2 = __pyx_t_1;
+  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+    __pyx_v_i = __pyx_t_3;
+
+    /* "View.MemoryView":1354
+ * 
+ *     for i in range(offset):
+ *         mslice.shape[i] = 1             # <<<<<<<<<<<<<<
+ *         mslice.strides[i] = mslice.strides[0]
+ *         mslice.suboffsets[i] = -1
+ */
+    (__pyx_v_mslice->shape[__pyx_v_i]) = 1;
+
+    /* "View.MemoryView":1355
+ *     for i in range(offset):
+ *         mslice.shape[i] = 1
+ *         mslice.strides[i] = mslice.strides[0]             # <<<<<<<<<<<<<<
+ *         mslice.suboffsets[i] = -1
+ * 
+ */
+    (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]);
+
+    /* "View.MemoryView":1356
+ *         mslice.shape[i] = 1
+ *         mslice.strides[i] = mslice.strides[0]
+ *         mslice.suboffsets[i] = -1             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+    (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L;
+  }
+
+  /* "View.MemoryView":1342
+ * 
+ * @cname('__pyx_memoryview_broadcast_leading')
+ * cdef void broadcast_leading(__Pyx_memviewslice *mslice,             # <<<<<<<<<<<<<<
+ *                             int ndim,
+ *                             int ndim_other) nogil:
+ */
+
+  /* function exit code */
+}
+
+/* "View.MemoryView":1364
+ * 
+ * @cname('__pyx_memoryview_refcount_copying')
+ * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object,             # <<<<<<<<<<<<<<
+ *                            int ndim, bint inc) nogil:
+ * 
+ */
+
+static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) {
+  int __pyx_t_1;
+
+  /* "View.MemoryView":1368
+ * 
+ * 
+ *     if dtype_is_object:             # <<<<<<<<<<<<<<
+ *         refcount_objects_in_slice_with_gil(dst.data, dst.shape,
+ *                                            dst.strides, ndim, inc)
+ */
+  __pyx_t_1 = (__pyx_v_dtype_is_object != 0);
+  if (__pyx_t_1) {
+
+    /* "View.MemoryView":1369
+ * 
+ *     if dtype_is_object:
+ *         refcount_objects_in_slice_with_gil(dst.data, dst.shape,             # <<<<<<<<<<<<<<
+ *                                            dst.strides, ndim, inc)
+ * 
+ */
+    __pyx_memoryview_refcount_objects_in_slice_with_gil(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_inc);
+
+    /* "View.MemoryView":1368
+ * 
+ * 
+ *     if dtype_is_object:             # <<<<<<<<<<<<<<
+ *         refcount_objects_in_slice_with_gil(dst.data, dst.shape,
+ *                                            dst.strides, ndim, inc)
+ */
+  }
+
+  /* "View.MemoryView":1364
+ * 
+ * @cname('__pyx_memoryview_refcount_copying')
+ * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object,             # <<<<<<<<<<<<<<
+ *                            int ndim, bint inc) nogil:
+ * 
+ */
+
+  /* function exit code */
+}
+
+/* "View.MemoryView":1373
+ * 
+ * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
+ * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                                              Py_ssize_t *strides, int ndim,
+ *                                              bint inc) with gil:
+ */
+
+static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
+  __Pyx_RefNannyDeclarations
+  #ifdef WITH_THREAD
+  PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
+  #endif
+  __Pyx_RefNannySetupContext("refcount_objects_in_slice_with_gil", 0);
+
+  /* "View.MemoryView":1376
+ *                                              Py_ssize_t *strides, int ndim,
+ *                                              bint inc) with gil:
+ *     refcount_objects_in_slice(data, shape, strides, ndim, inc)             # <<<<<<<<<<<<<<
+ * 
+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ */
+  __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, __pyx_v_shape, __pyx_v_strides, __pyx_v_ndim, __pyx_v_inc);
+
+  /* "View.MemoryView":1373
+ * 
+ * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
+ * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                                              Py_ssize_t *strides, int ndim,
+ *                                              bint inc) with gil:
+ */
+
+  /* function exit code */
+  __Pyx_RefNannyFinishContext();
+  #ifdef WITH_THREAD
+  __Pyx_PyGILState_Release(__pyx_gilstate_save);
+  #endif
+}
+
+/* "View.MemoryView":1379
+ * 
+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                                     Py_ssize_t *strides, int ndim, bint inc):
+ *     cdef Py_ssize_t i
+ */
+
+static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
+  CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+  __Pyx_RefNannyDeclarations
+  Py_ssize_t __pyx_t_1;
+  Py_ssize_t __pyx_t_2;
+  Py_ssize_t __pyx_t_3;
+  int __pyx_t_4;
+  __Pyx_RefNannySetupContext("refcount_objects_in_slice", 0);
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+  /* "View.MemoryView":1383
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+ * 
+ *     for i in range(shape[0]):             # <<<<<<<<<<<<<<
+ *         if ndim == 1:
+ *             if inc:
+ */
+  __pyx_t_1 = (__pyx_v_shape[0]);
+  __pyx_t_2 = __pyx_t_1;
+  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
+    __pyx_v_i = __pyx_t_3;
+
+    /* "View.MemoryView":1384
+ * 
+ *     for i in range(shape[0]):
+ *         if ndim == 1:             # <<<<<<<<<<<<<<
+ *             if inc:
+ *                 Py_INCREF((<PyObject **> data)[0])
+ */
+    __pyx_t_4 = ((__pyx_v_ndim == 1) != 0);
+    if (__pyx_t_4) {
+
+      /* "View.MemoryView":1385
+ *     for i in range(shape[0]):
+ *         if ndim == 1:
+ *             if inc:             # <<<<<<<<<<<<<<
+ *                 Py_INCREF((<PyObject **> data)[0])
+ *             else:
+ */
+      __pyx_t_4 = (__pyx_v_inc != 0);
+      if (__pyx_t_4) {
+
+        /* "View.MemoryView":1386
+ *         if ndim == 1:
+ *             if inc:
+ *                 Py_INCREF((<PyObject **> data)[0])             # <<<<<<<<<<<<<<
+ *             else:
+ *                 Py_DECREF((<PyObject **> data)[0])
+ */
+        Py_INCREF((((PyObject **)__pyx_v_data)[0]));
+
+        /* "View.MemoryView":1385
+ *     for i in range(shape[0]):
+ *         if ndim == 1:
+ *             if inc:             # <<<<<<<<<<<<<<
+ *                 Py_INCREF((<PyObject **> data)[0])
+ *             else:
+ */
+        goto __pyx_L6;
+      }
+
+      /* "View.MemoryView":1388
+ *                 Py_INCREF((<PyObject **> data)[0])
+ *             else:
+ *                 Py_DECREF((<PyObject **> data)[0])             # <<<<<<<<<<<<<<
+ *         else:
+ *             refcount_objects_in_slice(data, shape + 1, strides + 1,
+ */
+      /*else*/ {
+        Py_DECREF((((PyObject **)__pyx_v_data)[0]));
+      }
+      __pyx_L6:;
+
+      /* "View.MemoryView":1384
+ * 
+ *     for i in range(shape[0]):
+ *         if ndim == 1:             # <<<<<<<<<<<<<<
+ *             if inc:
+ *                 Py_INCREF((<PyObject **> data)[0])
+ */
+      goto __pyx_L5;
+    }
+
+    /* "View.MemoryView":1390
+ *                 Py_DECREF((<PyObject **> data)[0])
+ *         else:
+ *             refcount_objects_in_slice(data, shape + 1, strides + 1,             # <<<<<<<<<<<<<<
+ *                                       ndim - 1, inc)
+ * 
+ */
+    /*else*/ {
+
+      /* "View.MemoryView":1391
+ *         else:
+ *             refcount_objects_in_slice(data, shape + 1, strides + 1,
+ *                                       ndim - 1, inc)             # <<<<<<<<<<<<<<
+ * 
+ *         data += strides[0]
+ */
+      __pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc);
+    }
+    __pyx_L5:;
+
+    /* "View.MemoryView":1393
+ *                                       ndim - 1, inc)
+ * 
+ *         data += strides[0]             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+    __pyx_v_data = (__pyx_v_data + (__pyx_v_strides[0]));
+  }
+
+  /* "View.MemoryView":1379
+ * 
+ * @cname('__pyx_memoryview_refcount_objects_in_slice')
+ * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                                     Py_ssize_t *strides, int ndim, bint inc):
+ *     cdef Py_ssize_t i
+ */
+
+  /* function exit code */
+  __Pyx_RefNannyFinishContext();
+}
+
+/* "View.MemoryView":1399
+ * 
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim,             # <<<<<<<<<<<<<<
+ *                               size_t itemsize, void *item,
+ *                               bint dtype_is_object) nogil:
+ */
+
+static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {
+
+  /* "View.MemoryView":1402
+ *                               size_t itemsize, void *item,
+ *                               bint dtype_is_object) nogil:
+ *     refcount_copying(dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
+ *     _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ *                          itemsize, item)
+ */
+  __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
+
+  /* "View.MemoryView":1403
+ *                               bint dtype_is_object) nogil:
+ *     refcount_copying(dst, dtype_is_object, ndim, False)
+ *     _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,             # <<<<<<<<<<<<<<
+ *                          itemsize, item)
+ *     refcount_copying(dst, dtype_is_object, ndim, True)
+ */
+  __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item);
+
+  /* "View.MemoryView":1405
+ *     _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
+ *                          itemsize, item)
+ *     refcount_copying(dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
+
+  /* "View.MemoryView":1399
+ * 
+ * @cname('__pyx_memoryview_slice_assign_scalar')
+ * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim,             # <<<<<<<<<<<<<<
+ *                               size_t itemsize, void *item,
+ *                               bint dtype_is_object) nogil:
+ */
+
+  /* function exit code */
+}
+
+/* "View.MemoryView":1409
+ * 
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                               Py_ssize_t *strides, int ndim,
+ *                               size_t itemsize, void *item) nogil:
+ */
+
+static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
+  CYTHON_UNUSED Py_ssize_t __pyx_v_i;
+  Py_ssize_t __pyx_v_stride;
+  Py_ssize_t __pyx_v_extent;
+  int __pyx_t_1;
+  Py_ssize_t __pyx_t_2;
+  Py_ssize_t __pyx_t_3;
+  Py_ssize_t __pyx_t_4;
+
+  /* "View.MemoryView":1413
+ *                               size_t itemsize, void *item) nogil:
+ *     cdef Py_ssize_t i
+ *     cdef Py_ssize_t stride = strides[0]             # <<<<<<<<<<<<<<
+ *     cdef Py_ssize_t extent = shape[0]
+ * 
+ */
+  __pyx_v_stride = (__pyx_v_strides[0]);
+
+  /* "View.MemoryView":1414
+ *     cdef Py_ssize_t i
+ *     cdef Py_ssize_t stride = strides[0]
+ *     cdef Py_ssize_t extent = shape[0]             # <<<<<<<<<<<<<<
+ * 
+ *     if ndim == 1:
+ */
+  __pyx_v_extent = (__pyx_v_shape[0]);
+
+  /* "View.MemoryView":1416
+ *     cdef Py_ssize_t extent = shape[0]
+ * 
+ *     if ndim == 1:             # <<<<<<<<<<<<<<
+ *         for i in range(extent):
+ *             memcpy(data, item, itemsize)
+ */
+  __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
+  if (__pyx_t_1) {
+
+    /* "View.MemoryView":1417
+ * 
+ *     if ndim == 1:
+ *         for i in range(extent):             # <<<<<<<<<<<<<<
+ *             memcpy(data, item, itemsize)
+ *             data += stride
+ */
+    __pyx_t_2 = __pyx_v_extent;
+    __pyx_t_3 = __pyx_t_2;
+    for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
+      __pyx_v_i = __pyx_t_4;
+
+      /* "View.MemoryView":1418
+ *     if ndim == 1:
+ *         for i in range(extent):
+ *             memcpy(data, item, itemsize)             # <<<<<<<<<<<<<<
+ *             data += stride
+ *     else:
+ */
+      (void)(memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize));
+
+      /* "View.MemoryView":1419
+ *         for i in range(extent):
+ *             memcpy(data, item, itemsize)
+ *             data += stride             # <<<<<<<<<<<<<<
+ *     else:
+ *         for i in range(extent):
+ */
+      __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+    }
+
+    /* "View.MemoryView":1416
+ *     cdef Py_ssize_t extent = shape[0]
+ * 
+ *     if ndim == 1:             # <<<<<<<<<<<<<<
+ *         for i in range(extent):
+ *             memcpy(data, item, itemsize)
+ */
+    goto __pyx_L3;
+  }
+
+  /* "View.MemoryView":1421
+ *             data += stride
+ *     else:
+ *         for i in range(extent):             # <<<<<<<<<<<<<<
+ *             _slice_assign_scalar(data, shape + 1, strides + 1,
+ *                                 ndim - 1, itemsize, item)
+ */
+  /*else*/ {
+    __pyx_t_2 = __pyx_v_extent;
+    __pyx_t_3 = __pyx_t_2;
+    for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
+      __pyx_v_i = __pyx_t_4;
+
+      /* "View.MemoryView":1422
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+ *             _slice_assign_scalar(data, shape + 1, strides + 1,             # <<<<<<<<<<<<<<
+ *                                 ndim - 1, itemsize, item)
+ *             data += stride
+ */
+      __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item);
+
+      /* "View.MemoryView":1424
+ *             _slice_assign_scalar(data, shape + 1, strides + 1,
+ *                                 ndim - 1, itemsize, item)
+ *             data += stride             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+      __pyx_v_data = (__pyx_v_data + __pyx_v_stride);
+    }
+  }
+  __pyx_L3:;
+
+  /* "View.MemoryView":1409
+ * 
+ * @cname('__pyx_memoryview__slice_assign_scalar')
+ * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
+ *                               Py_ssize_t *strides, int ndim,
+ *                               size_t itemsize, void *item) nogil:
+ */
+
+  /* function exit code */
+}
+
+/* "(tree fragment)":1
+ * def __pyx_unpickle_Enum(__pyx_type, long __pyx_checksum, __pyx_state):             # <<<<<<<<<<<<<<
+ *     cdef object __pyx_PickleError
+ *     cdef object __pyx_result
+ */
+
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+      __pyx_t_8 = PyMethod_GET_SELF(__pyx_t_7);
+      if (likely(__pyx_t_8)) {
+        PyObject* function = PyMethod_GET_FUNCTION(__pyx_t_7);
+        __Pyx_INCREF(__pyx_t_8);
+        __Pyx_INCREF(function);
+        __Pyx_DECREF_SET(__pyx_t_7, function);
+      }
+    }
+    __pyx_t_1 = (__pyx_t_8) ? __Pyx_PyObject_Call2Args(__pyx_t_7, __pyx_t_8, __pyx_t_6) : __Pyx_PyObject_CallOneArg(__pyx_t_7, __pyx_t_6);
+    __Pyx_XDECREF(__pyx_t_8); __pyx_t_8 = 0;
+    __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+    if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 14, __pyx_L1_error)
+    __Pyx_GOTREF(__pyx_t_1);
+    __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
+    __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
+
+    /* "(tree fragment)":13
+ * cdef __pyx_unpickle_Enum__set_state(Enum __pyx_result, tuple __pyx_state):
+ *     __pyx_result.name = __pyx_state[0]
+ *     if len(__pyx_state) > 1 and hasattr(__pyx_result, '__dict__'):             # <<<<<<<<<<<<<<
+ *         __pyx_result.__dict__.update(__pyx_state[1])
+ */
+  }
+
+  /* "(tree fragment)":11
+ *         __pyx_unpickle_Enum__set_state(<Enum> __pyx_result, __pyx_state)
+ *     return __pyx_result
+ * cdef __pyx_unpickle_Enum__set_state(Enum __pyx_result, tuple __pyx_state):             # <<<<<<<<<<<<<<
+ *     __pyx_result.name = __pyx_state[0]
+ *     if len(__pyx_state) > 1 and hasattr(__pyx_result, '__dict__'):
+ */
+
+  /* function exit code */
+  __pyx_r = Py_None; __Pyx_INCREF(Py_None);
+  goto __pyx_L0;
+  __pyx_L1_error:;
+  __Pyx_XDECREF(__pyx_t_1);
+  __Pyx_XDECREF(__pyx_t_6);
+  __Pyx_XDECREF(__pyx_t_7);
+  __Pyx_XDECREF(__pyx_t_8);
+  __Pyx_AddTraceback("View.MemoryView.__pyx_unpickle_Enum__set_state", __pyx_clineno, __pyx_lineno, __pyx_filename);
+  __pyx_r = 0;
+  __pyx_L0:;
+  __Pyx_XGIVEREF(__pyx_r);
+  __Pyx_RefNannyFinishContext();
+  return __pyx_r;
+}
+static struct __pyx_vtabstruct_array __pyx_vtable_array;
+
+static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) {
+  struct __pyx_array_obj *p;
+  PyObject *o;
+  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+    o = (*t->tp_alloc)(t, 0);
+  } else {
+    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+  }
+  if (unlikely(!o)) return 0;
+  p = ((struct __pyx_array_obj *)o);
+  p->__pyx_vtab = __pyx_vtabptr_array;
+  p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None);
+  p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None);
+  if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad;
+  return o;
+  bad:
+  Py_DECREF(o); o = 0;
+  return NULL;
+}
+
+static void __pyx_tp_dealloc_array(PyObject *o) {
+  struct __pyx_array_obj *p = (struct __pyx_array_obj *)o;
+  #if CYTHON_USE_TP_FINALIZE
+  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
+    if (PyObject_CallFinalizerFromDealloc(o)) return;
+  }
+  #endif
+  {
+    PyObject *etype, *eval, *etb;
+    PyErr_Fetch(&etype, &eval, &etb);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1);
+    __pyx_array___dealloc__(o);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1);
+    PyErr_Restore(etype, eval, etb);
+  }
+  Py_CLEAR(p->mode);
+  Py_CLEAR(p->_format);
+  (*Py_TYPE(o)->tp_free)(o);
+}
+static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) {
+  PyObject *r;
+  PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+  r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+  Py_DECREF(x);
+  return r;
+}
+
+static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
+  if (v) {
+    return __pyx_array___setitem__(o, i, v);
+  }
+  else {
+    PyErr_Format(PyExc_NotImplementedError,
+      "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+    return -1;
+  }
+}
+
+static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
+  PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n);
+  if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+    PyErr_Clear();
+    v = __pyx_array___getattr__(o, n);
+  }
+  return v;
+}
+
+static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o);
+}
+
+static PyMethodDef __pyx_methods_array[] = {
+  {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
+  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0},
+  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0},
+  {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_array[] = {
+  {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0},
+  {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_array = {
+  __pyx_array___len__, /*sq_length*/
+  0, /*sq_concat*/
+  0, /*sq_repeat*/
+  __pyx_sq_item_array, /*sq_item*/
+  0, /*sq_slice*/
+  0, /*sq_ass_item*/
+  0, /*sq_ass_slice*/
+  0, /*sq_contains*/
+  0, /*sq_inplace_concat*/
+  0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_array = {
+  __pyx_array___len__, /*mp_length*/
+  __pyx_array___getitem__, /*mp_subscript*/
+  __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_array = {
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getreadbuffer*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getwritebuffer*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getsegcount*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getcharbuffer*/
+  #endif
+  __pyx_array_getbuffer, /*bf_getbuffer*/
+  0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_array = {
+  PyVarObject_HEAD_INIT(0, 0)
+  "monotonic_align.core.array", /*tp_name*/
+  sizeof(struct __pyx_array_obj), /*tp_basicsize*/
+  0, /*tp_itemsize*/
+  __pyx_tp_dealloc_array, /*tp_dealloc*/
+  #if PY_VERSION_HEX < 0x030800b4
+  0, /*tp_print*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4
+  0, /*tp_vectorcall_offset*/
+  #endif
+  0, /*tp_getattr*/
+  0, /*tp_setattr*/
+  #if PY_MAJOR_VERSION < 3
+  0, /*tp_compare*/
+  #endif
+  #if PY_MAJOR_VERSION >= 3
+  0, /*tp_as_async*/
+  #endif
+  0, /*tp_repr*/
+  0, /*tp_as_number*/
+  &__pyx_tp_as_sequence_array, /*tp_as_sequence*/
+  &__pyx_tp_as_mapping_array, /*tp_as_mapping*/
+  0, /*tp_hash*/
+  0, /*tp_call*/
+  0, /*tp_str*/
+  __pyx_tp_getattro_array, /*tp_getattro*/
+  0, /*tp_setattro*/
+  &__pyx_tp_as_buffer_array, /*tp_as_buffer*/
+  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
+  0, /*tp_doc*/
+  0, /*tp_traverse*/
+  0, /*tp_clear*/
+  0, /*tp_richcompare*/
+  0, /*tp_weaklistoffset*/
+  0, /*tp_iter*/
+  0, /*tp_iternext*/
+  __pyx_methods_array, /*tp_methods*/
+  0, /*tp_members*/
+  __pyx_getsets_array, /*tp_getset*/
+  0, /*tp_base*/
+  0, /*tp_dict*/
+  0, /*tp_descr_get*/
+  0, /*tp_descr_set*/
+  0, /*tp_dictoffset*/
+  0, /*tp_init*/
+  0, /*tp_alloc*/
+  __pyx_tp_new_array, /*tp_new*/
+  0, /*tp_free*/
+  0, /*tp_is_gc*/
+  0, /*tp_bases*/
+  0, /*tp_mro*/
+  0, /*tp_cache*/
+  0, /*tp_subclasses*/
+  0, /*tp_weaklist*/
+  0, /*tp_del*/
+  0, /*tp_version_tag*/
+  #if PY_VERSION_HEX >= 0x030400a1
+  0, /*tp_finalize*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
+  0, /*tp_vectorcall*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
+  0, /*tp_print*/
+  #endif
+  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
+  0, /*tp_pypy_flags*/
+  #endif
+};
+
+static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
+  struct __pyx_MemviewEnum_obj *p;
+  PyObject *o;
+  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+    o = (*t->tp_alloc)(t, 0);
+  } else {
+    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+  }
+  if (unlikely(!o)) return 0;
+  p = ((struct __pyx_MemviewEnum_obj *)o);
+  p->name = Py_None; Py_INCREF(Py_None);
+  return o;
+}
+
+static void __pyx_tp_dealloc_Enum(PyObject *o) {
+  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+  #if CYTHON_USE_TP_FINALIZE
+  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+    if (PyObject_CallFinalizerFromDealloc(o)) return;
+  }
+  #endif
+  PyObject_GC_UnTrack(o);
+  Py_CLEAR(p->name);
+  (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
+  int e;
+  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+  if (p->name) {
+    e = (*v)(p->name, a); if (e) return e;
+  }
+  return 0;
+}
+
+static int __pyx_tp_clear_Enum(PyObject *o) {
+  PyObject* tmp;
+  struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
+  tmp = ((PyObject*)p->name);
+  p->name = Py_None; Py_INCREF(Py_None);
+  Py_XDECREF(tmp);
+  return 0;
+}
+
+static PyMethodDef __pyx_methods_Enum[] = {
+  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0},
+  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0},
+  {0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_MemviewEnum = {
+  PyVarObject_HEAD_INIT(0, 0)
+  "monotonic_align.core.Enum", /*tp_name*/
+  sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
+  0, /*tp_itemsize*/
+  __pyx_tp_dealloc_Enum, /*tp_dealloc*/
+  #if PY_VERSION_HEX < 0x030800b4
+  0, /*tp_print*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4
+  0, /*tp_vectorcall_offset*/
+  #endif
+  0, /*tp_getattr*/
+  0, /*tp_setattr*/
+  #if PY_MAJOR_VERSION < 3
+  0, /*tp_compare*/
+  #endif
+  #if PY_MAJOR_VERSION >= 3
+  0, /*tp_as_async*/
+  #endif
+  __pyx_MemviewEnum___repr__, /*tp_repr*/
+  0, /*tp_as_number*/
+  0, /*tp_as_sequence*/
+  0, /*tp_as_mapping*/
+  0, /*tp_hash*/
+  0, /*tp_call*/
+  0, /*tp_str*/
+  0, /*tp_getattro*/
+  0, /*tp_setattro*/
+  0, /*tp_as_buffer*/
+  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+  0, /*tp_doc*/
+  __pyx_tp_traverse_Enum, /*tp_traverse*/
+  __pyx_tp_clear_Enum, /*tp_clear*/
+  0, /*tp_richcompare*/
+  0, /*tp_weaklistoffset*/
+  0, /*tp_iter*/
+  0, /*tp_iternext*/
+  __pyx_methods_Enum, /*tp_methods*/
+  0, /*tp_members*/
+  0, /*tp_getset*/
+  0, /*tp_base*/
+  0, /*tp_dict*/
+  0, /*tp_descr_get*/
+  0, /*tp_descr_set*/
+  0, /*tp_dictoffset*/
+  __pyx_MemviewEnum___init__, /*tp_init*/
+  0, /*tp_alloc*/
+  __pyx_tp_new_Enum, /*tp_new*/
+  0, /*tp_free*/
+  0, /*tp_is_gc*/
+  0, /*tp_bases*/
+  0, /*tp_mro*/
+  0, /*tp_cache*/
+  0, /*tp_subclasses*/
+  0, /*tp_weaklist*/
+  0, /*tp_del*/
+  0, /*tp_version_tag*/
+  #if PY_VERSION_HEX >= 0x030400a1
+  0, /*tp_finalize*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
+  0, /*tp_vectorcall*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
+  0, /*tp_print*/
+  #endif
+  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
+  0, /*tp_pypy_flags*/
+  #endif
+};
+static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
+
+static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
+  struct __pyx_memoryview_obj *p;
+  PyObject *o;
+  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
+    o = (*t->tp_alloc)(t, 0);
+  } else {
+    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
+  }
+  if (unlikely(!o)) return 0;
+  p = ((struct __pyx_memoryview_obj *)o);
+  p->__pyx_vtab = __pyx_vtabptr_memoryview;
+  p->obj = Py_None; Py_INCREF(Py_None);
+  p->_size = Py_None; Py_INCREF(Py_None);
+  p->_array_interface = Py_None; Py_INCREF(Py_None);
+  p->view.obj = NULL;
+  if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad;
+  return o;
+  bad:
+  Py_DECREF(o); o = 0;
+  return NULL;
+}
+
+static void __pyx_tp_dealloc_memoryview(PyObject *o) {
+  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+  #if CYTHON_USE_TP_FINALIZE
+  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+    if (PyObject_CallFinalizerFromDealloc(o)) return;
+  }
+  #endif
+  PyObject_GC_UnTrack(o);
+  {
+    PyObject *etype, *eval, *etb;
+    PyErr_Fetch(&etype, &eval, &etb);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1);
+    __pyx_memoryview___dealloc__(o);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1);
+    PyErr_Restore(etype, eval, etb);
+  }
+  Py_CLEAR(p->obj);
+  Py_CLEAR(p->_size);
+  Py_CLEAR(p->_array_interface);
+  (*Py_TYPE(o)->tp_free)(o);
+}
+
+static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
+  int e;
+  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+  if (p->obj) {
+    e = (*v)(p->obj, a); if (e) return e;
+  }
+  if (p->_size) {
+    e = (*v)(p->_size, a); if (e) return e;
+  }
+  if (p->_array_interface) {
+    e = (*v)(p->_array_interface, a); if (e) return e;
+  }
+  if (p->view.obj) {
+    e = (*v)(p->view.obj, a); if (e) return e;
+  }
+  return 0;
+}
+
+static int __pyx_tp_clear_memoryview(PyObject *o) {
+  PyObject* tmp;
+  struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
+  tmp = ((PyObject*)p->obj);
+  p->obj = Py_None; Py_INCREF(Py_None);
+  Py_XDECREF(tmp);
+  tmp = ((PyObject*)p->_size);
+  p->_size = Py_None; Py_INCREF(Py_None);
+  Py_XDECREF(tmp);
+  tmp = ((PyObject*)p->_array_interface);
+  p->_array_interface = Py_None; Py_INCREF(Py_None);
+  Py_XDECREF(tmp);
+  Py_CLEAR(p->view.obj);
+  return 0;
+}
+static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
+  PyObject *r;
+  PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
+  r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
+  Py_DECREF(x);
+  return r;
+}
+
+static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
+  if (v) {
+    return __pyx_memoryview___setitem__(o, i, v);
+  }
+  else {
+    PyErr_Format(PyExc_NotImplementedError,
+      "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
+    return -1;
+  }
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o);
+}
+
+static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o);
+}
+
+static PyMethodDef __pyx_methods_memoryview[] = {
+  {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
+  {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
+  {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
+  {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
+  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0},
+  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0},
+  {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets_memoryview[] = {
+  {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0},
+  {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0},
+  {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0},
+  {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0},
+  {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0},
+  {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0},
+  {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0},
+  {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0},
+  {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0},
+  {0, 0, 0, 0, 0}
+};
+
+static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
+  __pyx_memoryview___len__, /*sq_length*/
+  0, /*sq_concat*/
+  0, /*sq_repeat*/
+  __pyx_sq_item_memoryview, /*sq_item*/
+  0, /*sq_slice*/
+  0, /*sq_ass_item*/
+  0, /*sq_ass_slice*/
+  0, /*sq_contains*/
+  0, /*sq_inplace_concat*/
+  0, /*sq_inplace_repeat*/
+};
+
+static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
+  __pyx_memoryview___len__, /*mp_length*/
+  __pyx_memoryview___getitem__, /*mp_subscript*/
+  __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
+};
+
+static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getreadbuffer*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getwritebuffer*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getsegcount*/
+  #endif
+  #if PY_MAJOR_VERSION < 3
+  0, /*bf_getcharbuffer*/
+  #endif
+  __pyx_memoryview_getbuffer, /*bf_getbuffer*/
+  0, /*bf_releasebuffer*/
+};
+
+static PyTypeObject __pyx_type___pyx_memoryview = {
+  PyVarObject_HEAD_INIT(0, 0)
+  "monotonic_align.core.memoryview", /*tp_name*/
+  sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
+  0, /*tp_itemsize*/
+  __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
+  #if PY_VERSION_HEX < 0x030800b4
+  0, /*tp_print*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4
+  0, /*tp_vectorcall_offset*/
+  #endif
+  0, /*tp_getattr*/
+  0, /*tp_setattr*/
+  #if PY_MAJOR_VERSION < 3
+  0, /*tp_compare*/
+  #endif
+  #if PY_MAJOR_VERSION >= 3
+  0, /*tp_as_async*/
+  #endif
+  __pyx_memoryview___repr__, /*tp_repr*/
+  0, /*tp_as_number*/
+  &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
+  &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
+  0, /*tp_hash*/
+  0, /*tp_call*/
+  __pyx_memoryview___str__, /*tp_str*/
+  0, /*tp_getattro*/
+  0, /*tp_setattro*/
+  &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
+  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+  0, /*tp_doc*/
+  __pyx_tp_traverse_memoryview, /*tp_traverse*/
+  __pyx_tp_clear_memoryview, /*tp_clear*/
+  0, /*tp_richcompare*/
+  0, /*tp_weaklistoffset*/
+  0, /*tp_iter*/
+  0, /*tp_iternext*/
+  __pyx_methods_memoryview, /*tp_methods*/
+  0, /*tp_members*/
+  __pyx_getsets_memoryview, /*tp_getset*/
+  0, /*tp_base*/
+  0, /*tp_dict*/
+  0, /*tp_descr_get*/
+  0, /*tp_descr_set*/
+  0, /*tp_dictoffset*/
+  0, /*tp_init*/
+  0, /*tp_alloc*/
+  __pyx_tp_new_memoryview, /*tp_new*/
+  0, /*tp_free*/
+  0, /*tp_is_gc*/
+  0, /*tp_bases*/
+  0, /*tp_mro*/
+  0, /*tp_cache*/
+  0, /*tp_subclasses*/
+  0, /*tp_weaklist*/
+  0, /*tp_del*/
+  0, /*tp_version_tag*/
+  #if PY_VERSION_HEX >= 0x030400a1
+  0, /*tp_finalize*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
+  0, /*tp_vectorcall*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
+  0, /*tp_print*/
+  #endif
+  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
+  0, /*tp_pypy_flags*/
+  #endif
+};
+static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;
+
+static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
+  struct __pyx_memoryviewslice_obj *p;
+  PyObject *o = __pyx_tp_new_memoryview(t, a, k);
+  if (unlikely(!o)) return 0;
+  p = ((struct __pyx_memoryviewslice_obj *)o);
+  p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
+  p->from_object = Py_None; Py_INCREF(Py_None);
+  p->from_slice.memview = NULL;
+  return o;
+}
+
+static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
+  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+  #if CYTHON_USE_TP_FINALIZE
+  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
+    if (PyObject_CallFinalizerFromDealloc(o)) return;
+  }
+  #endif
+  PyObject_GC_UnTrack(o);
+  {
+    PyObject *etype, *eval, *etb;
+    PyErr_Fetch(&etype, &eval, &etb);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1);
+    __pyx_memoryviewslice___dealloc__(o);
+    __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1);
+    PyErr_Restore(etype, eval, etb);
+  }
+  Py_CLEAR(p->from_object);
+  PyObject_GC_Track(o);
+  __pyx_tp_dealloc_memoryview(o);
+}
+
+static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
+  int e;
+  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+  e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
+  if (p->from_object) {
+    e = (*v)(p->from_object, a); if (e) return e;
+  }
+  return 0;
+}
+
+static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
+  PyObject* tmp;
+  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
+  __pyx_tp_clear_memoryview(o);
+  tmp = ((PyObject*)p->from_object);
+  p->from_object = Py_None; Py_INCREF(Py_None);
+  Py_XDECREF(tmp);
+  __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
+  return 0;
+}
+
+static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
+  return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o);
+}
+
+static PyMethodDef __pyx_methods__memoryviewslice[] = {
+  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0},
+  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0},
+  {0, 0, 0, 0}
+};
+
+static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
+  {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0},
+  {0, 0, 0, 0, 0}
+};
+
+static PyTypeObject __pyx_type___pyx_memoryviewslice = {
+  PyVarObject_HEAD_INIT(0, 0)
+  "monotonic_align.core._memoryviewslice", /*tp_name*/
+  sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
+  0, /*tp_itemsize*/
+  __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
+  #if PY_VERSION_HEX < 0x030800b4
+  0, /*tp_print*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4
+  0, /*tp_vectorcall_offset*/
+  #endif
+  0, /*tp_getattr*/
+  0, /*tp_setattr*/
+  #if PY_MAJOR_VERSION < 3
+  0, /*tp_compare*/
+  #endif
+  #if PY_MAJOR_VERSION >= 3
+  0, /*tp_as_async*/
+  #endif
+  #if CYTHON_COMPILING_IN_PYPY
+  __pyx_memoryview___repr__, /*tp_repr*/
+  #else
+  0, /*tp_repr*/
+  #endif
+  0, /*tp_as_number*/
+  0, /*tp_as_sequence*/
+  0, /*tp_as_mapping*/
+  0, /*tp_hash*/
+  0, /*tp_call*/
+  #if CYTHON_COMPILING_IN_PYPY
+  __pyx_memoryview___str__, /*tp_str*/
+  #else
+  0, /*tp_str*/
+  #endif
+  0, /*tp_getattro*/
+  0, /*tp_setattro*/
+  0, /*tp_as_buffer*/
+  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
+  "Internal class for passing memoryview slices to Python", /*tp_doc*/
+  __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
+  __pyx_tp_clear__memoryviewslice, /*tp_clear*/
+  0, /*tp_richcompare*/
+  0, /*tp_weaklistoffset*/
+  0, /*tp_iter*/
+  0, /*tp_iternext*/
+  __pyx_methods__memoryviewslice, /*tp_methods*/
+  0, /*tp_members*/
+  __pyx_getsets__memoryviewslice, /*tp_getset*/
+  0, /*tp_base*/
+  0, /*tp_dict*/
+  0, /*tp_descr_get*/
+  0, /*tp_descr_set*/
+  0, /*tp_dictoffset*/
+  0, /*tp_init*/
+  0, /*tp_alloc*/
+  __pyx_tp_new__memoryviewslice, /*tp_new*/
+  0, /*tp_free*/
+  0, /*tp_is_gc*/
+  0, /*tp_bases*/
+  0, /*tp_mro*/
+  0, /*tp_cache*/
+  0, /*tp_subclasses*/
+  0, /*tp_weaklist*/
+  0, /*tp_del*/
+  0, /*tp_version_tag*/
+  #if PY_VERSION_HEX >= 0x030400a1
+  0, /*tp_finalize*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
+  0, /*tp_vectorcall*/
+  #endif
+  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
+  0, /*tp_print*/
+  #endif
+  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
+  0, /*tp_pypy_flags*/
+  #endif
+};
+
+static PyMethodDef __pyx_methods[] = {
+  {"maximum_path_c", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_15monotonic_align_4core_1maximum_path_c, METH_VARARGS|METH_KEYWORDS, 0},
+  {0, 0, 0, 0}
+};
+
+#if PY_MAJOR_VERSION >= 3
+#if CYTHON_PEP489_MULTI_PHASE_INIT
+static PyObject* __pyx_pymod_create(PyObject *spec, PyModuleDef *def); /*proto*/
+static int __pyx_pymod_exec_core(PyObject* module); /*proto*/
+static PyModuleDef_Slot __pyx_moduledef_slots[] = {
+  {Py_mod_create, (void*)__pyx_pymod_create},
+  {Py_mod_exec, (void*)__pyx_pymod_exec_core},
+  {0, NULL}
+};
+#endif
+
+static struct PyModuleDef __pyx_moduledef = {
+    PyModuleDef_HEAD_INIT,
+    "core",
+    0, /* m_doc */
+  #if CYTHON_PEP489_MULTI_PHASE_INIT
+    0, /* m_size */
+  #else
+    -1, /* m_size */
+  #endif
+    __pyx_methods /* m_methods */,
+  #if CYTHON_PEP489_MULTI_PHASE_INIT
+    __pyx_moduledef_slots, /* m_slots */
+  #else
+    NULL, /* m_reload */
+  #endif
+    NULL, /* m_traverse */
+    NULL, /* m_clear */
+    NULL /* m_free */
+};
+#endif
+#ifndef CYTHON_SMALL_CODE
+#if defined(__clang__)
+    #define CYTHON_SMALL_CODE
+#elif defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 3))
+    #define CYTHON_SMALL_CODE __attribute__((cold))
+#else
+    #define CYTHON_SMALL_CODE
+#endif
+#endif
+
+static __Pyx_StringTabEntry __pyx_string_tab[] = {
+  {&__pyx_n_s_ASCII, __pyx_k_ASCII, sizeof(__pyx_k_ASCII), 0, 0, 1, 1},
+  {&__pyx_kp_s_Buffer_view_does_not_expose_stri, __pyx_k_Buffer_view_does_not_expose_stri, sizeof(__pyx_k_Buffer_view_does_not_expose_stri), 0, 0, 1, 0},
+  {&__pyx_kp_s_Can_only_create_a_buffer_that_is, __pyx_k_Can_only_create_a_buffer_that_is, sizeof(__pyx_k_Can_only_create_a_buffer_that_is), 0, 0, 1, 0},
+  {&__pyx_kp_s_Cannot_assign_to_read_only_memor, __pyx_k_Cannot_assign_to_read_only_memor, sizeof(__pyx_k_Cannot_assign_to_read_only_memor), 0, 0, 1, 0},
+  {&__pyx_kp_s_Cannot_create_writable_memory_vi, __pyx_k_Cannot_create_writable_memory_vi, sizeof(__pyx_k_Cannot_create_writable_memory_vi), 0, 0, 1, 0},
+  {&__pyx_kp_s_Cannot_index_with_type_s, __pyx_k_Cannot_index_with_type_s, sizeof(__pyx_k_Cannot_index_with_type_s), 0, 0, 1, 0},
+  {&__pyx_n_s_Ellipsis, __pyx_k_Ellipsis, sizeof(__pyx_k_Ellipsis), 0, 0, 1, 1},
+  {&__pyx_kp_s_Empty_shape_tuple_for_cython_arr, __pyx_k_Empty_shape_tuple_for_cython_arr, sizeof(__pyx_k_Empty_shape_tuple_for_cython_arr), 0, 0, 1, 0},
+  {&__pyx_kp_s_Incompatible_checksums_0x_x_vs_0, __pyx_k_Incompatible_checksums_0x_x_vs_0, sizeof(__pyx_k_Incompatible_checksums_0x_x_vs_0), 0, 0, 1, 0},
+  {&__pyx_n_s_IndexError, __pyx_k_IndexError, sizeof(__pyx_k_IndexError), 0, 0, 1, 1},
+  {&__pyx_kp_s_Indirect_dimensions_not_supporte, __pyx_k_Indirect_dimensions_not_supporte, sizeof(__pyx_k_Indirect_dimensions_not_supporte), 0, 0, 1, 0},
+  {&__pyx_kp_s_Invalid_mode_expected_c_or_fortr, __pyx_k_Invalid_mode_expected_c_or_fortr, sizeof(__pyx_k_Invalid_mode_expected_c_or_fortr), 0, 0, 1, 0},
+  {&__pyx_kp_s_Invalid_shape_in_axis_d_d, __pyx_k_Invalid_shape_in_axis_d_d, sizeof(__pyx_k_Invalid_shape_in_axis_d_d), 0, 0, 1, 0},
+  {&__pyx_n_s_MemoryError, __pyx_k_MemoryError, sizeof(__pyx_k_MemoryError), 0, 0, 1, 1},
+  {&__pyx_kp_s_MemoryView_of_r_at_0x_x, __pyx_k_MemoryView_of_r_at_0x_x, sizeof(__pyx_k_MemoryView_of_r_at_0x_x), 0, 0, 1, 0},
+  {&__pyx_kp_s_MemoryView_of_r_object, __pyx_k_MemoryView_of_r_object, sizeof(__pyx_k_MemoryView_of_r_object), 0, 0, 1, 0},
+  {&__pyx_n_b_O, __pyx_k_O, sizeof(__pyx_k_O), 0, 0, 0, 1},
+  {&__pyx_kp_s_Out_of_bounds_on_buffer_access_a, __pyx_k_Out_of_bounds_on_buffer_access_a, sizeof(__pyx_k_Out_of_bounds_on_buffer_access_a), 0, 0, 1, 0},
+  {&__pyx_n_s_PickleError, __pyx_k_PickleError, sizeof(__pyx_k_PickleError), 0, 0, 1, 1},
+  {&__pyx_n_s_TypeError, __pyx_k_TypeError, sizeof(__pyx_k_TypeError), 0, 0, 1, 1},
+  {&__pyx_kp_s_Unable_to_convert_item_to_object, __pyx_k_Unable_to_convert_item_to_object, sizeof(__pyx_k_Unable_to_convert_item_to_object), 0, 0, 1, 0},
+  {&__pyx_n_s_ValueError, __pyx_k_ValueError, sizeof(__pyx_k_ValueError), 0, 0, 1, 1},
+  {&__pyx_n_s_View_MemoryView, __pyx_k_View_MemoryView, sizeof(__pyx_k_View_MemoryView), 0, 0, 1, 1},
+  {&__pyx_n_s_allocate_buffer, __pyx_k_allocate_buffer, sizeof(__pyx_k_allocate_buffer), 0, 0, 1, 1},
+  {&__pyx_n_s_base, __pyx_k_base, sizeof(__pyx_k_base), 0, 0, 1, 1},
+  {&__pyx_n_s_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 0, 1, 1},
+  {&__pyx_n_u_c, __pyx_k_c, sizeof(__pyx_k_c), 0, 1, 0, 1},
+  {&__pyx_n_s_class, __pyx_k_class, sizeof(__pyx_k_class), 0, 0, 1, 1},
+  {&__pyx_n_s_cline_in_traceback, __pyx_k_cline_in_traceback, sizeof(__pyx_k_cline_in_traceback), 0, 0, 1, 1},
+  {&__pyx_kp_s_contiguous_and_direct, __pyx_k_contiguous_and_direct, sizeof(__pyx_k_contiguous_and_direct), 0, 0, 1, 0},
+  {&__pyx_kp_s_contiguous_and_indirect, __pyx_k_contiguous_and_indirect, sizeof(__pyx_k_contiguous_and_indirect), 0, 0, 1, 0},
+  {&__pyx_n_s_dict, __pyx_k_dict, sizeof(__pyx_k_dict), 0, 0, 1, 1},
+  {&__pyx_n_s_dtype_is_object, __pyx_k_dtype_is_object, sizeof(__pyx_k_dtype_is_object), 0, 0, 1, 1},
+  {&__pyx_n_s_encode, __pyx_k_encode, sizeof(__pyx_k_encode), 0, 0, 1, 1},
+  {&__pyx_n_s_enumerate, __pyx_k_enumerate, sizeof(__pyx_k_enumerate), 0, 0, 1, 1},
+  {&__pyx_n_s_error, __pyx_k_error, sizeof(__pyx_k_error), 0, 0, 1, 1},
+  {&__pyx_n_s_flags, __pyx_k_flags, sizeof(__pyx_k_flags), 0, 0, 1, 1},
+  {&__pyx_n_s_format, __pyx_k_format, sizeof(__pyx_k_format), 0, 0, 1, 1},
+  {&__pyx_n_s_fortran, __pyx_k_fortran, sizeof(__pyx_k_fortran), 0, 0, 1, 1},
+  {&__pyx_n_u_fortran, __pyx_k_fortran, sizeof(__pyx_k_fortran), 0, 1, 0, 1},
+  {&__pyx_n_s_getstate, __pyx_k_getstate, sizeof(__pyx_k_getstate), 0, 0, 1, 1},
+  {&__pyx_kp_s_got_differing_extents_in_dimensi, __pyx_k_got_differing_extents_in_dimensi, sizeof(__pyx_k_got_differing_extents_in_dimensi), 0, 0, 1, 0},
+  {&__pyx_n_s_id, __pyx_k_id, sizeof(__pyx_k_id), 0, 0, 1, 1},
+  {&__pyx_n_s_import, __pyx_k_import, sizeof(__pyx_k_import), 0, 0, 1, 1},
+  {&__pyx_n_s_itemsize, __pyx_k_itemsize, sizeof(__pyx_k_itemsize), 0, 0, 1, 1},
+  {&__pyx_kp_s_itemsize_0_for_cython_array, __pyx_k_itemsize_0_for_cython_array, sizeof(__pyx_k_itemsize_0_for_cython_array), 0, 0, 1, 0},
+  {&__pyx_n_s_main, __pyx_k_main, sizeof(__pyx_k_main), 0, 0, 1, 1},
+  {&__pyx_n_s_memview, __pyx_k_memview, sizeof(__pyx_k_memview), 0, 0, 1, 1},
+  {&__pyx_n_s_mode, __pyx_k_mode, sizeof(__pyx_k_mode), 0, 0, 1, 1},
+  {&__pyx_n_s_name, __pyx_k_name, sizeof(__pyx_k_name), 0, 0, 1, 1},
+  {&__pyx_n_s_name_2, __pyx_k_name_2, sizeof(__pyx_k_name_2), 0, 0, 1, 1},
+  {&__pyx_n_s_ndim, __pyx_k_ndim, sizeof(__pyx_k_ndim), 0, 0, 1, 1},
+  {&__pyx_n_s_new, __pyx_k_new, sizeof(__pyx_k_new), 0, 0, 1, 1},
+  {&__pyx_kp_s_no_default___reduce___due_to_non, __pyx_k_no_default___reduce___due_to_non, sizeof(__pyx_k_no_default___reduce___due_to_non), 0, 0, 1, 0},
+  {&__pyx_n_s_obj, __pyx_k_obj, sizeof(__pyx_k_obj), 0, 0, 1, 1},
+  {&__pyx_n_s_pack, __pyx_k_pack, sizeof(__pyx_k_pack), 0, 0, 1, 1},
+  {&__pyx_n_s_paths, __pyx_k_paths, sizeof(__pyx_k_paths), 0, 0, 1, 1},
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+  __Pyx_DECREF_SET(indirect, __pyx_t_1);
+  __Pyx_GIVEREF(__pyx_t_1);
+  __pyx_t_1 = 0;
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+ * 
+ * cdef contiguous = Enum("<contiguous and direct>")             # <<<<<<<<<<<<<<
+ * cdef indirect_contiguous = Enum("<contiguous and indirect>")
+ * 
+ */
+  __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__24, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 292, __pyx_L1_error)
+  __Pyx_GOTREF(__pyx_t_1);
+  __Pyx_XGOTREF(contiguous);
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+  __Pyx_GIVEREF(__pyx_t_1);
+  __pyx_t_1 = 0;
+
+  /* "View.MemoryView":293
+ * 
+ * cdef contiguous = Enum("<contiguous and direct>")
+ * cdef indirect_contiguous = Enum("<contiguous and indirect>")             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  __pyx_t_1 = __Pyx_PyObject_Call(((PyObject *)__pyx_MemviewEnum_type), __pyx_tuple__25, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 293, __pyx_L1_error)
+  __Pyx_GOTREF(__pyx_t_1);
+  __Pyx_XGOTREF(indirect_contiguous);
+  __Pyx_DECREF_SET(indirect_contiguous, __pyx_t_1);
+  __Pyx_GIVEREF(__pyx_t_1);
+  __pyx_t_1 = 0;
+
+  /* "View.MemoryView":317
+ * 
+ * DEF THREAD_LOCKS_PREALLOCATED = 8
+ * cdef int __pyx_memoryview_thread_locks_used = 0             # <<<<<<<<<<<<<<
+ * cdef PyThread_type_lock[THREAD_LOCKS_PREALLOCATED] __pyx_memoryview_thread_locks = [
+ *     PyThread_allocate_lock(),
+ */
+  __pyx_memoryview_thread_locks_used = 0;
+
+  /* "View.MemoryView":318
+ * DEF THREAD_LOCKS_PREALLOCATED = 8
+ * cdef int __pyx_memoryview_thread_locks_used = 0
+ * cdef PyThread_type_lock[THREAD_LOCKS_PREALLOCATED] __pyx_memoryview_thread_locks = [             # <<<<<<<<<<<<<<
+ *     PyThread_allocate_lock(),
+ *     PyThread_allocate_lock(),
+ */
+  __pyx_t_2[0] = PyThread_allocate_lock();
+  __pyx_t_2[1] = PyThread_allocate_lock();
+  __pyx_t_2[2] = PyThread_allocate_lock();
+  __pyx_t_2[3] = PyThread_allocate_lock();
+  __pyx_t_2[4] = PyThread_allocate_lock();
+  __pyx_t_2[5] = PyThread_allocate_lock();
+  __pyx_t_2[6] = PyThread_allocate_lock();
+  __pyx_t_2[7] = PyThread_allocate_lock();
+  memcpy(&(__pyx_memoryview_thread_locks[0]), __pyx_t_2, sizeof(__pyx_memoryview_thread_locks[0]) * (8));
+
+  /* "View.MemoryView":551
+ *         info.obj = self
+ * 
+ *     __pyx_getbuffer = capsule(<void *> &__pyx_memoryview_getbuffer, "getbuffer(obj, view, flags)")             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+  __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 551, __pyx_L1_error)
+  __Pyx_GOTREF(__pyx_t_1);
+  if (PyDict_SetItem((PyObject *)__pyx_memoryview_type->tp_dict, __pyx_n_s_pyx_getbuffer, __pyx_t_1) < 0) __PYX_ERR(1, 551, __pyx_L1_error)
+  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
+  PyType_Modified(__pyx_memoryview_type);
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+  /* "View.MemoryView":997
+ *         return self.from_object
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+ * 
+ * 
+ */
+  __pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 997, __pyx_L1_error)
+  __Pyx_GOTREF(__pyx_t_1);
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+  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
+  PyType_Modified(__pyx_memoryviewslice_type);
+
+  /* "(tree fragment)":1
+ * def __pyx_unpickle_Enum(__pyx_type, long __pyx_checksum, __pyx_state):             # <<<<<<<<<<<<<<
+ *     cdef object __pyx_PickleError
+ *     cdef object __pyx_result
+ */
+  __pyx_t_1 = PyCFunction_NewEx(&__pyx_mdef_15View_dot_MemoryView_1__pyx_unpickle_Enum, NULL, __pyx_n_s_View_MemoryView); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 1, __pyx_L1_error)
+  __Pyx_GOTREF(__pyx_t_1);
+  if (PyDict_SetItem(__pyx_d, __pyx_n_s_pyx_unpickle_Enum, __pyx_t_1) < 0) __PYX_ERR(1, 1, __pyx_L1_error)
+  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
+
+  /* "(tree fragment)":11
+ *         __pyx_unpickle_Enum__set_state(<Enum> __pyx_result, __pyx_state)
+ *     return __pyx_result
+ * cdef __pyx_unpickle_Enum__set_state(Enum __pyx_result, tuple __pyx_state):             # <<<<<<<<<<<<<<
+ *     __pyx_result.name = __pyx_state[0]
+ *     if len(__pyx_state) > 1 and hasattr(__pyx_result, '__dict__'):
+ */
+
+  /*--- Wrapped vars code ---*/
+
+  goto __pyx_L0;
+  __pyx_L1_error:;
+  __Pyx_XDECREF(__pyx_t_1);
+  if (__pyx_m) {
+    if (__pyx_d) {
+      __Pyx_AddTraceback("init monotonic_align.core", __pyx_clineno, __pyx_lineno, __pyx_filename);
+    }
+    Py_CLEAR(__pyx_m);
+  } else if (!PyErr_Occurred()) {
+    PyErr_SetString(PyExc_ImportError, "init monotonic_align.core");
+  }
+  __pyx_L0:;
+  __Pyx_RefNannyFinishContext();
+  #if CYTHON_PEP489_MULTI_PHASE_INIT
+  return (__pyx_m != NULL) ? 0 : -1;
+  #elif PY_MAJOR_VERSION >= 3
+  return __pyx_m;
+  #else
+  return;
+  #endif
+}
+
+/* --- Runtime support code --- */
+/* Refnanny */
+#if CYTHON_REFNANNY
+static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
+    PyObject *m = NULL, *p = NULL;
+    void *r = NULL;
+    m = PyImport_ImportModule(modname);
+    if (!m) goto end;
+    p = PyObject_GetAttrString(m, "RefNannyAPI");
+    if (!p) goto end;
+    r = PyLong_AsVoidPtr(p);
+end:
+    Py_XDECREF(p);
+    Py_XDECREF(m);
+    return (__Pyx_RefNannyAPIStruct *)r;
+}
+#endif
+
+/* PyObjectGetAttrStr */
+#if CYTHON_USE_TYPE_SLOTS
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
+    PyTypeObject* tp = Py_TYPE(obj);
+    if (likely(tp->tp_getattro))
+        return tp->tp_getattro(obj, attr_name);
+#if PY_MAJOR_VERSION < 3
+    if (likely(tp->tp_getattr))
+        return tp->tp_getattr(obj, PyString_AS_STRING(attr_name));
+#endif
+    return PyObject_GetAttr(obj, attr_name);
+}
+#endif
+
+/* GetBuiltinName */
+static PyObject *__Pyx_GetBuiltinName(PyObject *name) {
+    PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name);
+    if (unlikely(!result)) {
+        PyErr_Format(PyExc_NameError,
+#if PY_MAJOR_VERSION >= 3
+            "name '%U' is not defined", name);
+#else
+            "name '%.200s' is not defined", PyString_AS_STRING(name));
+#endif
+    }
+    return result;
+}
+
+/* MemviewSliceInit */
+static int
+__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
+                        int ndim,
+                        __Pyx_memviewslice *memviewslice,
+                        int memview_is_new_reference)
+{
+    __Pyx_RefNannyDeclarations
+    int i, retval=-1;
+    Py_buffer *buf = &memview->view;
+    __Pyx_RefNannySetupContext("init_memviewslice", 0);
+    if (unlikely(memviewslice->memview || memviewslice->data)) {
+        PyErr_SetString(PyExc_ValueError,
+            "memviewslice is already initialized!");
+        goto fail;
+    }
+    if (buf->strides) {
+        for (i = 0; i < ndim; i++) {
+            memviewslice->strides[i] = buf->strides[i];
+        }
+    } else {
+        Py_ssize_t stride = buf->itemsize;
+        for (i = ndim - 1; i >= 0; i--) {
+            memviewslice->strides[i] = stride;
+            stride *= buf->shape[i];
+        }
+    }
+    for (i = 0; i < ndim; i++) {
+        memviewslice->shape[i]   = buf->shape[i];
+        if (buf->suboffsets) {
+            memviewslice->suboffsets[i] = buf->suboffsets[i];
+        } else {
+            memviewslice->suboffsets[i] = -1;
+        }
+    }
+    memviewslice->memview = memview;
+    memviewslice->data = (char *)buf->buf;
+    if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
+        Py_INCREF(memview);
+    }
+    retval = 0;
+    goto no_fail;
+fail:
+    memviewslice->memview = 0;
+    memviewslice->data = 0;
+    retval = -1;
+no_fail:
+    __Pyx_RefNannyFinishContext();
+    return retval;
+}
+#ifndef Py_NO_RETURN
+#define Py_NO_RETURN
+#endif
+static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN {
+    va_list vargs;
+    char msg[200];
+#if PY_VERSION_HEX >= 0x030A0000 || defined(HAVE_STDARG_PROTOTYPES)
+    va_start(vargs, fmt);
+#else
+    va_start(vargs);
+#endif
+    vsnprintf(msg, 200, fmt, vargs);
+    va_end(vargs);
+    Py_FatalError(msg);
+}
+static CYTHON_INLINE int
+__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+                                   PyThread_type_lock lock)
+{
+    int result;
+    PyThread_acquire_lock(lock, 1);
+    result = (*acquisition_count)++;
+    PyThread_release_lock(lock);
+    return result;
+}
+static CYTHON_INLINE int
+__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
+                                   PyThread_type_lock lock)
+{
+    int result;
+    PyThread_acquire_lock(lock, 1);
+    result = (*acquisition_count)--;
+    PyThread_release_lock(lock);
+    return result;
+}
+static CYTHON_INLINE void
+__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
+{
+    int first_time;
+    struct __pyx_memoryview_obj *memview = memslice->memview;
+    if (unlikely(!memview || (PyObject *) memview == Py_None))
+        return;
+    if (unlikely(__pyx_get_slice_count(memview) < 0))
+        __pyx_fatalerror("Acquisition count is %d (line %d)",
+                         __pyx_get_slice_count(memview), lineno);
+    first_time = __pyx_add_acquisition_count(memview) == 0;
+    if (unlikely(first_time)) {
+        if (have_gil) {
+            Py_INCREF((PyObject *) memview);
+        } else {
+            PyGILState_STATE _gilstate = PyGILState_Ensure();
+            Py_INCREF((PyObject *) memview);
+            PyGILState_Release(_gilstate);
+        }
+    }
+}
+static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
+                                             int have_gil, int lineno) {
+    int last_time;
+    struct __pyx_memoryview_obj *memview = memslice->memview;
+    if (unlikely(!memview || (PyObject *) memview == Py_None)) {
+        memslice->memview = NULL;
+        return;
+    }
+    if (unlikely(__pyx_get_slice_count(memview) <= 0))
+        __pyx_fatalerror("Acquisition count is %d (line %d)",
+                         __pyx_get_slice_count(memview), lineno);
+    last_time = __pyx_sub_acquisition_count(memview) == 1;
+    memslice->data = NULL;
+    if (unlikely(last_time)) {
+        if (have_gil) {
+            Py_CLEAR(memslice->memview);
+        } else {
+            PyGILState_STATE _gilstate = PyGILState_Ensure();
+            Py_CLEAR(memslice->memview);
+            PyGILState_Release(_gilstate);
+        }
+    } else {
+        memslice->memview = NULL;
+    }
+}
+
+/* RaiseArgTupleInvalid */
+static void __Pyx_RaiseArgtupleInvalid(
+    const char* func_name,
+    int exact,
+    Py_ssize_t num_min,
+    Py_ssize_t num_max,
+    Py_ssize_t num_found)
+{
+    Py_ssize_t num_expected;
+    const char *more_or_less;
+    if (num_found < num_min) {
+        num_expected = num_min;
+        more_or_less = "at least";
+    } else {
+        num_expected = num_max;
+        more_or_less = "at most";
+    }
+    if (exact) {
+        more_or_less = "exactly";
+    }
+    PyErr_Format(PyExc_TypeError,
+                 "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
+                 func_name, more_or_less, num_expected,
+                 (num_expected == 1) ? "" : "s", num_found);
+}
+
+/* RaiseDoubleKeywords */
+static void __Pyx_RaiseDoubleKeywordsError(
+    const char* func_name,
+    PyObject* kw_name)
+{
+    PyErr_Format(PyExc_TypeError,
+        #if PY_MAJOR_VERSION >= 3
+        "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
+        #else
+        "%s() got multiple values for keyword argument '%s'", func_name,
+        PyString_AsString(kw_name));
+        #endif
+}
+
+/* ParseKeywords */
+static int __Pyx_ParseOptionalKeywords(
+    PyObject *kwds,
+    PyObject **argnames[],
+    PyObject *kwds2,
+    PyObject *values[],
+    Py_ssize_t num_pos_args,
+    const char* function_name)
+{
+    PyObject *key = 0, *value = 0;
+    Py_ssize_t pos = 0;
+    PyObject*** name;
+    PyObject*** first_kw_arg = argnames + num_pos_args;
+    while (PyDict_Next(kwds, &pos, &key, &value)) {
+        name = first_kw_arg;
+        while (*name && (**name != key)) name++;
+        if (*name) {
+            values[name-argnames] = value;
+            continue;
+        }
+        name = first_kw_arg;
+        #if PY_MAJOR_VERSION < 3
+        if (likely(PyString_Check(key))) {
+            while (*name) {
+                if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
+                        && _PyString_Eq(**name, key)) {
+                    values[name-argnames] = value;
+                    break;
+                }
+                name++;
+            }
+            if (*name) continue;
+            else {
+                PyObject*** argname = argnames;
+                while (argname != first_kw_arg) {
+                    if ((**argname == key) || (
+                            (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
+                             && _PyString_Eq(**argname, key))) {
+                        goto arg_passed_twice;
+                    }
+                    argname++;
+                }
+            }
+        } else
+        #endif
+        if (likely(PyUnicode_Check(key))) {
+            while (*name) {
+                int cmp = (**name == key) ? 0 :
+                #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+                    (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 :
+                #endif
+                    PyUnicode_Compare(**name, key);
+                if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+                if (cmp == 0) {
+                    values[name-argnames] = value;
+                    break;
+                }
+                name++;
+            }
+            if (*name) continue;
+            else {
+                PyObject*** argname = argnames;
+                while (argname != first_kw_arg) {
+                    int cmp = (**argname == key) ? 0 :
+                    #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
+                        (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 :
+                    #endif
+                        PyUnicode_Compare(**argname, key);
+                    if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
+                    if (cmp == 0) goto arg_passed_twice;
+                    argname++;
+                }
+            }
+        } else
+            goto invalid_keyword_type;
+        if (kwds2) {
+            if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
+        } else {
+            goto invalid_keyword;
+        }
+    }
+    return 0;
+arg_passed_twice:
+    __Pyx_RaiseDoubleKeywordsError(function_name, key);
+    goto bad;
+invalid_keyword_type:
+    PyErr_Format(PyExc_TypeError,
+        "%.200s() keywords must be strings", function_name);
+    goto bad;
+invalid_keyword:
+    PyErr_Format(PyExc_TypeError,
+    #if PY_MAJOR_VERSION < 3
+        "%.200s() got an unexpected keyword argument '%.200s'",
+        function_name, PyString_AsString(key));
+    #else
+        "%s() got an unexpected keyword argument '%U'",
+        function_name, key);
+    #endif
+bad:
+    return -1;
+}
+
+/* None */
+static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
+    PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
+}
+
+/* ArgTypeTest */
+static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact)
+{
+    if (unlikely(!type)) {
+        PyErr_SetString(PyExc_SystemError, "Missing type object");
+        return 0;
+    }
+    else if (exact) {
+        #if PY_MAJOR_VERSION == 2
+        if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
+        #endif
+    }
+    else {
+        if (likely(__Pyx_TypeCheck(obj, type))) return 1;
+    }
+    PyErr_Format(PyExc_TypeError,
+        "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
+        name, type->tp_name, Py_TYPE(obj)->tp_name);
+    return 0;
+}
+
+/* PyObjectCall */
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) {
+    PyObject *result;
+    ternaryfunc call = Py_TYPE(func)->tp_call;
+    if (unlikely(!call))
+        return PyObject_Call(func, arg, kw);
+    if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+        return NULL;
+    result = (*call)(func, arg, kw);
+    Py_LeaveRecursiveCall();
+    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+        PyErr_SetString(
+            PyExc_SystemError,
+            "NULL result without error in PyObject_Call");
+    }
+    return result;
+}
+#endif
+
+/* PyErrFetchRestore */
+#if CYTHON_FAST_THREAD_STATE
+static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
+    PyObject *tmp_type, *tmp_value, *tmp_tb;
+    tmp_type = tstate->curexc_type;
+    tmp_value = tstate->curexc_value;
+    tmp_tb = tstate->curexc_traceback;
+    tstate->curexc_type = type;
+    tstate->curexc_value = value;
+    tstate->curexc_traceback = tb;
+    Py_XDECREF(tmp_type);
+    Py_XDECREF(tmp_value);
+    Py_XDECREF(tmp_tb);
+}
+static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
+    *type = tstate->curexc_type;
+    *value = tstate->curexc_value;
+    *tb = tstate->curexc_traceback;
+    tstate->curexc_type = 0;
+    tstate->curexc_value = 0;
+    tstate->curexc_traceback = 0;
+}
+#endif
+
+/* RaiseException */
+#if PY_MAJOR_VERSION < 3
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
+                        CYTHON_UNUSED PyObject *cause) {
+    __Pyx_PyThreadState_declare
+    Py_XINCREF(type);
+    if (!value || value == Py_None)
+        value = NULL;
+    else
+        Py_INCREF(value);
+    if (!tb || tb == Py_None)
+        tb = NULL;
+    else {
+        Py_INCREF(tb);
+        if (!PyTraceBack_Check(tb)) {
+            PyErr_SetString(PyExc_TypeError,
+                "raise: arg 3 must be a traceback or None");
+            goto raise_error;
+        }
+    }
+    if (PyType_Check(type)) {
+#if CYTHON_COMPILING_IN_PYPY
+        if (!value) {
+            Py_INCREF(Py_None);
+            value = Py_None;
+        }
+#endif
+        PyErr_NormalizeException(&type, &value, &tb);
+    } else {
+        if (value) {
+            PyErr_SetString(PyExc_TypeError,
+                "instance exception may not have a separate value");
+            goto raise_error;
+        }
+        value = type;
+        type = (PyObject*) Py_TYPE(type);
+        Py_INCREF(type);
+        if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
+            PyErr_SetString(PyExc_TypeError,
+                "raise: exception class must be a subclass of BaseException");
+            goto raise_error;
+        }
+    }
+    __Pyx_PyThreadState_assign
+    __Pyx_ErrRestore(type, value, tb);
+    return;
+raise_error:
+    Py_XDECREF(value);
+    Py_XDECREF(type);
+    Py_XDECREF(tb);
+    return;
+}
+#else
+static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
+    PyObject* owned_instance = NULL;
+    if (tb == Py_None) {
+        tb = 0;
+    } else if (tb && !PyTraceBack_Check(tb)) {
+        PyErr_SetString(PyExc_TypeError,
+            "raise: arg 3 must be a traceback or None");
+        goto bad;
+    }
+    if (value == Py_None)
+        value = 0;
+    if (PyExceptionInstance_Check(type)) {
+        if (value) {
+            PyErr_SetString(PyExc_TypeError,
+                "instance exception may not have a separate value");
+            goto bad;
+        }
+        value = type;
+        type = (PyObject*) Py_TYPE(value);
+    } else if (PyExceptionClass_Check(type)) {
+        PyObject *instance_class = NULL;
+        if (value && PyExceptionInstance_Check(value)) {
+            instance_class = (PyObject*) Py_TYPE(value);
+            if (instance_class != type) {
+                int is_subclass = PyObject_IsSubclass(instance_class, type);
+                if (!is_subclass) {
+                    instance_class = NULL;
+                } else if (unlikely(is_subclass == -1)) {
+                    goto bad;
+                } else {
+                    type = instance_class;
+                }
+            }
+        }
+        if (!instance_class) {
+            PyObject *args;
+            if (!value)
+                args = PyTuple_New(0);
+            else if (PyTuple_Check(value)) {
+                Py_INCREF(value);
+                args = value;
+            } else
+                args = PyTuple_Pack(1, value);
+            if (!args)
+                goto bad;
+            owned_instance = PyObject_Call(type, args, NULL);
+            Py_DECREF(args);
+            if (!owned_instance)
+                goto bad;
+            value = owned_instance;
+            if (!PyExceptionInstance_Check(value)) {
+                PyErr_Format(PyExc_TypeError,
+                             "calling %R should have returned an instance of "
+                             "BaseException, not %R",
+                             type, Py_TYPE(value));
+                goto bad;
+            }
+        }
+    } else {
+        PyErr_SetString(PyExc_TypeError,
+            "raise: exception class must be a subclass of BaseException");
+        goto bad;
+    }
+    if (cause) {
+        PyObject *fixed_cause;
+        if (cause == Py_None) {
+            fixed_cause = NULL;
+        } else if (PyExceptionClass_Check(cause)) {
+            fixed_cause = PyObject_CallObject(cause, NULL);
+            if (fixed_cause == NULL)
+                goto bad;
+        } else if (PyExceptionInstance_Check(cause)) {
+            fixed_cause = cause;
+            Py_INCREF(fixed_cause);
+        } else {
+            PyErr_SetString(PyExc_TypeError,
+                            "exception causes must derive from "
+                            "BaseException");
+            goto bad;
+        }
+        PyException_SetCause(value, fixed_cause);
+    }
+    PyErr_SetObject(type, value);
+    if (tb) {
+#if CYTHON_FAST_THREAD_STATE
+        PyThreadState *tstate = __Pyx_PyThreadState_Current;
+        PyObject* tmp_tb = tstate->curexc_traceback;
+        if (tb != tmp_tb) {
+            Py_INCREF(tb);
+            tstate->curexc_traceback = tb;
+            Py_XDECREF(tmp_tb);
+        }
+#else
+        PyObject *tmp_type, *tmp_value, *tmp_tb;
+        PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
+        Py_INCREF(tb);
+        PyErr_Restore(tmp_type, tmp_value, tb);
+        Py_XDECREF(tmp_tb);
+#endif
+    }
+bad:
+    Py_XDECREF(owned_instance);
+    return;
+}
+#endif
+
+/* PyCFunctionFastCall */
+#if CYTHON_FAST_PYCCALL
+static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) {
+    PyCFunctionObject *func = (PyCFunctionObject*)func_obj;
+    PyCFunction meth = PyCFunction_GET_FUNCTION(func);
+    PyObject *self = PyCFunction_GET_SELF(func);
+    int flags = PyCFunction_GET_FLAGS(func);
+    assert(PyCFunction_Check(func));
+    assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS)));
+    assert(nargs >= 0);
+    assert(nargs == 0 || args != NULL);
+    /* _PyCFunction_FastCallDict() must not be called with an exception set,
+       because it may clear it (directly or indirectly) and so the
+       caller loses its exception */
+    assert(!PyErr_Occurred());
+    if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) {
+        return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL);
+    } else {
+        return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs);
+    }
+}
+#endif
+
+/* PyFunctionFastCall */
+#if CYTHON_FAST_PYCALL
+static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na,
+                                               PyObject *globals) {
+    PyFrameObject *f;
+    PyThreadState *tstate = __Pyx_PyThreadState_Current;
+    PyObject **fastlocals;
+    Py_ssize_t i;
+    PyObject *result;
+    assert(globals != NULL);
+    /* XXX Perhaps we should create a specialized
+       PyFrame_New() that doesn't take locals, but does
+       take builtins without sanity checking them.
+       */
+    assert(tstate != NULL);
+    f = PyFrame_New(tstate, co, globals, NULL);
+    if (f == NULL) {
+        return NULL;
+    }
+    fastlocals = __Pyx_PyFrame_GetLocalsplus(f);
+    for (i = 0; i < na; i++) {
+        Py_INCREF(*args);
+        fastlocals[i] = *args++;
+    }
+    result = PyEval_EvalFrameEx(f,0);
+    ++tstate->recursion_depth;
+    Py_DECREF(f);
+    --tstate->recursion_depth;
+    return result;
+}
+#if 1 || PY_VERSION_HEX < 0x030600B1
+static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) {
+    PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func);
+    PyObject *globals = PyFunction_GET_GLOBALS(func);
+    PyObject *argdefs = PyFunction_GET_DEFAULTS(func);
+    PyObject *closure;
+#if PY_MAJOR_VERSION >= 3
+    PyObject *kwdefs;
+#endif
+    PyObject *kwtuple, **k;
+    PyObject **d;
+    Py_ssize_t nd;
+    Py_ssize_t nk;
+    PyObject *result;
+    assert(kwargs == NULL || PyDict_Check(kwargs));
+    nk = kwargs ? PyDict_Size(kwargs) : 0;
+    if (Py_EnterRecursiveCall((char*)" while calling a Python object")) {
+        return NULL;
+    }
+    if (
+#if PY_MAJOR_VERSION >= 3
+            co->co_kwonlyargcount == 0 &&
+#endif
+            likely(kwargs == NULL || nk == 0) &&
+            co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) {
+        if (argdefs == NULL && co->co_argcount == nargs) {
+            result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals);
+            goto done;
+        }
+        else if (nargs == 0 && argdefs != NULL
+                 && co->co_argcount == Py_SIZE(argdefs)) {
+            /* function called with no arguments, but all parameters have
+               a default value: use default values as arguments .*/
+            args = &PyTuple_GET_ITEM(argdefs, 0);
+            result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals);
+            goto done;
+        }
+    }
+    if (kwargs != NULL) {
+        Py_ssize_t pos, i;
+        kwtuple = PyTuple_New(2 * nk);
+        if (kwtuple == NULL) {
+            result = NULL;
+            goto done;
+        }
+        k = &PyTuple_GET_ITEM(kwtuple, 0);
+        pos = i = 0;
+        while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) {
+            Py_INCREF(k[i]);
+            Py_INCREF(k[i+1]);
+            i += 2;
+        }
+        nk = i / 2;
+    }
+    else {
+        kwtuple = NULL;
+        k = NULL;
+    }
+    closure = PyFunction_GET_CLOSURE(func);
+#if PY_MAJOR_VERSION >= 3
+    kwdefs = PyFunction_GET_KW_DEFAULTS(func);
+#endif
+    if (argdefs != NULL) {
+        d = &PyTuple_GET_ITEM(argdefs, 0);
+        nd = Py_SIZE(argdefs);
+    }
+    else {
+        d = NULL;
+        nd = 0;
+    }
+#if PY_MAJOR_VERSION >= 3
+    result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL,
+                               args, (int)nargs,
+                               k, (int)nk,
+                               d, (int)nd, kwdefs, closure);
+#else
+    result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL,
+                               args, (int)nargs,
+                               k, (int)nk,
+                               d, (int)nd, closure);
+#endif
+    Py_XDECREF(kwtuple);
+done:
+    Py_LeaveRecursiveCall();
+    return result;
+}
+#endif
+#endif
+
+/* PyObjectCall2Args */
+static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) {
+    PyObject *args, *result = NULL;
+    #if CYTHON_FAST_PYCALL
+    if (PyFunction_Check(function)) {
+        PyObject *args[2] = {arg1, arg2};
+        return __Pyx_PyFunction_FastCall(function, args, 2);
+    }
+    #endif
+    #if CYTHON_FAST_PYCCALL
+    if (__Pyx_PyFastCFunction_Check(function)) {
+        PyObject *args[2] = {arg1, arg2};
+        return __Pyx_PyCFunction_FastCall(function, args, 2);
+    }
+    #endif
+    args = PyTuple_New(2);
+    if (unlikely(!args)) goto done;
+    Py_INCREF(arg1);
+    PyTuple_SET_ITEM(args, 0, arg1);
+    Py_INCREF(arg2);
+    PyTuple_SET_ITEM(args, 1, arg2);
+    Py_INCREF(function);
+    result = __Pyx_PyObject_Call(function, args, NULL);
+    Py_DECREF(args);
+    Py_DECREF(function);
+done:
+    return result;
+}
+
+/* PyObjectCallMethO */
+#if CYTHON_COMPILING_IN_CPYTHON
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
+    PyObject *self, *result;
+    PyCFunction cfunc;
+    cfunc = PyCFunction_GET_FUNCTION(func);
+    self = PyCFunction_GET_SELF(func);
+    if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
+        return NULL;
+    result = cfunc(self, arg);
+    Py_LeaveRecursiveCall();
+    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
+        PyErr_SetString(
+            PyExc_SystemError,
+            "NULL result without error in PyObject_Call");
+    }
+    return result;
+}
+#endif
+
+/* PyObjectCallOneArg */
+#if CYTHON_COMPILING_IN_CPYTHON
+static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+    PyObject *result;
+    PyObject *args = PyTuple_New(1);
+    if (unlikely(!args)) return NULL;
+    Py_INCREF(arg);
+    PyTuple_SET_ITEM(args, 0, arg);
+    result = __Pyx_PyObject_Call(func, args, NULL);
+    Py_DECREF(args);
+    return result;
+}
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+#if CYTHON_FAST_PYCALL
+    if (PyFunction_Check(func)) {
+        return __Pyx_PyFunction_FastCall(func, &arg, 1);
+    }
+#endif
+    if (likely(PyCFunction_Check(func))) {
+        if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
+            return __Pyx_PyObject_CallMethO(func, arg);
+#if CYTHON_FAST_PYCCALL
+        } else if (__Pyx_PyFastCFunction_Check(func)) {
+            return __Pyx_PyCFunction_FastCall(func, &arg, 1);
+#endif
+        }
+    }
+    return __Pyx__PyObject_CallOneArg(func, arg);
+}
+#else
+static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
+    PyObject *result;
+    PyObject *args = PyTuple_Pack(1, arg);
+    if (unlikely(!args)) return NULL;
+    result = __Pyx_PyObject_Call(func, args, NULL);
+    Py_DECREF(args);
+    return result;
+}
+#endif
+
+/* BytesEquals */
+static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+    return PyObject_RichCompareBool(s1, s2, equals);
+#else
+    if (s1 == s2) {
+        return (equals == Py_EQ);
+    } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
+        const char *ps1, *ps2;
+        Py_ssize_t length = PyBytes_GET_SIZE(s1);
+        if (length != PyBytes_GET_SIZE(s2))
+            return (equals == Py_NE);
+        ps1 = PyBytes_AS_STRING(s1);
+        ps2 = PyBytes_AS_STRING(s2);
+        if (ps1[0] != ps2[0]) {
+            return (equals == Py_NE);
+        } else if (length == 1) {
+            return (equals == Py_EQ);
+        } else {
+            int result;
+#if CYTHON_USE_UNICODE_INTERNALS && (PY_VERSION_HEX < 0x030B0000)
+            Py_hash_t hash1, hash2;
+            hash1 = ((PyBytesObject*)s1)->ob_shash;
+            hash2 = ((PyBytesObject*)s2)->ob_shash;
+            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
+                return (equals == Py_NE);
+            }
+#endif
+            result = memcmp(ps1, ps2, (size_t)length);
+            return (equals == Py_EQ) ? (result == 0) : (result != 0);
+        }
+    } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
+        return (equals == Py_NE);
+    } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
+        return (equals == Py_NE);
+    } else {
+        int result;
+        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+        if (!py_result)
+            return -1;
+        result = __Pyx_PyObject_IsTrue(py_result);
+        Py_DECREF(py_result);
+        return result;
+    }
+#endif
+}
+
+/* UnicodeEquals */
+static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
+#if CYTHON_COMPILING_IN_PYPY
+    return PyObject_RichCompareBool(s1, s2, equals);
+#else
+#if PY_MAJOR_VERSION < 3
+    PyObject* owned_ref = NULL;
+#endif
+    int s1_is_unicode, s2_is_unicode;
+    if (s1 == s2) {
+        goto return_eq;
+    }
+    s1_is_unicode = PyUnicode_CheckExact(s1);
+    s2_is_unicode = PyUnicode_CheckExact(s2);
+#if PY_MAJOR_VERSION < 3
+    if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
+        owned_ref = PyUnicode_FromObject(s2);
+        if (unlikely(!owned_ref))
+            return -1;
+        s2 = owned_ref;
+        s2_is_unicode = 1;
+    } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
+        owned_ref = PyUnicode_FromObject(s1);
+        if (unlikely(!owned_ref))
+            return -1;
+        s1 = owned_ref;
+        s1_is_unicode = 1;
+    } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
+        return __Pyx_PyBytes_Equals(s1, s2, equals);
+    }
+#endif
+    if (s1_is_unicode & s2_is_unicode) {
+        Py_ssize_t length;
+        int kind;
+        void *data1, *data2;
+        if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
+            return -1;
+        length = __Pyx_PyUnicode_GET_LENGTH(s1);
+        if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
+            goto return_ne;
+        }
+#if CYTHON_USE_UNICODE_INTERNALS
+        {
+            Py_hash_t hash1, hash2;
+        #if CYTHON_PEP393_ENABLED
+            hash1 = ((PyASCIIObject*)s1)->hash;
+            hash2 = ((PyASCIIObject*)s2)->hash;
+        #else
+            hash1 = ((PyUnicodeObject*)s1)->hash;
+            hash2 = ((PyUnicodeObject*)s2)->hash;
+        #endif
+            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
+                goto return_ne;
+            }
+        }
+#endif
+        kind = __Pyx_PyUnicode_KIND(s1);
+        if (kind != __Pyx_PyUnicode_KIND(s2)) {
+            goto return_ne;
+        }
+        data1 = __Pyx_PyUnicode_DATA(s1);
+        data2 = __Pyx_PyUnicode_DATA(s2);
+        if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
+            goto return_ne;
+        } else if (length == 1) {
+            goto return_eq;
+        } else {
+            int result = memcmp(data1, data2, (size_t)(length * kind));
+            #if PY_MAJOR_VERSION < 3
+            Py_XDECREF(owned_ref);
+            #endif
+            return (equals == Py_EQ) ? (result == 0) : (result != 0);
+        }
+    } else if ((s1 == Py_None) & s2_is_unicode) {
+        goto return_ne;
+    } else if ((s2 == Py_None) & s1_is_unicode) {
+        goto return_ne;
+    } else {
+        int result;
+        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
+        #if PY_MAJOR_VERSION < 3
+        Py_XDECREF(owned_ref);
+        #endif
+        if (!py_result)
+            return -1;
+        result = __Pyx_PyObject_IsTrue(py_result);
+        Py_DECREF(py_result);
+        return result;
+    }
+return_eq:
+    #if PY_MAJOR_VERSION < 3
+    Py_XDECREF(owned_ref);
+    #endif
+    return (equals == Py_EQ);
+return_ne:
+    #if PY_MAJOR_VERSION < 3
+    Py_XDECREF(owned_ref);
+    #endif
+    return (equals == Py_NE);
+#endif
+}
+
+/* DivInt[Py_ssize_t] */
+static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
+    Py_ssize_t q = a / b;
+    Py_ssize_t r = a - q*b;
+    q -= ((r != 0) & ((r ^ b) < 0));
+    return q;
+}
+
+/* GetAttr */
+static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
+#if CYTHON_USE_TYPE_SLOTS
+#if PY_MAJOR_VERSION >= 3
+    if (likely(PyUnicode_Check(n)))
+#else
+    if (likely(PyString_Check(n)))
+#endif
+        return __Pyx_PyObject_GetAttrStr(o, n);
+#endif
+    return PyObject_GetAttr(o, n);
+}
+
+/* GetItemInt */
+static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
+    PyObject *r;
+    if (!j) return NULL;
+    r = PyObject_GetItem(o, j);
+    Py_DECREF(j);
+    return r;
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
+                                                              CYTHON_NCP_UNUSED int wraparound,
+                                                              CYTHON_NCP_UNUSED int boundscheck) {
+#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
+    Py_ssize_t wrapped_i = i;
+    if (wraparound & unlikely(i < 0)) {
+        wrapped_i += PyList_GET_SIZE(o);
+    }
+    if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) {
+        PyObject *r = PyList_GET_ITEM(o, wrapped_i);
+        Py_INCREF(r);
+        return r;
+    }
+    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+    return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
+                                                              CYTHON_NCP_UNUSED int wraparound,
+                                                              CYTHON_NCP_UNUSED int boundscheck) {
+#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
+    Py_ssize_t wrapped_i = i;
+    if (wraparound & unlikely(i < 0)) {
+        wrapped_i += PyTuple_GET_SIZE(o);
+    }
+    if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) {
+        PyObject *r = PyTuple_GET_ITEM(o, wrapped_i);
+        Py_INCREF(r);
+        return r;
+    }
+    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+#else
+    return PySequence_GetItem(o, i);
+#endif
+}
+static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list,
+                                                     CYTHON_NCP_UNUSED int wraparound,
+                                                     CYTHON_NCP_UNUSED int boundscheck) {
+#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
+    if (is_list || PyList_CheckExact(o)) {
+        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
+        if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) {
+            PyObject *r = PyList_GET_ITEM(o, n);
+            Py_INCREF(r);
+            return r;
+        }
+    }
+    else if (PyTuple_CheckExact(o)) {
+        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
+        if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) {
+            PyObject *r = PyTuple_GET_ITEM(o, n);
+            Py_INCREF(r);
+            return r;
+        }
+    } else {
+        PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
+        if (likely(m && m->sq_item)) {
+            if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
+                Py_ssize_t l = m->sq_length(o);
+                if (likely(l >= 0)) {
+                    i += l;
+                } else {
+                    if (!PyErr_ExceptionMatches(PyExc_OverflowError))
+                        return NULL;
+                    PyErr_Clear();
+                }
+            }
+            return m->sq_item(o, i);
+        }
+    }
+#else
+    if (is_list || PySequence_Check(o)) {
+        return PySequence_GetItem(o, i);
+    }
+#endif
+    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
+}
+
+/* ObjectGetItem */
+#if CYTHON_USE_TYPE_SLOTS
+static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) {
+    PyObject *runerr = NULL;
+    Py_ssize_t key_value;
+    PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence;
+    if (unlikely(!(m && m->sq_item))) {
+        PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name);
+        return NULL;
+    }
+    key_value = __Pyx_PyIndex_AsSsize_t(index);
+    if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) {
+        return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1);
+    }
+    if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) {
+        PyErr_Clear();
+        PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name);
+    }
+    return NULL;
+}
+static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) {
+    PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping;
+    if (likely(m && m->mp_subscript)) {
+        return m->mp_subscript(obj, key);
+    }
+    return __Pyx_PyObject_GetIndex(obj, key);
+}
+#endif
+
+/* decode_c_string */
+static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
+         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
+         const char* encoding, const char* errors,
+         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
+    Py_ssize_t length;
+    if (unlikely((start < 0) | (stop < 0))) {
+        size_t slen = strlen(cstring);
+        if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) {
+            PyErr_SetString(PyExc_OverflowError,
+                            "c-string too long to convert to Python");
+            return NULL;
+        }
+        length = (Py_ssize_t) slen;
+        if (start < 0) {
+            start += length;
+            if (start < 0)
+                start = 0;
+        }
+        if (stop < 0)
+            stop += length;
+    }
+    if (unlikely(stop <= start))
+        return __Pyx_NewRef(__pyx_empty_unicode);
+    length = stop - start;
+    cstring += start;
+    if (decode_func) {
+        return decode_func(cstring, length, errors);
+    } else {
+        return PyUnicode_Decode(cstring, length, encoding, errors);
+    }
+}
+
+/* PyErrExceptionMatches */
+#if CYTHON_FAST_THREAD_STATE
+static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) {
+    Py_ssize_t i, n;
+    n = PyTuple_GET_SIZE(tuple);
+#if PY_MAJOR_VERSION >= 3
+    for (i=0; i<n; i++) {
+        if (exc_type == PyTuple_GET_ITEM(tuple, i)) return 1;
+    }
+#endif
+    for (i=0; i<n; i++) {
+        if (__Pyx_PyErr_GivenExceptionMatches(exc_type, PyTuple_GET_ITEM(tuple, i))) return 1;
+    }
+    return 0;
+}
+static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) {
+    PyObject *exc_type = tstate->curexc_type;
+    if (exc_type == err) return 1;
+    if (unlikely(!exc_type)) return 0;
+    if (unlikely(PyTuple_Check(err)))
+        return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err);
+    return __Pyx_PyErr_GivenExceptionMatches(exc_type, err);
+}
+#endif
+
+/* GetAttr3 */
+static PyObject *__Pyx_GetAttr3Default(PyObject *d) {
+    __Pyx_PyThreadState_declare
+    __Pyx_PyThreadState_assign
+    if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
+        return NULL;
+    __Pyx_PyErr_Clear();
+    Py_INCREF(d);
+    return d;
+}
+static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) {
+    PyObject *r = __Pyx_GetAttr(o, n);
+    return (likely(r)) ? r : __Pyx_GetAttr3Default(d);
+}
+
+/* PyDictVersioning */
+#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS
+static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) {
+    PyObject *dict = Py_TYPE(obj)->tp_dict;
+    return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0;
+}
+static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) {
+    PyObject **dictptr = NULL;
+    Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset;
+    if (offset) {
+#if CYTHON_COMPILING_IN_CPYTHON
+        dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj);
+#else
+        dictptr = _PyObject_GetDictPtr(obj);
+#endif
+    }
+    return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0;
+}
+static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) {
+    PyObject *dict = Py_TYPE(obj)->tp_dict;
+    if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict)))
+        return 0;
+    return obj_dict_version == __Pyx_get_object_dict_version(obj);
+}
+#endif
+
+/* GetModuleGlobalName */
+#if CYTHON_USE_DICT_VERSIONS
+static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value)
+#else
+static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name)
+#endif
+{
+    PyObject *result;
+#if !CYTHON_AVOID_BORROWED_REFS
+#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1
+    result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash);
+    __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
+    if (likely(result)) {
+        return __Pyx_NewRef(result);
+    } else if (unlikely(PyErr_Occurred())) {
+        return NULL;
+    }
+#else
+    result = PyDict_GetItem(__pyx_d, name);
+    __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
+    if (likely(result)) {
+        return __Pyx_NewRef(result);
+    }
+#endif
+#else
+    result = PyObject_GetItem(__pyx_d, name);
+    __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version)
+    if (likely(result)) {
+        return __Pyx_NewRef(result);
+    }
+    PyErr_Clear();
+#endif
+    return __Pyx_GetBuiltinName(name);
+}
+
+/* RaiseTooManyValuesToUnpack */
+static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
+    PyErr_Format(PyExc_ValueError,
+                 "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
+}
+
+/* RaiseNeedMoreValuesToUnpack */
+static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
+    PyErr_Format(PyExc_ValueError,
+                 "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
+                 index, (index == 1) ? "" : "s");
+}
+
+/* RaiseNoneIterError */
+static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
+    PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
+}
+
+/* ExtTypeTest */
+static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
+    if (unlikely(!type)) {
+        PyErr_SetString(PyExc_SystemError, "Missing type object");
+        return 0;
+    }
+    if (likely(__Pyx_TypeCheck(obj, type)))
+        return 1;
+    PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
+                 Py_TYPE(obj)->tp_name, type->tp_name);
+    return 0;
+}
+
+/* GetTopmostException */
+#if CYTHON_USE_EXC_INFO_STACK
+static _PyErr_StackItem *
+__Pyx_PyErr_GetTopmostException(PyThreadState *tstate)
+{
+    _PyErr_StackItem *exc_info = tstate->exc_info;
+    while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) &&
+           exc_info->previous_item != NULL)
+    {
+        exc_info = exc_info->previous_item;
+    }
+    return exc_info;
+}
+#endif
+
+/* SaveResetException */
+#if CYTHON_FAST_THREAD_STATE
+static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
+    #if CYTHON_USE_EXC_INFO_STACK
+    _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate);
+    *type = exc_info->exc_type;
+    *value = exc_info->exc_value;
+    *tb = exc_info->exc_traceback;
+    #else
+    *type = tstate->exc_type;
+    *value = tstate->exc_value;
+    *tb = tstate->exc_traceback;
+    #endif
+    Py_XINCREF(*type);
+    Py_XINCREF(*value);
+    Py_XINCREF(*tb);
+}
+static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
+    PyObject *tmp_type, *tmp_value, *tmp_tb;
+    #if CYTHON_USE_EXC_INFO_STACK
+    _PyErr_StackItem *exc_info = tstate->exc_info;
+    tmp_type = exc_info->exc_type;
+    tmp_value = exc_info->exc_value;
+    tmp_tb = exc_info->exc_traceback;
+    exc_info->exc_type = type;
+    exc_info->exc_value = value;
+    exc_info->exc_traceback = tb;
+    #else
+    tmp_type = tstate->exc_type;
+    tmp_value = tstate->exc_value;
+    tmp_tb = tstate->exc_traceback;
+    tstate->exc_type = type;
+    tstate->exc_value = value;
+    tstate->exc_traceback = tb;
+    #endif
+    Py_XDECREF(tmp_type);
+    Py_XDECREF(tmp_value);
+    Py_XDECREF(tmp_tb);
+}
+#endif
+
+/* GetException */
+#if CYTHON_FAST_THREAD_STATE
+static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb)
+#else
+static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb)
+#endif
+{
+    PyObject *local_type, *local_value, *local_tb;
+#if CYTHON_FAST_THREAD_STATE
+    PyObject *tmp_type, *tmp_value, *tmp_tb;
+    local_type = tstate->curexc_type;
+    local_value = tstate->curexc_value;
+    local_tb = tstate->curexc_traceback;
+    tstate->curexc_type = 0;
+    tstate->curexc_value = 0;
+    tstate->curexc_traceback = 0;
+#else
+    PyErr_Fetch(&local_type, &local_value, &local_tb);
+#endif
+    PyErr_NormalizeException(&local_type, &local_value, &local_tb);
+#if CYTHON_FAST_THREAD_STATE
+    if (unlikely(tstate->curexc_type))
+#else
+    if (unlikely(PyErr_Occurred()))
+#endif
+        goto bad;
+    #if PY_MAJOR_VERSION >= 3
+    if (local_tb) {
+        if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
+            goto bad;
+    }
+    #endif
+    Py_XINCREF(local_tb);
+    Py_XINCREF(local_type);
+    Py_XINCREF(local_value);
+    *type = local_type;
+    *value = local_value;
+    *tb = local_tb;
+#if CYTHON_FAST_THREAD_STATE
+    #if CYTHON_USE_EXC_INFO_STACK
+    {
+        _PyErr_StackItem *exc_info = tstate->exc_info;
+        tmp_type = exc_info->exc_type;
+        tmp_value = exc_info->exc_value;
+        tmp_tb = exc_info->exc_traceback;
+        exc_info->exc_type = local_type;
+        exc_info->exc_value = local_value;
+        exc_info->exc_traceback = local_tb;
+    }
+    #else
+    tmp_type = tstate->exc_type;
+    tmp_value = tstate->exc_value;
+    tmp_tb = tstate->exc_traceback;
+    tstate->exc_type = local_type;
+    tstate->exc_value = local_value;
+    tstate->exc_traceback = local_tb;
+    #endif
+    Py_XDECREF(tmp_type);
+    Py_XDECREF(tmp_value);
+    Py_XDECREF(tmp_tb);
+#else
+    PyErr_SetExcInfo(local_type, local_value, local_tb);
+#endif
+    return 0;
+bad:
+    *type = 0;
+    *value = 0;
+    *tb = 0;
+    Py_XDECREF(local_type);
+    Py_XDECREF(local_value);
+    Py_XDECREF(local_tb);
+    return -1;
+}
+
+/* SwapException */
+#if CYTHON_FAST_THREAD_STATE
+static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
+    PyObject *tmp_type, *tmp_value, *tmp_tb;
+    #if CYTHON_USE_EXC_INFO_STACK
+    _PyErr_StackItem *exc_info = tstate->exc_info;
+    tmp_type = exc_info->exc_type;
+    tmp_value = exc_info->exc_value;
+    tmp_tb = exc_info->exc_traceback;
+    exc_info->exc_type = *type;
+    exc_info->exc_value = *value;
+    exc_info->exc_traceback = *tb;
+    #else
+    tmp_type = tstate->exc_type;
+    tmp_value = tstate->exc_value;
+    tmp_tb = tstate->exc_traceback;
+    tstate->exc_type = *type;
+    tstate->exc_value = *value;
+    tstate->exc_traceback = *tb;
+    #endif
+    *type = tmp_type;
+    *value = tmp_value;
+    *tb = tmp_tb;
+}
+#else
+static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
+    PyObject *tmp_type, *tmp_value, *tmp_tb;
+    PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
+    PyErr_SetExcInfo(*type, *value, *tb);
+    *type = tmp_type;
+    *value = tmp_value;
+    *tb = tmp_tb;
+}
+#endif
+
+/* Import */
+static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
+    PyObject *empty_list = 0;
+    PyObject *module = 0;
+    PyObject *global_dict = 0;
+    PyObject *empty_dict = 0;
+    PyObject *list;
+    #if PY_MAJOR_VERSION < 3
+    PyObject *py_import;
+    py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
+    if (!py_import)
+        goto bad;
+    #endif
+    if (from_list)
+        list = from_list;
+    else {
+        empty_list = PyList_New(0);
+        if (!empty_list)
+            goto bad;
+        list = empty_list;
+    }
+    global_dict = PyModule_GetDict(__pyx_m);
+    if (!global_dict)
+        goto bad;
+    empty_dict = PyDict_New();
+    if (!empty_dict)
+        goto bad;
+    {
+        #if PY_MAJOR_VERSION >= 3
+        if (level == -1) {
+            if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) {
+                module = PyImport_ImportModuleLevelObject(
+                    name, global_dict, empty_dict, list, 1);
+                if (!module) {
+                    if (!PyErr_ExceptionMatches(PyExc_ImportError))
+                        goto bad;
+                    PyErr_Clear();
+                }
+            }
+            level = 0;
+        }
+        #endif
+        if (!module) {
+            #if PY_MAJOR_VERSION < 3
+            PyObject *py_level = PyInt_FromLong(level);
+            if (!py_level)
+                goto bad;
+            module = PyObject_CallFunctionObjArgs(py_import,
+                name, global_dict, empty_dict, list, py_level, (PyObject *)NULL);
+            Py_DECREF(py_level);
+            #else
+            module = PyImport_ImportModuleLevelObject(
+                name, global_dict, empty_dict, list, level);
+            #endif
+        }
+    }
+bad:
+    #if PY_MAJOR_VERSION < 3
+    Py_XDECREF(py_import);
+    #endif
+    Py_XDECREF(empty_list);
+    Py_XDECREF(empty_dict);
+    return module;
+}
+
+/* FastTypeChecks */
+#if CYTHON_COMPILING_IN_CPYTHON
+static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) {
+    while (a) {
+        a = a->tp_base;
+        if (a == b)
+            return 1;
+    }
+    return b == &PyBaseObject_Type;
+}
+static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) {
+    PyObject *mro;
+    if (a == b) return 1;
+    mro = a->tp_mro;
+    if (likely(mro)) {
+        Py_ssize_t i, n;
+        n = PyTuple_GET_SIZE(mro);
+        for (i = 0; i < n; i++) {
+            if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b)
+                return 1;
+        }
+        return 0;
+    }
+    return __Pyx_InBases(a, b);
+}
+#if PY_MAJOR_VERSION == 2
+static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) {
+    PyObject *exception, *value, *tb;
+    int res;
+    __Pyx_PyThreadState_declare
+    __Pyx_PyThreadState_assign
+    __Pyx_ErrFetch(&exception, &value, &tb);
+    res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0;
+    if (unlikely(res == -1)) {
+        PyErr_WriteUnraisable(err);
+        res = 0;
+    }
+    if (!res) {
+        res = PyObject_IsSubclass(err, exc_type2);
+        if (unlikely(res == -1)) {
+            PyErr_WriteUnraisable(err);
+            res = 0;
+        }
+    }
+    __Pyx_ErrRestore(exception, value, tb);
+    return res;
+}
+#else
+static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) {
+    int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0;
+    if (!res) {
+        res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2);
+    }
+    return res;
+}
+#endif
+static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) {
+    Py_ssize_t i, n;
+    assert(PyExceptionClass_Check(exc_type));
+    n = PyTuple_GET_SIZE(tuple);
+#if PY_MAJOR_VERSION >= 3
+    for (i=0; i<n; i++) {
+        if (exc_type == PyTuple_GET_ITEM(tuple, i)) return 1;
+    }
+#endif
+    for (i=0; i<n; i++) {
+        PyObject *t = PyTuple_GET_ITEM(tuple, i);
+        #if PY_MAJOR_VERSION < 3
+        if (likely(exc_type == t)) return 1;
+        #endif
+        if (likely(PyExceptionClass_Check(t))) {
+            if (__Pyx_inner_PyErr_GivenExceptionMatches2(exc_type, NULL, t)) return 1;
+        } else {
+        }
+    }
+    return 0;
+}
+static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject* exc_type) {
+    if (likely(err == exc_type)) return 1;
+    if (likely(PyExceptionClass_Check(err))) {
+        if (likely(PyExceptionClass_Check(exc_type))) {
+            return __Pyx_inner_PyErr_GivenExceptionMatches2(err, NULL, exc_type);
+        } else if (likely(PyTuple_Check(exc_type))) {
+            return __Pyx_PyErr_GivenExceptionMatchesTuple(err, exc_type);
+        } else {
+        }
+    }
+    return PyErr_GivenExceptionMatches(err, exc_type);
+}
+static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *exc_type1, PyObject *exc_type2) {
+    assert(PyExceptionClass_Check(exc_type1));
+    assert(PyExceptionClass_Check(exc_type2));
+    if (likely(err == exc_type1 || err == exc_type2)) return 1;
+    if (likely(PyExceptionClass_Check(err))) {
+        return __Pyx_inner_PyErr_GivenExceptionMatches2(err, exc_type1, exc_type2);
+    }
+    return (PyErr_GivenExceptionMatches(err, exc_type1) || PyErr_GivenExceptionMatches(err, exc_type2));
+}
+#endif
+
+/* PyIntBinop */
+#if !CYTHON_COMPILING_IN_PYPY
+static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) {
+    (void)inplace;
+    (void)zerodivision_check;
+    #if PY_MAJOR_VERSION < 3
+    if (likely(PyInt_CheckExact(op1))) {
+        const long b = intval;
+        long x;
+        long a = PyInt_AS_LONG(op1);
+            x = (long)((unsigned long)a + b);
+            if (likely((x^a) >= 0 || (x^b) >= 0))
+                return PyInt_FromLong(x);
+            return PyLong_Type.tp_as_number->nb_add(op1, op2);
+    }
+    #endif
+    #if CYTHON_USE_PYLONG_INTERNALS
+    if (likely(PyLong_CheckExact(op1))) {
+        const long b = intval;
+        long a, x;
+#ifdef HAVE_LONG_LONG
+        const PY_LONG_LONG llb = intval;
+        PY_LONG_LONG lla, llx;
+#endif
+        const digit* digits = ((PyLongObject*)op1)->ob_digit;
+        const Py_ssize_t size = Py_SIZE(op1);
+        if (likely(__Pyx_sst_abs(size) <= 1)) {
+            a = likely(size) ? digits[0] : 0;
+            if (size == -1) a = -a;
+        } else {
+            switch (size) {
+                case -2:
+                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
+                        a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
+                        lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                case 2:
+                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
+                        a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
+                        lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                case -3:
+                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
+                        a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
+                        lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                case 3:
+                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
+                        a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
+                        lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                case -4:
+                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
+                        a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
+                        lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                case 4:
+                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
+                        a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
+                        break;
+#ifdef HAVE_LONG_LONG
+                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
+                        lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
+                        goto long_long;
+#endif
+                    }
+                    CYTHON_FALLTHROUGH;
+                default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
+            }
+        }
+                x = a + b;
+            return PyLong_FromLong(x);
+#ifdef HAVE_LONG_LONG
+        long_long:
+                llx = lla + llb;
+            return PyLong_FromLongLong(llx);
+#endif
+        
+        
+    }
+    #endif
+    if (PyFloat_CheckExact(op1)) {
+        const long b = intval;
+        double a = PyFloat_AS_DOUBLE(op1);
+            double result;
+            PyFPE_START_PROTECT("add", return NULL)
+            result = ((double)a) + (double)b;
+            PyFPE_END_PROTECT(result)
+            return PyFloat_FromDouble(result);
+    }
+    return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
+}
+#endif
+
+/* DivInt[long] */
+static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
+    long q = a / b;
+    long r = a - q*b;
+    q -= ((r != 0) & ((r ^ b) < 0));
+    return q;
+}
+
+/* ImportFrom */
+static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
+    PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
+    if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
+        PyErr_Format(PyExc_ImportError,
+        #if PY_MAJOR_VERSION < 3
+            "cannot import name %.230s", PyString_AS_STRING(name));
+        #else
+            "cannot import name %S", name);
+        #endif
+    }
+    return value;
+}
+
+/* HasAttr */
+static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) {
+    PyObject *r;
+    if (unlikely(!__Pyx_PyBaseString_Check(n))) {
+        PyErr_SetString(PyExc_TypeError,
+                        "hasattr(): attribute name must be string");
+        return -1;
+    }
+    r = __Pyx_GetAttr(o, n);
+    if (unlikely(!r)) {
+        PyErr_Clear();
+        return 0;
+    } else {
+        Py_DECREF(r);
+        return 1;
+    }
+}
+
+/* PyObject_GenericGetAttrNoDict */
+#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
+static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) {
+    PyErr_Format(PyExc_AttributeError,
+#if PY_MAJOR_VERSION >= 3
+                 "'%.50s' object has no attribute '%U'",
+                 tp->tp_name, attr_name);
+#else
+                 "'%.50s' object has no attribute '%.400s'",
+                 tp->tp_name, PyString_AS_STRING(attr_name));
+#endif
+    return NULL;
+}
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) {
+    PyObject *descr;
+    PyTypeObject *tp = Py_TYPE(obj);
+    if (unlikely(!PyString_Check(attr_name))) {
+        return PyObject_GenericGetAttr(obj, attr_name);
+    }
+    assert(!tp->tp_dictoffset);
+    descr = _PyType_Lookup(tp, attr_name);
+    if (unlikely(!descr)) {
+        return __Pyx_RaiseGenericGetAttributeError(tp, attr_name);
+    }
+    Py_INCREF(descr);
+    #if PY_MAJOR_VERSION < 3
+    if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS)))
+    #endif
+    {
+        descrgetfunc f = Py_TYPE(descr)->tp_descr_get;
+        if (unlikely(f)) {
+            PyObject *res = f(descr, obj, (PyObject *)tp);
+            Py_DECREF(descr);
+            return res;
+        }
+    }
+    return descr;
+}
+#endif
+
+/* PyObject_GenericGetAttr */
+#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
+static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) {
+    if (unlikely(Py_TYPE(obj)->tp_dictoffset)) {
+        return PyObject_GenericGetAttr(obj, attr_name);
+    }
+    return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name);
+}
+#endif
+
+/* SetVTable */
+static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
+#if PY_VERSION_HEX >= 0x02070000
+    PyObject *ob = PyCapsule_New(vtable, 0, 0);
+#else
+    PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
+#endif
+    if (!ob)
+        goto bad;
+    if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
+        goto bad;
+    Py_DECREF(ob);
+    return 0;
+bad:
+    Py_XDECREF(ob);
+    return -1;
+}
+
+/* PyObjectGetAttrStrNoError */
+static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) {
+    __Pyx_PyThreadState_declare
+    __Pyx_PyThreadState_assign
+    if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
+        __Pyx_PyErr_Clear();
+}
+static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) {
+    PyObject *result;
+#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1
+    PyTypeObject* tp = Py_TYPE(obj);
+    if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) {
+        return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1);
+    }
+#endif
+    result = __Pyx_PyObject_GetAttrStr(obj, attr_name);
+    if (unlikely(!result)) {
+        __Pyx_PyObject_GetAttrStr_ClearAttributeError();
+    }
+    return result;
+}
+
+/* SetupReduce */
+static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) {
+  int ret;
+  PyObject *name_attr;
+  name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2);
+  if (likely(name_attr)) {
+      ret = PyObject_RichCompareBool(name_attr, name, Py_EQ);
+  } else {
+      ret = -1;
+  }
+  if (unlikely(ret < 0)) {
+      PyErr_Clear();
+      ret = 0;
+  }
+  Py_XDECREF(name_attr);
+  return ret;
+}
+static int __Pyx_setup_reduce(PyObject* type_obj) {
+    int ret = 0;
+    PyObject *object_reduce = NULL;
+    PyObject *object_getstate = NULL;
+    PyObject *object_reduce_ex = NULL;
+    PyObject *reduce = NULL;
+    PyObject *reduce_ex = NULL;
+    PyObject *reduce_cython = NULL;
+    PyObject *setstate = NULL;
+    PyObject *setstate_cython = NULL;
+    PyObject *getstate = NULL;
+#if CYTHON_USE_PYTYPE_LOOKUP
+    getstate = _PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate);
+#else
+    getstate = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_getstate);
+    if (!getstate && PyErr_Occurred()) {
+        goto __PYX_BAD;
+    }
+#endif
+    if (getstate) {
+#if CYTHON_USE_PYTYPE_LOOKUP
+        object_getstate = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_getstate);
+#else
+        object_getstate = __Pyx_PyObject_GetAttrStrNoError((PyObject*)&PyBaseObject_Type, __pyx_n_s_getstate);
+        if (!object_getstate && PyErr_Occurred()) {
+            goto __PYX_BAD;
+        }
+#endif
+        if (object_getstate != getstate) {
+            goto __PYX_GOOD;
+        }
+    }
+#if CYTHON_USE_PYTYPE_LOOKUP
+    object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
+#else
+    object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
+#endif
+    reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD;
+    if (reduce_ex == object_reduce_ex) {
+#if CYTHON_USE_PYTYPE_LOOKUP
+        object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
+#else
+        object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
+#endif
+        reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD;
+        if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) {
+            reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython);
+            if (likely(reduce_cython)) {
+                ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
+                ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
+            } else if (reduce == object_reduce || PyErr_Occurred()) {
+                goto __PYX_BAD;
+            }
+            setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate);
+            if (!setstate) PyErr_Clear();
+            if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) {
+                setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython);
+                if (likely(setstate_cython)) {
+                    ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
+                    ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
+                } else if (!setstate || PyErr_Occurred()) {
+                    goto __PYX_BAD;
+                }
+            }
+            PyType_Modified((PyTypeObject*)type_obj);
+        }
+    }
+    goto __PYX_GOOD;
+__PYX_BAD:
+    if (!PyErr_Occurred())
+        PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name);
+    ret = -1;
+__PYX_GOOD:
+#if !CYTHON_USE_PYTYPE_LOOKUP
+    Py_XDECREF(object_reduce);
+    Py_XDECREF(object_reduce_ex);
+    Py_XDECREF(object_getstate);
+    Py_XDECREF(getstate);
+#endif
+    Py_XDECREF(reduce);
+    Py_XDECREF(reduce_ex);
+    Py_XDECREF(reduce_cython);
+    Py_XDECREF(setstate);
+    Py_XDECREF(setstate_cython);
+    return ret;
+}
+
+/* CLineInTraceback */
+#ifndef CYTHON_CLINE_IN_TRACEBACK
+static int __Pyx_CLineForTraceback(CYTHON_UNUSED PyThreadState *tstate, int c_line) {
+    PyObject *use_cline;
+    PyObject *ptype, *pvalue, *ptraceback;
+#if CYTHON_COMPILING_IN_CPYTHON
+    PyObject **cython_runtime_dict;
+#endif
+    if (unlikely(!__pyx_cython_runtime)) {
+        return c_line;
+    }
+    __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback);
+#if CYTHON_COMPILING_IN_CPYTHON
+    cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime);
+    if (likely(cython_runtime_dict)) {
+        __PYX_PY_DICT_LOOKUP_IF_MODIFIED(
+            use_cline, *cython_runtime_dict,
+            __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback))
+    } else
+#endif
+    {
+      PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback);
+      if (use_cline_obj) {
+        use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True;
+        Py_DECREF(use_cline_obj);
+      } else {
+        PyErr_Clear();
+        use_cline = NULL;
+      }
+    }
+    if (!use_cline) {
+        c_line = 0;
+        (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False);
+    }
+    else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) {
+        c_line = 0;
+    }
+    __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback);
+    return c_line;
+}
+#endif
+
+/* CodeObjectCache */
+static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
+    int start = 0, mid = 0, end = count - 1;
+    if (end >= 0 && code_line > entries[end].code_line) {
+        return count;
+    }
+    while (start < end) {
+        mid = start + (end - start) / 2;
+        if (code_line < entries[mid].code_line) {
+            end = mid;
+        } else if (code_line > entries[mid].code_line) {
+             start = mid + 1;
+        } else {
+            return mid;
+        }
+    }
+    if (code_line <= entries[mid].code_line) {
+        return mid;
+    } else {
+        return mid + 1;
+    }
+}
+static PyCodeObject *__pyx_find_code_object(int code_line) {
+    PyCodeObject* code_object;
+    int pos;
+    if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
+        return NULL;
+    }
+    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+    if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
+        return NULL;
+    }
+    code_object = __pyx_code_cache.entries[pos].code_object;
+    Py_INCREF(code_object);
+    return code_object;
+}
+static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
+    int pos, i;
+    __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
+    if (unlikely(!code_line)) {
+        return;
+    }
+    if (unlikely(!entries)) {
+        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
+        if (likely(entries)) {
+            __pyx_code_cache.entries = entries;
+            __pyx_code_cache.max_count = 64;
+            __pyx_code_cache.count = 1;
+            entries[0].code_line = code_line;
+            entries[0].code_object = code_object;
+            Py_INCREF(code_object);
+        }
+        return;
+    }
+    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
+    if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
+        PyCodeObject* tmp = entries[pos].code_object;
+        entries[pos].code_object = code_object;
+        Py_DECREF(tmp);
+        return;
+    }
+    if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
+        int new_max = __pyx_code_cache.max_count + 64;
+        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
+            __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry));
+        if (unlikely(!entries)) {
+            return;
+        }
+        __pyx_code_cache.entries = entries;
+        __pyx_code_cache.max_count = new_max;
+    }
+    for (i=__pyx_code_cache.count; i>pos; i--) {
+        entries[i] = entries[i-1];
+    }
+    entries[pos].code_line = code_line;
+    entries[pos].code_object = code_object;
+    __pyx_code_cache.count++;
+    Py_INCREF(code_object);
+}
+
+/* AddTraceback */
+#include "compile.h"
+#include "frameobject.h"
+#include "traceback.h"
+#if PY_VERSION_HEX >= 0x030b00a6
+  #ifndef Py_BUILD_CORE
+    #define Py_BUILD_CORE 1
+  #endif
+  #include "internal/pycore_frame.h"
+#endif
+static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
+            const char *funcname, int c_line,
+            int py_line, const char *filename) {
+    PyCodeObject *py_code = NULL;
+    PyObject *py_funcname = NULL;
+    #if PY_MAJOR_VERSION < 3
+    PyObject *py_srcfile = NULL;
+    py_srcfile = PyString_FromString(filename);
+    if (!py_srcfile) goto bad;
+    #endif
+    if (c_line) {
+        #if PY_MAJOR_VERSION < 3
+        py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+        if (!py_funcname) goto bad;
+        #else
+        py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
+        if (!py_funcname) goto bad;
+        funcname = PyUnicode_AsUTF8(py_funcname);
+        if (!funcname) goto bad;
+        #endif
+    }
+    else {
+        #if PY_MAJOR_VERSION < 3
+        py_funcname = PyString_FromString(funcname);
+        if (!py_funcname) goto bad;
+        #endif
+    }
+    #if PY_MAJOR_VERSION < 3
+    py_code = __Pyx_PyCode_New(
+        0,
+        0,
+        0,
+        0,
+        0,
+        __pyx_empty_bytes, /*PyObject *code,*/
+        __pyx_empty_tuple, /*PyObject *consts,*/
+        __pyx_empty_tuple, /*PyObject *names,*/
+        __pyx_empty_tuple, /*PyObject *varnames,*/
+        __pyx_empty_tuple, /*PyObject *freevars,*/
+        __pyx_empty_tuple, /*PyObject *cellvars,*/
+        py_srcfile,   /*PyObject *filename,*/
+        py_funcname,  /*PyObject *name,*/
+        py_line,
+        __pyx_empty_bytes  /*PyObject *lnotab*/
+    );
+    Py_DECREF(py_srcfile);
+    #else
+    py_code = PyCode_NewEmpty(filename, funcname, py_line);
+    #endif
+    Py_XDECREF(py_funcname);  // XDECREF since it's only set on Py3 if cline
+    return py_code;
+bad:
+    Py_XDECREF(py_funcname);
+    #if PY_MAJOR_VERSION < 3
+    Py_XDECREF(py_srcfile);
+    #endif
+    return NULL;
+}
+static void __Pyx_AddTraceback(const char *funcname, int c_line,
+                               int py_line, const char *filename) {
+    PyCodeObject *py_code = 0;
+    PyFrameObject *py_frame = 0;
+    PyThreadState *tstate = __Pyx_PyThreadState_Current;
+    PyObject *ptype, *pvalue, *ptraceback;
+    if (c_line) {
+        c_line = __Pyx_CLineForTraceback(tstate, c_line);
+    }
+    py_code = __pyx_find_code_object(c_line ? -c_line : py_line);
+    if (!py_code) {
+        __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback);
+        py_code = __Pyx_CreateCodeObjectForTraceback(
+            funcname, c_line, py_line, filename);
+        if (!py_code) {
+            /* If the code object creation fails, then we should clear the
+               fetched exception references and propagate the new exception */
+            Py_XDECREF(ptype);
+            Py_XDECREF(pvalue);
+            Py_XDECREF(ptraceback);
+            goto bad;
+        }
+        __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback);
+        __pyx_insert_code_object(c_line ? -c_line : py_line, py_code);
+    }
+    py_frame = PyFrame_New(
+        tstate,            /*PyThreadState *tstate,*/
+        py_code,           /*PyCodeObject *code,*/
+        __pyx_d,    /*PyObject *globals,*/
+        0                  /*PyObject *locals*/
+    );
+    if (!py_frame) goto bad;
+    __Pyx_PyFrame_SetLineNumber(py_frame, py_line);
+    PyTraceBack_Here(py_frame);
+bad:
+    Py_XDECREF(py_code);
+    Py_XDECREF(py_frame);
+}
+
+#if PY_MAJOR_VERSION < 3
+static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
+    if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
+        if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
+        if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
+    PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
+    return -1;
+}
+static void __Pyx_ReleaseBuffer(Py_buffer *view) {
+    PyObject *obj = view->obj;
+    if (!obj) return;
+    if (PyObject_CheckBuffer(obj)) {
+        PyBuffer_Release(view);
+        return;
+    }
+    if ((0)) {}
+    view->obj = NULL;
+    Py_DECREF(obj);
+}
+#endif
+
+
+/* MemviewSliceIsContig */
+static int
+__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim)
+{
+    int i, index, step, start;
+    Py_ssize_t itemsize = mvs.memview->view.itemsize;
+    if (order == 'F') {
+        step = 1;
+        start = 0;
+    } else {
+        step = -1;
+        start = ndim - 1;
+    }
+    for (i = 0; i < ndim; i++) {
+        index = start + step * i;
+        if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize)
+            return 0;
+        itemsize *= mvs.shape[index];
+    }
+    return 1;
+}
+
+/* OverlappingSlices */
+static void
+__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
+                               void **out_start, void **out_end,
+                               int ndim, size_t itemsize)
+{
+    char *start, *end;
+    int i;
+    start = end = slice->data;
+    for (i = 0; i < ndim; i++) {
+        Py_ssize_t stride = slice->strides[i];
+        Py_ssize_t extent = slice->shape[i];
+        if (extent == 0) {
+            *out_start = *out_end = start;
+            return;
+        } else {
+            if (stride > 0)
+                end += stride * (extent - 1);
+            else
+                start += stride * (extent - 1);
+        }
+    }
+    *out_start = start;
+    *out_end = end + itemsize;
+}
+static int
+__pyx_slices_overlap(__Pyx_memviewslice *slice1,
+                     __Pyx_memviewslice *slice2,
+                     int ndim, size_t itemsize)
+{
+    void *start1, *end1, *start2, *end2;
+    __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
+    __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
+    return (start1 < end2) && (start2 < end1);
+}
+
+/* Capsule */
+static CYTHON_INLINE PyObject *
+__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
+{
+    PyObject *cobj;
+#if PY_VERSION_HEX >= 0x02070000
+    cobj = PyCapsule_New(p, sig, NULL);
+#else
+    cobj = PyCObject_FromVoidPtr(p, NULL);
+#endif
+    return cobj;
+}
+
+/* IsLittleEndian */
+static CYTHON_INLINE int __Pyx_Is_Little_Endian(void)
+{
+  union {
+    uint32_t u32;
+    uint8_t u8[4];
+  } S;
+  S.u32 = 0x01020304;
+  return S.u8[0] == 4;
+}
+
+/* BufferFormatCheck */
+static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
+                              __Pyx_BufFmt_StackElem* stack,
+                              __Pyx_TypeInfo* type) {
+  stack[0].field = &ctx->root;
+  stack[0].parent_offset = 0;
+  ctx->root.type = type;
+  ctx->root.name = "buffer dtype";
+  ctx->root.offset = 0;
+  ctx->head = stack;
+  ctx->head->field = &ctx->root;
+  ctx->fmt_offset = 0;
+  ctx->head->parent_offset = 0;
+  ctx->new_packmode = '@';
+  ctx->enc_packmode = '@';
+  ctx->new_count = 1;
+  ctx->enc_count = 0;
+  ctx->enc_type = 0;
+  ctx->is_complex = 0;
+  ctx->is_valid_array = 0;
+  ctx->struct_alignment = 0;
+  while (type->typegroup == 'S') {
+    ++ctx->head;
+    ctx->head->field = type->fields;
+    ctx->head->parent_offset = 0;
+    type = type->fields->type;
+  }
+}
+static int __Pyx_BufFmt_ParseNumber(const char** ts) {
+    int count;
+    const char* t = *ts;
+    if (*t < '0' || *t > '9') {
+      return -1;
+    } else {
+        count = *t++ - '0';
+        while (*t >= '0' && *t <= '9') {
+            count *= 10;
+            count += *t++ - '0';
+        }
+    }
+    *ts = t;
+    return count;
+}
+static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
+    int number = __Pyx_BufFmt_ParseNumber(ts);
+    if (number == -1)
+        PyErr_Format(PyExc_ValueError,\
+                     "Does not understand character buffer dtype format string ('%c')", **ts);
+    return number;
+}
+static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
+  PyErr_Format(PyExc_ValueError,
+               "Unexpected format string character: '%c'", ch);
+}
+static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
+  switch (ch) {
+    case '?': return "'bool'";
+    case 'c': return "'char'";
+    case 'b': return "'signed char'";
+    case 'B': return "'unsigned char'";
+    case 'h': return "'short'";
+    case 'H': return "'unsigned short'";
+    case 'i': return "'int'";
+    case 'I': return "'unsigned int'";
+    case 'l': return "'long'";
+    case 'L': return "'unsigned long'";
+    case 'q': return "'long long'";
+    case 'Q': return "'unsigned long long'";
+    case 'f': return (is_complex ? "'complex float'" : "'float'");
+    case 'd': return (is_complex ? "'complex double'" : "'double'");
+    case 'g': return (is_complex ? "'complex long double'" : "'long double'");
+    case 'T': return "a struct";
+    case 'O': return "Python object";
+    case 'P': return "a pointer";
+    case 's': case 'p': return "a string";
+    case 0: return "end";
+    default: return "unparseable format string";
+  }
+}
+static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
+  switch (ch) {
+    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+    case 'h': case 'H': return 2;
+    case 'i': case 'I': case 'l': case 'L': return 4;
+    case 'q': case 'Q': return 8;
+    case 'f': return (is_complex ? 8 : 4);
+    case 'd': return (is_complex ? 16 : 8);
+    case 'g': {
+      PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
+      return 0;
+    }
+    case 'O': case 'P': return sizeof(void*);
+    default:
+      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+      return 0;
+    }
+}
+static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
+  switch (ch) {
+    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+    case 'h': case 'H': return sizeof(short);
+    case 'i': case 'I': return sizeof(int);
+    case 'l': case 'L': return sizeof(long);
+    #ifdef HAVE_LONG_LONG
+    case 'q': case 'Q': return sizeof(PY_LONG_LONG);
+    #endif
+    case 'f': return sizeof(float) * (is_complex ? 2 : 1);
+    case 'd': return sizeof(double) * (is_complex ? 2 : 1);
+    case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
+    case 'O': case 'P': return sizeof(void*);
+    default: {
+      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+      return 0;
+    }
+  }
+}
+typedef struct { char c; short x; } __Pyx_st_short;
+typedef struct { char c; int x; } __Pyx_st_int;
+typedef struct { char c; long x; } __Pyx_st_long;
+typedef struct { char c; float x; } __Pyx_st_float;
+typedef struct { char c; double x; } __Pyx_st_double;
+typedef struct { char c; long double x; } __Pyx_st_longdouble;
+typedef struct { char c; void *x; } __Pyx_st_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
+  switch (ch) {
+    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+    case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
+    case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
+    case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+    case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
+#endif
+    case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
+    case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
+    case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
+    case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
+    default:
+      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+      return 0;
+    }
+}
+/* These are for computing the padding at the end of the struct to align
+   on the first member of the struct. This will probably the same as above,
+   but we don't have any guarantees.
+ */
+typedef struct { short x; char c; } __Pyx_pad_short;
+typedef struct { int x; char c; } __Pyx_pad_int;
+typedef struct { long x; char c; } __Pyx_pad_long;
+typedef struct { float x; char c; } __Pyx_pad_float;
+typedef struct { double x; char c; } __Pyx_pad_double;
+typedef struct { long double x; char c; } __Pyx_pad_longdouble;
+typedef struct { void *x; char c; } __Pyx_pad_void_p;
+#ifdef HAVE_LONG_LONG
+typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
+#endif
+static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
+  switch (ch) {
+    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
+    case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
+    case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
+    case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
+#ifdef HAVE_LONG_LONG
+    case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
+#endif
+    case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
+    case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
+    case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
+    case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
+    default:
+      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+      return 0;
+    }
+}
+static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
+  switch (ch) {
+    case 'c':
+        return 'H';
+    case 'b': case 'h': case 'i':
+    case 'l': case 'q': case 's': case 'p':
+        return 'I';
+    case '?': case 'B': case 'H': case 'I': case 'L': case 'Q':
+        return 'U';
+    case 'f': case 'd': case 'g':
+        return (is_complex ? 'C' : 'R');
+    case 'O':
+        return 'O';
+    case 'P':
+        return 'P';
+    default: {
+      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
+      return 0;
+    }
+  }
+}
+static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
+  if (ctx->head == NULL || ctx->head->field == &ctx->root) {
+    const char* expected;
+    const char* quote;
+    if (ctx->head == NULL) {
+      expected = "end";
+      quote = "";
+    } else {
+      expected = ctx->head->field->type->name;
+      quote = "'";
+    }
+    PyErr_Format(PyExc_ValueError,
+                 "Buffer dtype mismatch, expected %s%s%s but got %s",
+                 quote, expected, quote,
+                 __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
+  } else {
+    __Pyx_StructField* field = ctx->head->field;
+    __Pyx_StructField* parent = (ctx->head - 1)->field;
+    PyErr_Format(PyExc_ValueError,
+                 "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
+                 field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
+                 parent->type->name, field->name);
+  }
+}
+static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
+  char group;
+  size_t size, offset, arraysize = 1;
+  if (ctx->enc_type == 0) return 0;
+  if (ctx->head->field->type->arraysize[0]) {
+    int i, ndim = 0;
+    if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
+        ctx->is_valid_array = ctx->head->field->type->ndim == 1;
+        ndim = 1;
+        if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
+            PyErr_Format(PyExc_ValueError,
+                         "Expected a dimension of size %zu, got %zu",
+                         ctx->head->field->type->arraysize[0], ctx->enc_count);
+            return -1;
+        }
+    }
+    if (!ctx->is_valid_array) {
+      PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
+                   ctx->head->field->type->ndim, ndim);
+      return -1;
+    }
+    for (i = 0; i < ctx->head->field->type->ndim; i++) {
+      arraysize *= ctx->head->field->type->arraysize[i];
+    }
+    ctx->is_valid_array = 0;
+    ctx->enc_count = 1;
+  }
+  group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
+  do {
+    __Pyx_StructField* field = ctx->head->field;
+    __Pyx_TypeInfo* type = field->type;
+    if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
+      size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
+    } else {
+      size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
+    }
+    if (ctx->enc_packmode == '@') {
+      size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
+      size_t align_mod_offset;
+      if (align_at == 0) return -1;
+      align_mod_offset = ctx->fmt_offset % align_at;
+      if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
+      if (ctx->struct_alignment == 0)
+          ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
+                                                                 ctx->is_complex);
+    }
+    if (type->size != size || type->typegroup != group) {
+      if (type->typegroup == 'C' && type->fields != NULL) {
+        size_t parent_offset = ctx->head->parent_offset + field->offset;
+        ++ctx->head;
+        ctx->head->field = type->fields;
+        ctx->head->parent_offset = parent_offset;
+        continue;
+      }
+      if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
+      } else {
+          __Pyx_BufFmt_RaiseExpected(ctx);
+          return -1;
+      }
+    }
+    offset = ctx->head->parent_offset + field->offset;
+    if (ctx->fmt_offset != offset) {
+      PyErr_Format(PyExc_ValueError,
+                   "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
+                   (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
+      return -1;
+    }
+    ctx->fmt_offset += size;
+    if (arraysize)
+      ctx->fmt_offset += (arraysize - 1) * size;
+    --ctx->enc_count;
+    while (1) {
+      if (field == &ctx->root) {
+        ctx->head = NULL;
+        if (ctx->enc_count != 0) {
+          __Pyx_BufFmt_RaiseExpected(ctx);
+          return -1;
+        }
+        break;
+      }
+      ctx->head->field = ++field;
+      if (field->type == NULL) {
+        --ctx->head;
+        field = ctx->head->field;
+        continue;
+      } else if (field->type->typegroup == 'S') {
+        size_t parent_offset = ctx->head->parent_offset + field->offset;
+        if (field->type->fields->type == NULL) continue;
+        field = field->type->fields;
+        ++ctx->head;
+        ctx->head->field = field;
+        ctx->head->parent_offset = parent_offset;
+        break;
+      } else {
+        break;
+      }
+    }
+  } while (ctx->enc_count);
+  ctx->enc_type = 0;
+  ctx->is_complex = 0;
+  return 0;
+}
+static PyObject *
+__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
+{
+    const char *ts = *tsp;
+    int i = 0, number, ndim;
+    ++ts;
+    if (ctx->new_count != 1) {
+        PyErr_SetString(PyExc_ValueError,
+                        "Cannot handle repeated arrays in format string");
+        return NULL;
+    }
+    if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+    ndim = ctx->head->field->type->ndim;
+    while (*ts && *ts != ')') {
+        switch (*ts) {
+            case ' ': case '\f': case '\r': case '\n': case '\t': case '\v':  continue;
+            default:  break;
+        }
+        number = __Pyx_BufFmt_ExpectNumber(&ts);
+        if (number == -1) return NULL;
+        if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
+            return PyErr_Format(PyExc_ValueError,
+                        "Expected a dimension of size %zu, got %d",
+                        ctx->head->field->type->arraysize[i], number);
+        if (*ts != ',' && *ts != ')')
+            return PyErr_Format(PyExc_ValueError,
+                                "Expected a comma in format string, got '%c'", *ts);
+        if (*ts == ',') ts++;
+        i++;
+    }
+    if (i != ndim)
+        return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
+                            ctx->head->field->type->ndim, i);
+    if (!*ts) {
+        PyErr_SetString(PyExc_ValueError,
+                        "Unexpected end of format string, expected ')'");
+        return NULL;
+    }
+    ctx->is_valid_array = 1;
+    ctx->new_count = 1;
+    *tsp = ++ts;
+    return Py_None;
+}
+static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
+  int got_Z = 0;
+  while (1) {
+    switch(*ts) {
+      case 0:
+        if (ctx->enc_type != 0 && ctx->head == NULL) {
+          __Pyx_BufFmt_RaiseExpected(ctx);
+          return NULL;
+        }
+        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+        if (ctx->head != NULL) {
+          __Pyx_BufFmt_RaiseExpected(ctx);
+          return NULL;
+        }
+        return ts;
+      case ' ':
+      case '\r':
+      case '\n':
+        ++ts;
+        break;
+      case '<':
+        if (!__Pyx_Is_Little_Endian()) {
+          PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
+          return NULL;
+        }
+        ctx->new_packmode = '=';
+        ++ts;
+        break;
+      case '>':
+      case '!':
+        if (__Pyx_Is_Little_Endian()) {
+          PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
+          return NULL;
+        }
+        ctx->new_packmode = '=';
+        ++ts;
+        break;
+      case '=':
+      case '@':
+      case '^':
+        ctx->new_packmode = *ts++;
+        break;
+      case 'T':
+        {
+          const char* ts_after_sub;
+          size_t i, struct_count = ctx->new_count;
+          size_t struct_alignment = ctx->struct_alignment;
+          ctx->new_count = 1;
+          ++ts;
+          if (*ts != '{') {
+            PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
+            return NULL;
+          }
+          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+          ctx->enc_type = 0;
+          ctx->enc_count = 0;
+          ctx->struct_alignment = 0;
+          ++ts;
+          ts_after_sub = ts;
+          for (i = 0; i != struct_count; ++i) {
+            ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
+            if (!ts_after_sub) return NULL;
+          }
+          ts = ts_after_sub;
+          if (struct_alignment) ctx->struct_alignment = struct_alignment;
+        }
+        break;
+      case '}':
+        {
+          size_t alignment = ctx->struct_alignment;
+          ++ts;
+          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+          ctx->enc_type = 0;
+          if (alignment && ctx->fmt_offset % alignment) {
+            ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
+          }
+        }
+        return ts;
+      case 'x':
+        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+        ctx->fmt_offset += ctx->new_count;
+        ctx->new_count = 1;
+        ctx->enc_count = 0;
+        ctx->enc_type = 0;
+        ctx->enc_packmode = ctx->new_packmode;
+        ++ts;
+        break;
+      case 'Z':
+        got_Z = 1;
+        ++ts;
+        if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
+          __Pyx_BufFmt_RaiseUnexpectedChar('Z');
+          return NULL;
+        }
+        CYTHON_FALLTHROUGH;
+      case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
+      case 'l': case 'L': case 'q': case 'Q':
+      case 'f': case 'd': case 'g':
+      case 'O': case 'p':
+        if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) &&
+            (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) {
+          ctx->enc_count += ctx->new_count;
+          ctx->new_count = 1;
+          got_Z = 0;
+          ++ts;
+          break;
+        }
+        CYTHON_FALLTHROUGH;
+      case 's':
+        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
+        ctx->enc_count = ctx->new_count;
+        ctx->enc_packmode = ctx->new_packmode;
+        ctx->enc_type = *ts;
+        ctx->is_complex = got_Z;
+        ++ts;
+        ctx->new_count = 1;
+        got_Z = 0;
+        break;
+      case ':':
+        ++ts;
+        while(*ts != ':') ++ts;
+        ++ts;
+        break;
+      case '(':
+        if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
+        break;
+      default:
+        {
+          int number = __Pyx_BufFmt_ExpectNumber(&ts);
+          if (number == -1) return NULL;
+          ctx->new_count = (size_t)number;
+        }
+    }
+  }
+}
+
+/* TypeInfoCompare */
+  static int
+__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
+{
+    int i;
+    if (!a || !b)
+        return 0;
+    if (a == b)
+        return 1;
+    if (a->size != b->size || a->typegroup != b->typegroup ||
+            a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
+        if (a->typegroup == 'H' || b->typegroup == 'H') {
+            return a->size == b->size;
+        } else {
+            return 0;
+        }
+    }
+    if (a->ndim) {
+        for (i = 0; i < a->ndim; i++)
+            if (a->arraysize[i] != b->arraysize[i])
+                return 0;
+    }
+    if (a->typegroup == 'S') {
+        if (a->flags != b->flags)
+            return 0;
+        if (a->fields || b->fields) {
+            if (!(a->fields && b->fields))
+                return 0;
+            for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
+                __Pyx_StructField *field_a = a->fields + i;
+                __Pyx_StructField *field_b = b->fields + i;
+                if (field_a->offset != field_b->offset ||
+                    !__pyx_typeinfo_cmp(field_a->type, field_b->type))
+                    return 0;
+            }
+            return !a->fields[i].type && !b->fields[i].type;
+        }
+    }
+    return 1;
+}
+
+/* MemviewSliceValidateAndInit */
+  static int
+__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
+{
+    if (buf->shape[dim] <= 1)
+        return 1;
+    if (buf->strides) {
+        if (spec & __Pyx_MEMVIEW_CONTIG) {
+            if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
+                if (unlikely(buf->strides[dim] != sizeof(void *))) {
+                    PyErr_Format(PyExc_ValueError,
+                                 "Buffer is not indirectly contiguous "
+                                 "in dimension %d.", dim);
+                    goto fail;
+                }
+            } else if (unlikely(buf->strides[dim] != buf->itemsize)) {
+                PyErr_SetString(PyExc_ValueError,
+                                "Buffer and memoryview are not contiguous "
+                                "in the same dimension.");
+                goto fail;
+            }
+        }
+        if (spec & __Pyx_MEMVIEW_FOLLOW) {
+            Py_ssize_t stride = buf->strides[dim];
+            if (stride < 0)
+                stride = -stride;
+            if (unlikely(stride < buf->itemsize)) {
+                PyErr_SetString(PyExc_ValueError,
+                                "Buffer and memoryview are not contiguous "
+                                "in the same dimension.");
+                goto fail;
+            }
+        }
+    } else {
+        if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) {
+            PyErr_Format(PyExc_ValueError,
+                         "C-contiguous buffer is not contiguous in "
+                         "dimension %d", dim);
+            goto fail;
+        } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) {
+            PyErr_Format(PyExc_ValueError,
+                         "C-contiguous buffer is not indirect in "
+                         "dimension %d", dim);
+            goto fail;
+        } else if (unlikely(buf->suboffsets)) {
+            PyErr_SetString(PyExc_ValueError,
+                            "Buffer exposes suboffsets but no strides");
+            goto fail;
+        }
+    }
+    return 1;
+fail:
+    return 0;
+}
+static int
+__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
+{
+    if (spec & __Pyx_MEMVIEW_DIRECT) {
+        if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) {
+            PyErr_Format(PyExc_ValueError,
+                         "Buffer not compatible with direct access "
+                         "in dimension %d.", dim);
+            goto fail;
+        }
+    }
+    if (spec & __Pyx_MEMVIEW_PTR) {
+        if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) {
+            PyErr_Format(PyExc_ValueError,
+                         "Buffer is not indirectly accessible "
+                         "in dimension %d.", dim);
+            goto fail;
+        }
+    }
+    return 1;
+fail:
+    return 0;
+}
+static int
+__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
+{
+    int i;
+    if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
+        Py_ssize_t stride = 1;
+        for (i = 0; i < ndim; i++) {
+            if (unlikely(stride * buf->itemsize != buf->strides[i]  &&  buf->shape[i] > 1)) {
+                PyErr_SetString(PyExc_ValueError,
+                    "Buffer not fortran contiguous.");
+                goto fail;
+            }
+            stride = stride * buf->shape[i];
+        }
+    } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
+        Py_ssize_t stride = 1;
+        for (i = ndim - 1; i >- 1; i--) {
+            if (unlikely(stride * buf->itemsize != buf->strides[i]  &&  buf->shape[i] > 1)) {
+                PyErr_SetString(PyExc_ValueError,
+                    "Buffer not C contiguous.");
+                goto fail;
+            }
+            stride = stride * buf->shape[i];
+        }
+    }
+    return 1;
+fail:
+    return 0;
+}
+static int __Pyx_ValidateAndInit_memviewslice(
+                int *axes_specs,
+                int c_or_f_flag,
+                int buf_flags,
+                int ndim,
+                __Pyx_TypeInfo *dtype,
+                __Pyx_BufFmt_StackElem stack[],
+                __Pyx_memviewslice *memviewslice,
+                PyObject *original_obj)
+{
+    struct __pyx_memoryview_obj *memview, *new_memview;
+    __Pyx_RefNannyDeclarations
+    Py_buffer *buf;
+    int i, spec = 0, retval = -1;
+    __Pyx_BufFmt_Context ctx;
+    int from_memoryview = __pyx_memoryview_check(original_obj);
+    __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
+    if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
+                                                            original_obj)->typeinfo)) {
+        memview = (struct __pyx_memoryview_obj *) original_obj;
+        new_memview = NULL;
+    } else {
+        memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+                                            original_obj, buf_flags, 0, dtype);
+        new_memview = memview;
+        if (unlikely(!memview))
+            goto fail;
+    }
+    buf = &memview->view;
+    if (unlikely(buf->ndim != ndim)) {
+        PyErr_Format(PyExc_ValueError,
+                "Buffer has wrong number of dimensions (expected %d, got %d)",
+                ndim, buf->ndim);
+        goto fail;
+    }
+    if (new_memview) {
+        __Pyx_BufFmt_Init(&ctx, stack, dtype);
+        if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail;
+    }
+    if (unlikely((unsigned) buf->itemsize != dtype->size)) {
+        PyErr_Format(PyExc_ValueError,
+                     "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
+                     "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
+                     buf->itemsize,
+                     (buf->itemsize > 1) ? "s" : "",
+                     dtype->name,
+                     dtype->size,
+                     (dtype->size > 1) ? "s" : "");
+        goto fail;
+    }
+    if (buf->len > 0) {
+        for (i = 0; i < ndim; i++) {
+            spec = axes_specs[i];
+            if (unlikely(!__pyx_check_strides(buf, i, ndim, spec)))
+                goto fail;
+            if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec)))
+                goto fail;
+        }
+        if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)))
+            goto fail;
+    }
+    if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
+                                         new_memview != NULL) == -1)) {
+        goto fail;
+    }
+    retval = 0;
+    goto no_fail;
+fail:
+    Py_XDECREF(new_memview);
+    retval = -1;
+no_fail:
+    __Pyx_RefNannyFinishContext();
+    return retval;
+}
+
+/* ObjectToMemviewSlice */
+  static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_int(PyObject *obj, int writable_flag) {
+    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+    __Pyx_BufFmt_StackElem stack[1];
+    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+    int retcode;
+    if (obj == Py_None) {
+        result.memview = (struct __pyx_memoryview_obj *) Py_None;
+        return result;
+    }
+    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 3,
+                                                 &__Pyx_TypeInfo_int, stack,
+                                                 &result, obj);
+    if (unlikely(retcode == -1))
+        goto __pyx_fail;
+    return result;
+__pyx_fail:
+    result.memview = NULL;
+    result.data = NULL;
+    return result;
+}
+
+/* ObjectToMemviewSlice */
+  static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_d_dc_float(PyObject *obj, int writable_flag) {
+    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+    __Pyx_BufFmt_StackElem stack[1];
+    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+    int retcode;
+    if (obj == Py_None) {
+        result.memview = (struct __pyx_memoryview_obj *) Py_None;
+        return result;
+    }
+    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 3,
+                                                 &__Pyx_TypeInfo_float, stack,
+                                                 &result, obj);
+    if (unlikely(retcode == -1))
+        goto __pyx_fail;
+    return result;
+__pyx_fail:
+    result.memview = NULL;
+    result.data = NULL;
+    return result;
+}
+
+/* ObjectToMemviewSlice */
+  static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_int(PyObject *obj, int writable_flag) {
+    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
+    __Pyx_BufFmt_StackElem stack[1];
+    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
+    int retcode;
+    if (obj == Py_None) {
+        result.memview = (struct __pyx_memoryview_obj *) Py_None;
+        return result;
+    }
+    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
+                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 1,
+                                                 &__Pyx_TypeInfo_int, stack,
+                                                 &result, obj);
+    if (unlikely(retcode == -1))
+        goto __pyx_fail;
+    return result;
+__pyx_fail:
+    result.memview = NULL;
+    result.data = NULL;
+    return result;
+}
+
+/* CIntFromPyVerify */
+  #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
+    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
+#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
+    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
+#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
+    {\
+        func_type value = func_value;\
+        if (sizeof(target_type) < sizeof(func_type)) {\
+            if (unlikely(value != (func_type) (target_type) value)) {\
+                func_type zero = 0;\
+                if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
+                    return (target_type) -1;\
+                if (is_unsigned && unlikely(value < zero))\
+                    goto raise_neg_overflow;\
+                else\
+                    goto raise_overflow;\
+            }\
+        }\
+        return (target_type) value;\
+    }
+
+/* MemviewSliceCopyTemplate */
+  static __Pyx_memviewslice
+__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
+                                 const char *mode, int ndim,
+                                 size_t sizeof_dtype, int contig_flag,
+                                 int dtype_is_object)
+{
+    __Pyx_RefNannyDeclarations
+    int i;
+    __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
+    struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
+    Py_buffer *buf = &from_memview->view;
+    PyObject *shape_tuple = NULL;
+    PyObject *temp_int = NULL;
+    struct __pyx_array_obj *array_obj = NULL;
+    struct __pyx_memoryview_obj *memview_obj = NULL;
+    __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
+    for (i = 0; i < ndim; i++) {
+        if (unlikely(from_mvs->suboffsets[i] >= 0)) {
+            PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
+                                           "indirect dimensions (axis %d)", i);
+            goto fail;
+        }
+    }
+    shape_tuple = PyTuple_New(ndim);
+    if (unlikely(!shape_tuple)) {
+        goto fail;
+    }
+    __Pyx_GOTREF(shape_tuple);
+    for(i = 0; i < ndim; i++) {
+        temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
+        if(unlikely(!temp_int)) {
+            goto fail;
+        } else {
+            PyTuple_SET_ITEM(shape_tuple, i, temp_int);
+            temp_int = NULL;
+        }
+    }
+    array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
+    if (unlikely(!array_obj)) {
+        goto fail;
+    }
+    __Pyx_GOTREF(array_obj);
+    memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
+                                    (PyObject *) array_obj, contig_flag,
+                                    dtype_is_object,
+                                    from_mvs->memview->typeinfo);
+    if (unlikely(!memview_obj))
+        goto fail;
+    if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
+        goto fail;
+    if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
+                                                dtype_is_object) < 0))
+        goto fail;
+    goto no_fail;
+fail:
+    __Pyx_XDECREF(new_mvs.memview);
+    new_mvs.memview = NULL;
+    new_mvs.data = NULL;
+no_fail:
+    __Pyx_XDECREF(shape_tuple);
+    __Pyx_XDECREF(temp_int);
+    __Pyx_XDECREF(array_obj);
+    __Pyx_RefNannyFinishContext();
+    return new_mvs;
+}
+
+/* CIntToPy */
+  static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wconversion"
+#endif
+    const int neg_one = (int) -1, const_zero = (int) 0;
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic pop
+#endif
+    const int is_unsigned = neg_one > const_zero;
+    if (is_unsigned) {
+        if (sizeof(int) < sizeof(long)) {
+            return PyInt_FromLong((long) value);
+        } else if (sizeof(int) <= sizeof(unsigned long)) {
+            return PyLong_FromUnsignedLong((unsigned long) value);
+#ifdef HAVE_LONG_LONG
+        } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
+            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
+#endif
+        }
+    } else {
+        if (sizeof(int) <= sizeof(long)) {
+            return PyInt_FromLong((long) value);
+#ifdef HAVE_LONG_LONG
+        } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
+            return PyLong_FromLongLong((PY_LONG_LONG) value);
+#endif
+        }
+    }
+    {
+        int one = 1; int little = (int)*(unsigned char *)&one;
+        unsigned char *bytes = (unsigned char *)&value;
+        return _PyLong_FromByteArray(bytes, sizeof(int),
+                                     little, !is_unsigned);
+    }
+}
+
+/* CIntFromPy */
+  static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wconversion"
+#endif
+    const int neg_one = (int) -1, const_zero = (int) 0;
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic pop
+#endif
+    const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+    if (likely(PyInt_Check(x))) {
+        if (sizeof(int) < sizeof(long)) {
+            __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
+        } else {
+            long val = PyInt_AS_LONG(x);
+            if (is_unsigned && unlikely(val < 0)) {
+                goto raise_neg_overflow;
+            }
+            return (int) val;
+        }
+    } else
+#endif
+    if (likely(PyLong_Check(x))) {
+        if (is_unsigned) {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (int) 0;
+                case  1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
+                case 2:
+                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
+                            return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
+                            return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
+                            return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
+                        }
+                    }
+                    break;
+            }
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON
+            if (unlikely(Py_SIZE(x) < 0)) {
+                goto raise_neg_overflow;
+            }
+#else
+            {
+                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
+                if (unlikely(result < 0))
+                    return (int) -1;
+                if (unlikely(result == 1))
+                    goto raise_neg_overflow;
+            }
+#endif
+            if (sizeof(int) <= sizeof(unsigned long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
+#endif
+            }
+        } else {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (int) 0;
+                case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
+                case  1: __PYX_VERIFY_RETURN_INT(int,  digit, +digits[0])
+                case -2:
+                    if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
+                            return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+                case 2:
+                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
+                            return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+                case -3:
+                    if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
+                            return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
+                            return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+                case -4:
+                    if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
+                            return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
+                            return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
+                        }
+                    }
+                    break;
+            }
+#endif
+            if (sizeof(int) <= sizeof(long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
+#endif
+            }
+        }
+        {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+            PyErr_SetString(PyExc_RuntimeError,
+                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+            int val;
+            PyObject *v = __Pyx_PyNumber_IntOrLong(x);
+ #if PY_MAJOR_VERSION < 3
+            if (likely(v) && !PyLong_Check(v)) {
+                PyObject *tmp = v;
+                v = PyNumber_Long(tmp);
+                Py_DECREF(tmp);
+            }
+ #endif
+            if (likely(v)) {
+                int one = 1; int is_little = (int)*(unsigned char *)&one;
+                unsigned char *bytes = (unsigned char *)&val;
+                int ret = _PyLong_AsByteArray((PyLongObject *)v,
+                                              bytes, sizeof(val),
+                                              is_little, !is_unsigned);
+                Py_DECREF(v);
+                if (likely(!ret))
+                    return val;
+            }
+#endif
+            return (int) -1;
+        }
+    } else {
+        int val;
+        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
+        if (!tmp) return (int) -1;
+        val = __Pyx_PyInt_As_int(tmp);
+        Py_DECREF(tmp);
+        return val;
+    }
+raise_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "value too large to convert to int");
+    return (int) -1;
+raise_neg_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "can't convert negative value to int");
+    return (int) -1;
+}
+
+/* CIntToPy */
+  static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wconversion"
+#endif
+    const long neg_one = (long) -1, const_zero = (long) 0;
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic pop
+#endif
+    const int is_unsigned = neg_one > const_zero;
+    if (is_unsigned) {
+        if (sizeof(long) < sizeof(long)) {
+            return PyInt_FromLong((long) value);
+        } else if (sizeof(long) <= sizeof(unsigned long)) {
+            return PyLong_FromUnsignedLong((unsigned long) value);
+#ifdef HAVE_LONG_LONG
+        } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
+            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
+#endif
+        }
+    } else {
+        if (sizeof(long) <= sizeof(long)) {
+            return PyInt_FromLong((long) value);
+#ifdef HAVE_LONG_LONG
+        } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
+            return PyLong_FromLongLong((PY_LONG_LONG) value);
+#endif
+        }
+    }
+    {
+        int one = 1; int little = (int)*(unsigned char *)&one;
+        unsigned char *bytes = (unsigned char *)&value;
+        return _PyLong_FromByteArray(bytes, sizeof(long),
+                                     little, !is_unsigned);
+    }
+}
+
+/* CIntFromPy */
+  static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wconversion"
+#endif
+    const long neg_one = (long) -1, const_zero = (long) 0;
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic pop
+#endif
+    const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+    if (likely(PyInt_Check(x))) {
+        if (sizeof(long) < sizeof(long)) {
+            __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
+        } else {
+            long val = PyInt_AS_LONG(x);
+            if (is_unsigned && unlikely(val < 0)) {
+                goto raise_neg_overflow;
+            }
+            return (long) val;
+        }
+    } else
+#endif
+    if (likely(PyLong_Check(x))) {
+        if (is_unsigned) {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (long) 0;
+                case  1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
+                case 2:
+                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
+                            return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
+                            return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
+                            return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
+                        }
+                    }
+                    break;
+            }
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON
+            if (unlikely(Py_SIZE(x) < 0)) {
+                goto raise_neg_overflow;
+            }
+#else
+            {
+                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
+                if (unlikely(result < 0))
+                    return (long) -1;
+                if (unlikely(result == 1))
+                    goto raise_neg_overflow;
+            }
+#endif
+            if (sizeof(long) <= sizeof(unsigned long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
+#endif
+            }
+        } else {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (long) 0;
+                case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
+                case  1: __PYX_VERIFY_RETURN_INT(long,  digit, +digits[0])
+                case -2:
+                    if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
+                            return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+                case 2:
+                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
+                            return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+                case -3:
+                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
+                            return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
+                            return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+                case -4:
+                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
+                            return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
+                            return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
+                        }
+                    }
+                    break;
+            }
+#endif
+            if (sizeof(long) <= sizeof(long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
+#endif
+            }
+        }
+        {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+            PyErr_SetString(PyExc_RuntimeError,
+                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+            long val;
+            PyObject *v = __Pyx_PyNumber_IntOrLong(x);
+ #if PY_MAJOR_VERSION < 3
+            if (likely(v) && !PyLong_Check(v)) {
+                PyObject *tmp = v;
+                v = PyNumber_Long(tmp);
+                Py_DECREF(tmp);
+            }
+ #endif
+            if (likely(v)) {
+                int one = 1; int is_little = (int)*(unsigned char *)&one;
+                unsigned char *bytes = (unsigned char *)&val;
+                int ret = _PyLong_AsByteArray((PyLongObject *)v,
+                                              bytes, sizeof(val),
+                                              is_little, !is_unsigned);
+                Py_DECREF(v);
+                if (likely(!ret))
+                    return val;
+            }
+#endif
+            return (long) -1;
+        }
+    } else {
+        long val;
+        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
+        if (!tmp) return (long) -1;
+        val = __Pyx_PyInt_As_long(tmp);
+        Py_DECREF(tmp);
+        return val;
+    }
+raise_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "value too large to convert to long");
+    return (long) -1;
+raise_neg_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "can't convert negative value to long");
+    return (long) -1;
+}
+
+/* CIntFromPy */
+  static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wconversion"
+#endif
+    const char neg_one = (char) -1, const_zero = (char) 0;
+#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
+#pragma GCC diagnostic pop
+#endif
+    const int is_unsigned = neg_one > const_zero;
+#if PY_MAJOR_VERSION < 3
+    if (likely(PyInt_Check(x))) {
+        if (sizeof(char) < sizeof(long)) {
+            __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
+        } else {
+            long val = PyInt_AS_LONG(x);
+            if (is_unsigned && unlikely(val < 0)) {
+                goto raise_neg_overflow;
+            }
+            return (char) val;
+        }
+    } else
+#endif
+    if (likely(PyLong_Check(x))) {
+        if (is_unsigned) {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (char) 0;
+                case  1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0])
+                case 2:
+                    if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) {
+                            return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) {
+                            return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) {
+                            return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
+                        }
+                    }
+                    break;
+            }
+#endif
+#if CYTHON_COMPILING_IN_CPYTHON
+            if (unlikely(Py_SIZE(x) < 0)) {
+                goto raise_neg_overflow;
+            }
+#else
+            {
+                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
+                if (unlikely(result < 0))
+                    return (char) -1;
+                if (unlikely(result == 1))
+                    goto raise_neg_overflow;
+            }
+#endif
+            if (sizeof(char) <= sizeof(unsigned long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
+#endif
+            }
+        } else {
+#if CYTHON_USE_PYLONG_INTERNALS
+            const digit* digits = ((PyLongObject*)x)->ob_digit;
+            switch (Py_SIZE(x)) {
+                case  0: return (char) 0;
+                case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0]))
+                case  1: __PYX_VERIFY_RETURN_INT(char,  digit, +digits[0])
+                case -2:
+                    if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
+                            return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+                case 2:
+                    if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
+                            return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+                case -3:
+                    if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
+                            return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+                case 3:
+                    if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
+                            return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+                case -4:
+                    if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
+                            return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+                case 4:
+                    if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
+                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
+                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
+                        } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
+                            return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
+                        }
+                    }
+                    break;
+            }
+#endif
+            if (sizeof(char) <= sizeof(long)) {
+                __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x))
+#ifdef HAVE_LONG_LONG
+            } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
+                __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x))
+#endif
+            }
+        }
+        {
+#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
+            PyErr_SetString(PyExc_RuntimeError,
+                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
+#else
+            char val;
+            PyObject *v = __Pyx_PyNumber_IntOrLong(x);
+ #if PY_MAJOR_VERSION < 3
+            if (likely(v) && !PyLong_Check(v)) {
+                PyObject *tmp = v;
+                v = PyNumber_Long(tmp);
+                Py_DECREF(tmp);
+            }
+ #endif
+            if (likely(v)) {
+                int one = 1; int is_little = (int)*(unsigned char *)&one;
+                unsigned char *bytes = (unsigned char *)&val;
+                int ret = _PyLong_AsByteArray((PyLongObject *)v,
+                                              bytes, sizeof(val),
+                                              is_little, !is_unsigned);
+                Py_DECREF(v);
+                if (likely(!ret))
+                    return val;
+            }
+#endif
+            return (char) -1;
+        }
+    } else {
+        char val;
+        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
+        if (!tmp) return (char) -1;
+        val = __Pyx_PyInt_As_char(tmp);
+        Py_DECREF(tmp);
+        return val;
+    }
+raise_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "value too large to convert to char");
+    return (char) -1;
+raise_neg_overflow:
+    PyErr_SetString(PyExc_OverflowError,
+        "can't convert negative value to char");
+    return (char) -1;
+}
+
+/* CheckBinaryVersion */
+  static int __Pyx_check_binary_version(void) {
+    char ctversion[5];
+    int same=1, i, found_dot;
+    const char* rt_from_call = Py_GetVersion();
+    PyOS_snprintf(ctversion, 5, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
+    found_dot = 0;
+    for (i = 0; i < 4; i++) {
+        if (!ctversion[i]) {
+            same = (rt_from_call[i] < '0' || rt_from_call[i] > '9');
+            break;
+        }
+        if (rt_from_call[i] != ctversion[i]) {
+            same = 0;
+            break;
+        }
+    }
+    if (!same) {
+        char rtversion[5] = {'\0'};
+        char message[200];
+        for (i=0; i<4; ++i) {
+            if (rt_from_call[i] == '.') {
+                if (found_dot) break;
+                found_dot = 1;
+            } else if (rt_from_call[i] < '0' || rt_from_call[i] > '9') {
+                break;
+            }
+            rtversion[i] = rt_from_call[i];
+        }
+        PyOS_snprintf(message, sizeof(message),
+                      "compiletime version %s of module '%.100s' "
+                      "does not match runtime version %s",
+                      ctversion, __Pyx_MODULE_NAME, rtversion);
+        return PyErr_WarnEx(NULL, message, 1);
+    }
+    return 0;
+}
+
+/* InitStrings */
+  static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
+    while (t->p) {
+        #if PY_MAJOR_VERSION < 3
+        if (t->is_unicode) {
+            *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
+        } else if (t->intern) {
+            *t->p = PyString_InternFromString(t->s);
+        } else {
+            *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
+        }
+        #else
+        if (t->is_unicode | t->is_str) {
+            if (t->intern) {
+                *t->p = PyUnicode_InternFromString(t->s);
+            } else if (t->encoding) {
+                *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
+            } else {
+                *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
+            }
+        } else {
+            *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
+        }
+        #endif
+        if (!*t->p)
+            return -1;
+        if (PyObject_Hash(*t->p) == -1)
+            return -1;
+        ++t;
+    }
+    return 0;
+}
+
+static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
+    return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
+}
+static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) {
+    Py_ssize_t ignore;
+    return __Pyx_PyObject_AsStringAndSize(o, &ignore);
+}
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+#if !CYTHON_PEP393_ENABLED
+static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+    char* defenc_c;
+    PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
+    if (!defenc) return NULL;
+    defenc_c = PyBytes_AS_STRING(defenc);
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+    {
+        char* end = defenc_c + PyBytes_GET_SIZE(defenc);
+        char* c;
+        for (c = defenc_c; c < end; c++) {
+            if ((unsigned char) (*c) >= 128) {
+                PyUnicode_AsASCIIString(o);
+                return NULL;
+            }
+        }
+    }
+#endif
+    *length = PyBytes_GET_SIZE(defenc);
+    return defenc_c;
+}
+#else
+static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+    if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL;
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+    if (likely(PyUnicode_IS_ASCII(o))) {
+        *length = PyUnicode_GET_LENGTH(o);
+        return PyUnicode_AsUTF8(o);
+    } else {
+        PyUnicode_AsASCIIString(o);
+        return NULL;
+    }
+#else
+    return PyUnicode_AsUTF8AndSize(o, length);
+#endif
+}
+#endif
+#endif
+static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
+#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
+    if (
+#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
+            __Pyx_sys_getdefaultencoding_not_ascii &&
+#endif
+            PyUnicode_Check(o)) {
+        return __Pyx_PyUnicode_AsStringAndSize(o, length);
+    } else
+#endif
+#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
+    if (PyByteArray_Check(o)) {
+        *length = PyByteArray_GET_SIZE(o);
+        return PyByteArray_AS_STRING(o);
+    } else
+#endif
+    {
+        char* result;
+        int r = PyBytes_AsStringAndSize(o, &result, length);
+        if (unlikely(r < 0)) {
+            return NULL;
+        } else {
+            return result;
+        }
+    }
+}
+static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
+   int is_true = x == Py_True;
+   if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
+   else return PyObject_IsTrue(x);
+}
+static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) {
+    int retval;
+    if (unlikely(!x)) return -1;
+    retval = __Pyx_PyObject_IsTrue(x);
+    Py_DECREF(x);
+    return retval;
+}
+static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) {
+#if PY_MAJOR_VERSION >= 3
+    if (PyLong_Check(result)) {
+        if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1,
+                "__int__ returned non-int (type %.200s).  "
+                "The ability to return an instance of a strict subclass of int "
+                "is deprecated, and may be removed in a future version of Python.",
+                Py_TYPE(result)->tp_name)) {
+            Py_DECREF(result);
+            return NULL;
+        }
+        return result;
+    }
+#endif
+    PyErr_Format(PyExc_TypeError,
+                 "__%.4s__ returned non-%.4s (type %.200s)",
+                 type_name, type_name, Py_TYPE(result)->tp_name);
+    Py_DECREF(result);
+    return NULL;
+}
+static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) {
+#if CYTHON_USE_TYPE_SLOTS
+  PyNumberMethods *m;
+#endif
+  const char *name = NULL;
+  PyObject *res = NULL;
+#if PY_MAJOR_VERSION < 3
+  if (likely(PyInt_Check(x) || PyLong_Check(x)))
+#else
+  if (likely(PyLong_Check(x)))
+#endif
+    return __Pyx_NewRef(x);
+#if CYTHON_USE_TYPE_SLOTS
+  m = Py_TYPE(x)->tp_as_number;
+  #if PY_MAJOR_VERSION < 3
+  if (m && m->nb_int) {
+    name = "int";
+    res = m->nb_int(x);
+  }
+  else if (m && m->nb_long) {
+    name = "long";
+    res = m->nb_long(x);
+  }
+  #else
+  if (likely(m && m->nb_int)) {
+    name = "int";
+    res = m->nb_int(x);
+  }
+  #endif
+#else
+  if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) {
+    res = PyNumber_Int(x);
+  }
+#endif
+  if (likely(res)) {
+#if PY_MAJOR_VERSION < 3
+    if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) {
+#else
+    if (unlikely(!PyLong_CheckExact(res))) {
+#endif
+        return __Pyx_PyNumber_IntOrLongWrongResultType(res, name);
+    }
+  }
+  else if (!PyErr_Occurred()) {
+    PyErr_SetString(PyExc_TypeError,
+                    "an integer is required");
+  }
+  return res;
+}
+static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
+  Py_ssize_t ival;
+  PyObject *x;
+#if PY_MAJOR_VERSION < 3
+  if (likely(PyInt_CheckExact(b))) {
+    if (sizeof(Py_ssize_t) >= sizeof(long))
+        return PyInt_AS_LONG(b);
+    else
+        return PyInt_AsSsize_t(b);
+  }
+#endif
+  if (likely(PyLong_CheckExact(b))) {
+    #if CYTHON_USE_PYLONG_INTERNALS
+    const digit* digits = ((PyLongObject*)b)->ob_digit;
+    const Py_ssize_t size = Py_SIZE(b);
+    if (likely(__Pyx_sst_abs(size) <= 1)) {
+        ival = likely(size) ? digits[0] : 0;
+        if (size == -1) ival = -ival;
+        return ival;
+    } else {
+      switch (size) {
+         case 2:
+           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
+             return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+         case -2:
+           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
+             return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+         case 3:
+           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
+             return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+         case -3:
+           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
+             return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+         case 4:
+           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
+             return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+         case -4:
+           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
+             return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
+           }
+           break;
+      }
+    }
+    #endif
+    return PyLong_AsSsize_t(b);
+  }
+  x = PyNumber_Index(b);
+  if (!x) return -1;
+  ival = PyInt_AsSsize_t(x);
+  Py_DECREF(x);
+  return ival;
+}
+static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) {
+  if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) {
+    return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o);
+#if PY_MAJOR_VERSION < 3
+  } else if (likely(PyInt_CheckExact(o))) {
+    return PyInt_AS_LONG(o);
+#endif
+  } else {
+    Py_ssize_t ival;
+    PyObject *x;
+    x = PyNumber_Index(o);
+    if (!x) return -1;
+    ival = PyInt_AsLong(x);
+    Py_DECREF(x);
+    return ival;
+  }
+}
+static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) {
+  return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False);
+}
+static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
+    return PyInt_FromSize_t(ival);
+}
+
+
+#endif /* Py_PYTHON_H */
diff --git a/monotonic_align/core.pyx b/monotonic_align/core.pyx
new file mode 100644
index 0000000000000000000000000000000000000000..1fa3fbd38c190073201107c8d569a9f464a029c7
--- /dev/null
+++ b/monotonic_align/core.pyx
@@ -0,0 +1,42 @@
+cimport cython
+from cython.parallel import prange
+
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+cdef void maximum_path_each(int[:,::1] path, float[:,::1] value, int t_y, int t_x, float max_neg_val=-1e9) nogil:
+  cdef int x
+  cdef int y
+  cdef float v_prev
+  cdef float v_cur
+  cdef float tmp
+  cdef int index = t_x - 1
+
+  for y in range(t_y):
+    for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
+      if x == y:
+        v_cur = max_neg_val
+      else:
+        v_cur = value[y-1, x]
+      if x == 0:
+        if y == 0:
+          v_prev = 0.
+        else:
+          v_prev = max_neg_val
+      else:
+        v_prev = value[y-1, x-1]
+      value[y, x] += max(v_prev, v_cur)
+
+  for y in range(t_y - 1, -1, -1):
+    path[y, index] = 1
+    if index != 0 and (index == y or value[y-1, index] < value[y-1, index-1]):
+      index = index - 1
+
+
+@cython.boundscheck(False)
+@cython.wraparound(False)
+cpdef void maximum_path_c(int[:,:,::1] paths, float[:,:,::1] values, int[::1] t_ys, int[::1] t_xs) nogil:
+  cdef int b = paths.shape[0]
+  cdef int i
+  for i in prange(b, nogil=True):
+    maximum_path_each(paths[i], values[i], t_ys[i], t_xs[i])
diff --git a/monotonic_align/monotonic_align/core.cpython-310-x86_64-linux-gnu.so b/monotonic_align/monotonic_align/core.cpython-310-x86_64-linux-gnu.so
new file mode 100644
index 0000000000000000000000000000000000000000..8acb4d1eac6192654b643fa9e186a7e75e580889
Binary files /dev/null and b/monotonic_align/monotonic_align/core.cpython-310-x86_64-linux-gnu.so differ
diff --git a/monotonic_align/setup.py b/monotonic_align/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..391e759b82fbc3fa8c6b7522563eb1bbfaab1f59
--- /dev/null
+++ b/monotonic_align/setup.py
@@ -0,0 +1,9 @@
+from distutils.core import setup
+from Cython.Build import cythonize
+import numpy
+
+setup(
+  name = 'monotonic_align',
+  ext_modules = cythonize("core.pyx"),
+  include_dirs=[numpy.get_include()]
+)
diff --git a/preprocess_v2.py b/preprocess_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..0636340cce4586b2dae00425788ed8aaab09a6a3
--- /dev/null
+++ b/preprocess_v2.py
@@ -0,0 +1,153 @@
+import os
+import argparse
+import json
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--add_auxiliary_data", type=bool, help="Whether to add extra data as fine-tuning helper")
+    parser.add_argument("--languages", default="CJE")
+    args = parser.parse_args()
+    if args.languages == "CJE":
+        langs = ["[ZH]", "[JA]", "[EN]"]
+    elif args.languages == "CJ":
+        langs = ["[ZH]", "[JA]"]
+    elif args.languages == "C":
+        langs = ["[ZH]"]
+    elif args.languages == "J":
+        langs = ["[JA]"]
+    new_annos = []
+    # Source 1: transcribed short audios
+    if os.path.exists("short_character_anno.txt"):
+        with open("short_character_anno.txt", 'r', encoding='utf-8') as f:
+            short_character_anno = f.readlines()
+            new_annos += short_character_anno
+    # Source 2: transcribed long audio segments
+    if os.path.exists("./long_character_anno.txt"):
+        with open("./long_character_anno.txt", 'r', encoding='utf-8') as f:
+            long_character_anno = f.readlines()
+            new_annos += long_character_anno
+
+    # Get all speaker names
+    speakers = []
+    for line in new_annos:
+        path, speaker, text = line.split("|")
+        if speaker not in speakers:
+            speakers.append(speaker)
+    assert (len(speakers) != 0), "No audio file found. Please check your uploaded file structure."
+    # Source 3 (Optional): sampled audios as extra training helpers
+    if args.add_auxiliary_data:
+        with open("./sampled_audio4ft.txt", 'r', encoding='utf-8') as f:
+            old_annos = f.readlines()
+        # filter old_annos according to supported languages
+        filtered_old_annos = []
+        for line in old_annos:
+            for lang in langs:
+                if lang in line:
+                    filtered_old_annos.append(line)
+        old_annos = filtered_old_annos
+        for line in old_annos:
+            path, speaker, text = line.split("|")
+            if speaker not in speakers:
+                speakers.append(speaker)
+        num_old_voices = len(old_annos)
+        num_new_voices = len(new_annos)
+        # STEP 1: balance number of new & old voices
+        cc_duplicate = num_old_voices // num_new_voices
+        if cc_duplicate == 0:
+            cc_duplicate = 1
+
+
+        # STEP 2: modify config file
+        with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+            hps = json.load(f)
+
+        # assign ids to new speakers
+        speaker2id = {}
+        for i, speaker in enumerate(speakers):
+            speaker2id[speaker] = i
+        # modify n_speakers
+        hps['data']["n_speakers"] = len(speakers)
+        # overwrite speaker names
+        hps['speakers'] = speaker2id
+        hps['train']['log_interval'] = 10
+        hps['train']['eval_interval'] = 100
+        hps['train']['batch_size'] = 16
+        hps['data']['training_files'] = "final_annotation_train.txt"
+        hps['data']['validation_files'] = "final_annotation_val.txt"
+        # save modified config
+        with open("./configs/modified_finetune_speaker.json", 'w', encoding='utf-8') as f:
+            json.dump(hps, f, indent=2)
+
+        # STEP 3: clean annotations, replace speaker names with assigned speaker IDs
+        import text
+        cleaned_new_annos = []
+        for i, line in enumerate(new_annos):
+            path, speaker, txt = line.split("|")
+            if len(txt) > 150:
+                continue
+            cleaned_text = text._clean_text(txt, hps['data']['text_cleaners'])
+            cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+            cleaned_new_annos.append(path + "|" + str(speaker2id[speaker]) + "|" + cleaned_text)
+        cleaned_old_annos = []
+        for i, line in enumerate(old_annos):
+            path, speaker, txt = line.split("|")
+            if len(txt) > 150:
+                continue
+            cleaned_text = text._clean_text(txt, hps['data']['text_cleaners'])
+            cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+            cleaned_old_annos.append(path + "|" + str(speaker2id[speaker]) + "|" + cleaned_text)
+        # merge with old annotation
+        final_annos = cleaned_old_annos + cc_duplicate * cleaned_new_annos
+        # save annotation file
+        with open("./final_annotation_train.txt", 'w', encoding='utf-8') as f:
+            for line in final_annos:
+                f.write(line)
+        # save annotation file for validation
+        with open("./final_annotation_val.txt", 'w', encoding='utf-8') as f:
+            for line in cleaned_new_annos:
+                f.write(line)
+        print("finished")
+    else:
+        # Do not add extra helper data
+        # STEP 1: modify config file
+        with open("./configs/amitaro_jp_base.json", 'r', encoding='utf-8') as f:
+            hps = json.load(f)
+
+        # assign ids to new speakers
+        speaker2id = {}
+        for i, speaker in enumerate(speakers):
+            speaker2id[speaker] = i
+        # modify n_speakers
+        hps['data']["n_speakers"] = len(speakers)
+        # overwrite speaker names
+        hps['speakers'] = speaker2id
+        hps['train']['log_interval'] = 10
+        hps['train']['eval_interval'] = 100
+        hps['train']['batch_size'] = 16
+        hps['data']['training_files'] = "final_annotation_train.txt"
+        hps['data']['validation_files'] = "final_annotation_val.txt"
+        # save modified config
+        with open("./configs/modified_finetune_speaker.json", 'w', encoding='utf-8') as f:
+            json.dump(hps, f, indent=2)
+
+        # STEP 2: clean annotations, replace speaker names with assigned speaker IDs
+        import text
+
+        cleaned_new_annos = []
+        for i, line in enumerate(new_annos):
+            path, speaker, txt = line.split("|")
+            if len(txt) > 150:
+                continue
+            cleaned_text = text._clean_text(txt, hps['data']['text_cleaners']).replace("[ZH]", "")
+            cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+            cleaned_new_annos.append(path + "|" + str(speaker2id[speaker]) + "|" + cleaned_text)
+
+        final_annos = cleaned_new_annos
+        # save annotation file
+        with open("./final_annotation_train.txt", 'w', encoding='utf-8') as f:
+            for line in final_annos:
+                f.write(line)
+        # save annotation file for validation
+        with open("./final_annotation_val.txt", 'w', encoding='utf-8') as f:
+            for line in cleaned_new_annos:
+                f.write(line)
+        print("finished")
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..222cf85123125c14a967846a6b16cbab41d698a4
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,26 @@
+Cython==0.29.21
+librosa==0.9.2
+matplotlib==3.3.1
+scikit-learn==1.0.2
+numpy==1.22
+scipy
+tensorboard
+pyopenjtalk>=0.3.0
+torch
+torchvision
+torchaudio
+unidecode
+jamo
+pypinyin
+jieba
+protobuf
+cn2an
+inflect
+eng_to_ipa
+ko_pron
+indic_transliteration==2.3.37
+num_thai==0.0.5
+opencc==1.1.1
+demucs
+openai-whisper
+gradio
\ No newline at end of file
diff --git a/scripts/denoise_audio.py b/scripts/denoise_audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..fc061c61bdd470ced61bc7fb448c94e2c5fd8b30
--- /dev/null
+++ b/scripts/denoise_audio.py
@@ -0,0 +1,22 @@
+import os
+import json
+import torchaudio
+raw_audio_dir = "./raw_audio/"
+denoise_audio_dir = "./denoised_audio/"
+filelist = list(os.walk(raw_audio_dir))[0][2]
+# 2023/4/21: Get the target sampling rate
+with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+    hps = json.load(f)
+target_sr = hps['data']['sampling_rate']
+for file in filelist:
+    if file.endswith(".wav"):
+        os.system(f"demucs --two-stems=vocals {raw_audio_dir}{file}")
+for file in filelist:
+    file = file.replace(".wav", "")
+    wav, sr = torchaudio.load(f"./separated/htdemucs/{file}/vocals.wav", frame_offset=0, num_frames=-1, normalize=True,
+                              channels_first=True)
+    # merge two channels into one
+    wav = wav.mean(dim=0).unsqueeze(0)
+    if sr != target_sr:
+        wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sr)(wav)
+    torchaudio.save(denoise_audio_dir + file + ".wav", wav, target_sr, channels_first=True)
\ No newline at end of file
diff --git a/scripts/download_model.py b/scripts/download_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f1ab59aa549afdf107bf2ff97d48149a87da6f4
--- /dev/null
+++ b/scripts/download_model.py
@@ -0,0 +1,4 @@
+from google.colab import files
+files.download("./G_latest.pth")
+files.download("./finetune_speaker.json")
+files.download("./moegoe_config.json")
\ No newline at end of file
diff --git a/scripts/download_video.py b/scripts/download_video.py
new file mode 100644
index 0000000000000000000000000000000000000000..3ab1a7f3698d373c3fff6119f1f222c061f4c20f
--- /dev/null
+++ b/scripts/download_video.py
@@ -0,0 +1,37 @@
+import os
+import random
+import shutil
+from concurrent.futures import ThreadPoolExecutor
+from google.colab import files
+
+basepath = os.getcwd()
+uploaded = files.upload()  # 上传文件
+for filename in uploaded.keys():
+    assert (filename.endswith(".txt")), "speaker-videolink info could only be .txt file!"
+    shutil.move(os.path.join(basepath, filename), os.path.join("./speaker_links.txt"))
+
+
+def generate_infos():
+    infos = []
+    with open("./speaker_links.txt", 'r', encoding='utf-8') as f:
+        lines = f.readlines()
+    for line in lines:
+        line = line.replace("\n", "").replace(" ", "")
+        if line == "":
+            continue
+        speaker, link = line.split("|")
+        filename = speaker + "_" + str(random.randint(0, 1000000))
+        infos.append({"link": link, "filename": filename})
+    return infos
+
+
+def download_video(info):
+    link = info["link"]
+    filename = info["filename"]
+    os.system(f"youtube-dl -f 0 {link} -o ./video_data/{filename}.mp4 --no-check-certificate")
+
+
+if __name__ == "__main__":
+    infos = generate_infos()
+    with ThreadPoolExecutor(max_workers=os.cpu_count()) as executor:
+        executor.map(download_video, infos)
diff --git a/scripts/long_audio_transcribe.py b/scripts/long_audio_transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..1d0026c2d5061e0f0e113d7b6b9742ef4dcc09f7
--- /dev/null
+++ b/scripts/long_audio_transcribe.py
@@ -0,0 +1,75 @@
+from moviepy.editor import AudioFileClip
+import whisper
+import os
+import json
+import torchaudio
+import librosa
+import torch
+import argparse
+parent_dir = "./denoised_audio/"
+filelist = list(os.walk(parent_dir))[0][2]
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--languages", default="CJE")
+    parser.add_argument("--whisper_size", default="medium")
+    args = parser.parse_args()
+    if args.languages == "CJE":
+        lang2token = {
+            'zh': "[ZH]",
+            'ja': "[JA]",
+            "en": "[EN]",
+        }
+    elif args.languages == "CJ":
+        lang2token = {
+            'zh': "[ZH]",
+            'ja': "[JA]",
+        }
+    elif args.languages == "C":
+        lang2token = {
+            'zh': "[ZH]",
+        }
+    assert(torch.cuda.is_available()), "Please enable GPU in order to run Whisper!"
+    with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+    target_sr = hps['data']['sampling_rate']
+    model = whisper.load_model(args.whisper_size)
+    speaker_annos = []
+    for file in filelist:
+        print(f"transcribing {parent_dir + file}...\n")
+        options = dict(beam_size=5, best_of=5)
+        transcribe_options = dict(task="transcribe", **options)
+        result = model.transcribe(parent_dir + file, word_timestamps=True, **transcribe_options)
+        segments = result["segments"]
+        # result = model.transcribe(parent_dir + file)
+        lang = result['language']
+        if result['language'] not in list(lang2token.keys()):
+            print(f"{lang} not supported, ignoring...\n")
+            continue
+        # segment audio based on segment results
+        character_name = file.rstrip(".wav").split("_")[0]
+        code = file.rstrip(".wav").split("_")[1]
+        if not os.path.exists("./segmented_character_voice/" + character_name):
+            os.mkdir("./segmented_character_voice/" + character_name)
+        wav, sr = torchaudio.load(parent_dir + file, frame_offset=0, num_frames=-1, normalize=True,
+                                  channels_first=True)
+
+        for i, seg in enumerate(result['segments']):
+            start_time = seg['start']
+            end_time = seg['end']
+            text = seg['text']
+            text = lang2token[lang] + text.replace("\n", "") + lang2token[lang]
+            text = text + "\n"
+            wav_seg = wav[:, int(start_time*sr):int(end_time*sr)]
+            wav_seg_name = f"{character_name}_{code}_{i}.wav"
+            savepth = "./segmented_character_voice/" + character_name + "/" + wav_seg_name
+            speaker_annos.append(savepth + "|" + character_name + "|" + text)
+            print(f"Transcribed segment: {speaker_annos[-1]}")
+            # trimmed_wav_seg = librosa.effects.trim(wav_seg.squeeze().numpy())
+            # trimmed_wav_seg = torch.tensor(trimmed_wav_seg[0]).unsqueeze(0)
+            torchaudio.save(savepth, wav_seg, target_sr, channels_first=True)
+    if len(speaker_annos) == 0:
+        print("Warning: no long audios & videos found, this IS expected if you have only uploaded short audios")
+        print("this IS NOT expected if you have uploaded any long audios, videos or video links. Please check your file structure or make sure your audio/video language is supported.")
+    with open("./long_character_anno.txt", 'w', encoding='utf-8') as f:
+        for line in speaker_annos:
+            f.write(line)
diff --git a/scripts/rearrange_speaker.py b/scripts/rearrange_speaker.py
new file mode 100644
index 0000000000000000000000000000000000000000..de0f7545904cc088377c552cc6d9b058c5e9d342
--- /dev/null
+++ b/scripts/rearrange_speaker.py
@@ -0,0 +1,37 @@
+import torch
+import argparse
+import json
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model_dir", type=str, default="./OUTPUT_MODEL/G_latest.pth")
+    parser.add_argument("--config_dir", type=str, default="./configs/modified_finetune_speaker.json")
+    args = parser.parse_args()
+
+    model_sd = torch.load(args.model_dir, map_location='cpu')
+    with open(args.config_dir, 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+
+    valid_speakers = list(hps['speakers'].keys())
+    if hps['data']['n_speakers'] > len(valid_speakers):
+        new_emb_g = torch.zeros([len(valid_speakers), 256])
+        old_emb_g = model_sd['model']['emb_g.weight']
+        for i, speaker in enumerate(valid_speakers):
+            new_emb_g[i, :] = old_emb_g[hps['speakers'][speaker], :]
+            hps['speakers'][speaker] = i
+        hps['data']['n_speakers'] = len(valid_speakers)
+        model_sd['model']['emb_g.weight'] = new_emb_g
+        with open("./finetune_speaker.json", 'w', encoding='utf-8') as f:
+            json.dump(hps, f, indent=2)
+        torch.save(model_sd, "./G_latest.pth")
+    else:
+        with open("./finetune_speaker.json", 'w', encoding='utf-8') as f:
+            json.dump(hps, f, indent=2)
+        torch.save(model_sd, "./G_latest.pth")
+    # save another config file copy in MoeGoe format
+    hps['speakers'] = valid_speakers
+    with open("./moegoe_config.json", 'w', encoding='utf-8') as f:
+        json.dump(hps, f, indent=2)
+
+
+
diff --git a/scripts/resample.py b/scripts/resample.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ed44ff6036cb6cd6f89cfc8b14c7d97115f4df4
--- /dev/null
+++ b/scripts/resample.py
@@ -0,0 +1,20 @@
+import os
+import json
+import argparse
+import torchaudio
+
+
+def main():
+    with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+    target_sr = hps['data']['sampling_rate']
+    filelist = list(os.walk("./sampled_audio4ft"))[0][2]
+    if target_sr != 22050:
+        for wavfile in filelist:
+            wav, sr = torchaudio.load("./sampled_audio4ft" + "/" + wavfile, frame_offset=0, num_frames=-1,
+                                      normalize=True, channels_first=True)
+            wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sr)(wav)
+            torchaudio.save("./sampled_audio4ft" + "/" + wavfile, wav, target_sr, channels_first=True)
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/scripts/short_audio_transcribe.py b/scripts/short_audio_transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd6a6210b80cf7a511916324fdafbbf7f1466bab
--- /dev/null
+++ b/scripts/short_audio_transcribe.py
@@ -0,0 +1,91 @@
+import whisper
+import os
+import json
+import torchaudio
+import argparse
+import torch
+from tqdm import tqdm
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--whisper_size", default="large")
+    args = parser.parse_args()
+    #assert (torch.cuda.is_available()), "Please enable GPU in order to run Whisper!"
+    model = whisper.load_model(args.whisper_size)
+    parent_dir = "./custom_character_voice/"
+    speaker_names = list(os.walk(parent_dir))[0][1]
+    speaker_annos = []
+    total_files = sum([len(files) for r, d, files in os.walk(parent_dir)])
+    # resample audios
+    # 2023/4/21: Get the target sampling rate
+    with open("./configs/amitaro_jp_base.json", 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+    target_sr = hps['data']['sampling_rate']
+    processed_files = 0
+    for speaker in speaker_names:
+        filelist = (list(os.walk(parent_dir + speaker))[0][2])
+        for i, wavfile in tqdm(enumerate(filelist), desc="Processing Audio:", total=len(filelist)):
+            # try to load file as audio
+            if wavfile.startswith("processed_"):
+                continue
+            try:
+                wav, sr = torchaudio.load(parent_dir + speaker + "/" + wavfile, frame_offset=0, num_frames=-1, normalize=True,
+                                          channels_first=True)
+                wav = wav.mean(dim=0).unsqueeze(0)
+                if sr != target_sr:
+                    wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sr)(wav)
+                if wav.shape[1] / sr > 20:
+                    print(f"{wavfile} too long, ignoring\n")
+                save_path = parent_dir + speaker + "/" + f"processed_{i}.wav"
+                torchaudio.save(save_path, wav, target_sr, channels_first=True)
+                # transcribe text
+                #lang, text = transcribe_one(save_path)
+
+                audio = whisper.load_audio(save_path)
+                audio = whisper.pad_or_trim(audio)
+
+                # make log-Mel spectrogram and move to the same device as the model
+                mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+                options = whisper.DecodingOptions(beam_size=5, language="ja", fp16 = False)
+                result = whisper.decode(model, mel, options)
+
+                text = "[JA]"+ result.text + "[JA]\n"
+                speaker_annos.append(save_path + "|" + speaker + "|" + text)
+
+                processed_files += 1
+            #print(f"Processed: {processed_files}/{total_files}")
+            except:
+                print(f"Error occurred: {wavfile}")
+                continue
+
+    # # clean annotation
+    # import argparse
+    # import text
+    # from utils import load_filepaths_and_text
+    # for i, line in enumerate(speaker_annos):
+    #     path, sid, txt = line.split("|")
+    #     cleaned_text = text._clean_text(txt, ["cjke_cleaners2"])
+    #     cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+    #     speaker_annos[i] = path + "|" + sid + "|" + cleaned_text
+    # write into annotation
+    if len(speaker_annos) == 0:
+        print("Warning: no short audios found, this IS expected if you have only uploaded long audios, videos or video links.")
+        print("this IS NOT expected if you have uploaded a zip file of short audios. Please check your file structure or make sure your audio language is supported.")
+    with open("short_character_anno.txt", 'w', encoding='utf-8') as f:
+        for line in speaker_annos:
+            f.write(line)
+
+    # import json
+    # # generate new config
+    # with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+    #     hps = json.load(f)
+    # # modify n_speakers
+    # hps['data']["n_speakers"] = 1000 + len(speaker2id)
+    # # add speaker names
+    # for speaker in speaker_names:
+    #     hps['speakers'][speaker] = speaker2id[speaker]
+    # # save modified config
+    # with open("./configs/modified_finetune_speaker.json", 'w', encoding='utf-8') as f:
+    #     json.dump(hps, f, indent=2)
+    # print("finished")
diff --git a/scripts/video2audio.py b/scripts/video2audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..db50a5c6b62c4c1faea5fefbb078f16aa9bb7fa3
--- /dev/null
+++ b/scripts/video2audio.py
@@ -0,0 +1,27 @@
+import os
+from concurrent.futures import ThreadPoolExecutor
+
+from moviepy.editor import AudioFileClip
+
+video_dir = "./video_data/"
+audio_dir = "./raw_audio/"
+filelist = list(os.walk(video_dir))[0][2]
+
+
+def generate_infos():
+    videos = []
+    for file in filelist:
+        if file.endswith(".mp4"):
+            videos.append(file)
+    return videos
+
+
+def clip_file(file):
+    my_audio_clip = AudioFileClip(video_dir + file)
+    my_audio_clip.write_audiofile(audio_dir + file.rstrip(".mp4") + ".wav")
+
+
+if __name__ == "__main__":
+    infos = generate_infos()
+    with ThreadPoolExecutor(max_workers=os.cpu_count()) as executor:
+        executor.map(clip_file, infos)
diff --git a/scripts/voice_upload.py b/scripts/voice_upload.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c825a933a7970e17e57c381b59a5fc4e06ea569
--- /dev/null
+++ b/scripts/voice_upload.py
@@ -0,0 +1,28 @@
+from google.colab import files
+import shutil
+import os
+import argparse
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--type", type=str, required=True, help="type of file to upload")
+    args = parser.parse_args()
+    file_type = args.type
+
+    basepath = os.getcwd()
+    uploaded = files.upload() # 上传文件
+    assert(file_type in ['zip', 'audio', 'video'])
+    if file_type == "zip":
+        upload_path = "./custom_character_voice/"
+        for filename in uploaded.keys():
+            #将上传的文件移动到指定的位置上
+            shutil.move(os.path.join(basepath, filename), os.path.join(upload_path, "custom_character_voice.zip"))
+    elif file_type == "audio":
+        upload_path = "./raw_audio/"
+        for filename in uploaded.keys():
+            #将上传的文件移动到指定的位置上
+            shutil.move(os.path.join(basepath, filename), os.path.join(upload_path, filename))
+    elif file_type == "video":
+        upload_path = "./video_data/"
+        for filename in uploaded.keys():
+            # 将上传的文件移动到指定的位置上
+            shutil.move(os.path.join(basepath, filename), os.path.join(upload_path, filename))
\ No newline at end of file
diff --git a/short_audio_transcribe.py b/short_audio_transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..68f7295f5ece16fceb75a96bd0c453bf3aa67558
--- /dev/null
+++ b/short_audio_transcribe.py
@@ -0,0 +1,91 @@
+import whisper
+import os
+import json
+import torchaudio
+import argparse
+import torch
+from tqdm import tqdm
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--whisper_size", default="large")
+    args = parser.parse_args()
+    #assert (torch.cuda.is_available()), "Please enable GPU in order to run Whisper!"
+    model = whisper.load_model(args.whisper_size, device="cpu")
+    parent_dir = "./custom_character_voice/"
+    speaker_names = list(os.walk(parent_dir))[0][1]
+    speaker_annos = []
+    total_files = sum([len(files) for r, d, files in os.walk(parent_dir)])
+    # resample audios
+    # 2023/4/21: Get the target sampling rate
+    with open("./configs/amitaro_jp_base.json", 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+    target_sr = hps['data']['sampling_rate']
+    processed_files = 0
+    for speaker in speaker_names:
+        filelist = (list(os.walk(parent_dir + speaker))[0][2])
+        for i, wavfile in tqdm(enumerate(filelist), desc="Processing Audio:", total=len(filelist)):
+            # try to load file as audio
+            if wavfile.startswith("processed_"):
+                continue
+            #try:
+            wav, sr = torchaudio.load(parent_dir + speaker + "/" + wavfile, frame_offset=0, num_frames=-1, normalize=True,
+                                      channels_first=True)
+            wav = wav.mean(dim=0).unsqueeze(0)
+            if sr != target_sr:
+                wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sr)(wav)
+            if wav.shape[1] / sr > 20:
+                print(f"{wavfile} too long, ignoring\n")
+            save_path = parent_dir + speaker + "/" + f"processed_{i}.wav"
+            torchaudio.save(save_path, wav, target_sr, channels_first=True)
+            # transcribe text
+            #lang, text = transcribe_one(save_path)
+
+            audio = whisper.load_audio(save_path)
+            audio = whisper.pad_or_trim(audio)
+
+            # make log-Mel spectrogram and move to the same device as the model
+            mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+            options = whisper.DecodingOptions(beam_size=5, language="ja", fp16 = False)
+            result = whisper.decode(model, mel, options)
+
+            text = "[JA]"+ result.text + "[JA]\n"
+            speaker_annos.append(save_path + "|" + speaker + "|" + text)
+
+            processed_files += 1
+            #print(f"Processed: {processed_files}/{total_files}")
+            #except:
+            #    print(f"Error occurred: {wavfile}")
+            #    continue
+
+    # # clean annotation
+    # import argparse
+    # import text
+    # from utils import load_filepaths_and_text
+    # for i, line in enumerate(speaker_annos):
+    #     path, sid, txt = line.split("|")
+    #     cleaned_text = text._clean_text(txt, ["cjke_cleaners2"])
+    #     cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+    #     speaker_annos[i] = path + "|" + sid + "|" + cleaned_text
+    # write into annotation
+    if len(speaker_annos) == 0:
+        print("Warning: no short audios found, this IS expected if you have only uploaded long audios, videos or video links.")
+        print("this IS NOT expected if you have uploaded a zip file of short audios. Please check your file structure or make sure your audio language is supported.")
+    with open("short_character_anno.txt", 'w', encoding='utf-8') as f:
+        for line in speaker_annos:
+            f.write(line)
+
+    # import json
+    # # generate new config
+    # with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+    #     hps = json.load(f)
+    # # modify n_speakers
+    # hps['data']["n_speakers"] = 1000 + len(speaker2id)
+    # # add speaker names
+    # for speaker in speaker_names:
+    #     hps['speakers'][speaker] = speaker2id[speaker]
+    # # save modified config
+    # with open("./configs/modified_finetune_speaker.json", 'w', encoding='utf-8') as f:
+    #     json.dump(hps, f, indent=2)
+    # print("finished")
diff --git a/short_character_anno.txt b/short_character_anno.txt
new file mode 100644
index 0000000000000000000000000000000000000000..95acb7d7217b521ea22c4fd2124eabeda7ffaccc
--- /dev/null
+++ b/short_character_anno.txt
@@ -0,0 +1,76 @@
+./custom_character_voice/amitaro/processed_0.wav|amitaro|[JA]一件落着…かな?[JA]
+./custom_character_voice/amitaro/processed_1.wav|amitaro|[JA]へーすっごーい[JA]
+./custom_character_voice/amitaro/processed_2.wav|amitaro|[JA]あなたがいないと私…[JA]
+./custom_character_voice/amitaro/processed_3.wav|amitaro|[JA]ご注文はお決まりですか?[JA]
+./custom_character_voice/amitaro/processed_4.wav|amitaro|[JA]ど、どうしたらいいかな?[JA]
+./custom_character_voice/amitaro/processed_5.wav|amitaro|[JA]はーい!大丈夫ですよー![JA]
+./custom_character_voice/amitaro/processed_6.wav|amitaro|[JA]えっと、つまり…[JA]
+./custom_character_voice/amitaro/processed_7.wav|amitaro|[JA]みなさんおつかれさまでした[JA]
+./custom_character_voice/amitaro/processed_8.wav|amitaro|[JA]バックしまーすお兄ちゃん、お姉ちゃん危ないから離れててね[JA]
+./custom_character_voice/amitaro/processed_9.wav|amitaro|[JA]だってあんなに頑張ってきたのに[JA]
+./custom_character_voice/amitaro/processed_10.wav|amitaro|[JA]右に曲がります。ご注意ください。[JA]
+./custom_character_voice/amitaro/processed_11.wav|amitaro|[JA]あっつい エアコンつけるよ[JA]
+./custom_character_voice/amitaro/processed_12.wav|amitaro|[JA]いただきます[JA]
+./custom_character_voice/amitaro/processed_13.wav|amitaro|[JA]あれを…こうして…あっちが…こうだから…[JA]
+./custom_character_voice/amitaro/processed_14.wav|amitaro|[JA]いってらっしゃいませ、ご主人様[JA]
+./custom_character_voice/amitaro/processed_16.wav|amitaro|[JA]緊急車両が近くにいるよ[JA]
+./custom_character_voice/amitaro/processed_17.wav|amitaro|[JA]今度こそできるよ[JA]
+./custom_character_voice/amitaro/processed_18.wav|amitaro|[JA]はーい、どうぞー[JA]
+./custom_character_voice/amitaro/processed_19.wav|amitaro|[JA]間違っているのはどれだ?[JA]
+./custom_character_voice/amitaro/processed_20.wav|amitaro|[JA]あぶなかった[JA]
+./custom_character_voice/amitaro/processed_21.wav|amitaro|[JA]4名様ご来店[JA]
+./custom_character_voice/amitaro/processed_22.wav|amitaro|[JA]道の駅があるよ、休憩しませんか?[JA]
+./custom_character_voice/amitaro/processed_23.wav|amitaro|[JA]どなたかいらっしゃいませんか?[JA]
+./custom_character_voice/amitaro/processed_24.wav|amitaro|[JA]たまにはかまってほしいなぁ[JA]
+./custom_character_voice/amitaro/processed_25.wav|amitaro|[JA]インターネットにつながりません[JA]
+./custom_character_voice/amitaro/processed_26.wav|amitaro|[JA]大丈夫だよ最初からうまくいく人なんていないんだから[JA]
+./custom_character_voice/amitaro/processed_27.wav|amitaro|[JA]はーい!開いてますよー![JA]
+./custom_character_voice/amitaro/processed_28.wav|amitaro|[JA]車が曲がります。ご注意ください。[JA]
+./custom_character_voice/amitaro/processed_29.wav|amitaro|[JA]コハルネアミ 歌います[JA]
+./custom_character_voice/amitaro/processed_30.wav|amitaro|[JA]およそ200メートル先を左方向です。[JA]
+./custom_character_voice/amitaro/processed_31.wav|amitaro|[JA]頑張りすぎは良くないですよ[JA]
+./custom_character_voice/amitaro/processed_32.wav|amitaro|[JA]じゃんけんぽん![JA]
+./custom_character_voice/amitaro/processed_33.wav|amitaro|[JA]次の中から間違っているものを選んでね[JA]
+./custom_character_voice/amitaro/processed_34.wav|amitaro|[JA]ごめんなさーい[JA]
+./custom_character_voice/amitaro/processed_35.wav|amitaro|[JA]声の素材を作った人アミ太郎[JA]
+./custom_character_voice/amitaro/processed_36.wav|amitaro|[JA]ひどいよぉ[JA]
+./custom_character_voice/amitaro/processed_37.wav|amitaro|[JA]左に曲がります。ご注意ください。[JA]
+./custom_character_voice/amitaro/processed_38.wav|amitaro|[JA]がんばるのもほどほどにしてくださいね[JA]
+./custom_character_voice/amitaro/processed_39.wav|amitaro|[JA]生き返るぅ…[JA]
+./custom_character_voice/amitaro/processed_40.wav|amitaro|[JA]起動しました 今日も安全運転よろしくお願いします[JA]
+./custom_character_voice/amitaro/processed_41.wav|amitaro|[JA]今日はどこへ行きますか?[JA]
+./custom_character_voice/amitaro/processed_42.wav|amitaro|[JA]遊んでくれてありがとう[JA]
+./custom_character_voice/amitaro/processed_43.wav|amitaro|[JA]これでとどめだぁ[JA]
+./custom_character_voice/amitaro/processed_44.wav|amitaro|[JA]このままじゃやられちゃうかも[JA]
+./custom_character_voice/amitaro/processed_45.wav|amitaro|[JA]こんなのってないよ[JA]
+./custom_character_voice/amitaro/processed_46.wav|amitaro|[JA]この音声は、アミタロの声素材工房がお届けしました。[JA]
+./custom_character_voice/amitaro/processed_47.wav|amitaro|[JA]どなたかいらっしゃいますか?[JA]
+./custom_character_voice/amitaro/processed_48.wav|amitaro|[JA]ご注文は以上でよろしいですか?[JA]
+./custom_character_voice/amitaro/processed_49.wav|amitaro|[JA]ごちそうさまでした[JA]
+./custom_character_voice/amitaro/processed_50.wav|amitaro|[JA]はーい、注目ー![JA]
+./custom_character_voice/amitaro/processed_51.wav|amitaro|[JA]あ、怒ってる?[JA]
+./custom_character_voice/amitaro/processed_52.wav|amitaro|[JA]このあたりでちょっと休憩しませんか?[JA]
+./custom_character_voice/amitaro/processed_53.wav|amitaro|[JA]諦めないでもう一回やってみよう!ねっ![JA]
+./custom_character_voice/amitaro/processed_54.wav|amitaro|[JA]早く起きて[JA]
+./custom_character_voice/amitaro/processed_55.wav|amitaro|[JA]あらね[JA]
+./custom_character_voice/amitaro/processed_56.wav|amitaro|[JA]でもでも大丈夫だよ これから何度だって挑戦すればいいんだから[JA]
+./custom_character_voice/amitaro/processed_57.wav|amitaro|[JA]この中だと…[JA]
+./custom_character_voice/amitaro/processed_58.wav|amitaro|[JA]だって、あんなに頑張ったじゃない[JA]
+./custom_character_voice/amitaro/processed_59.wav|amitaro|[JA]少しだけ休憩しませんか[JA]
+./custom_character_voice/amitaro/processed_60.wav|amitaro|[JA]これもくらえ![JA]
+./custom_character_voice/amitaro/processed_61.wav|amitaro|[JA]えっと、だから…[JA]
+./custom_character_voice/amitaro/processed_62.wav|amitaro|[JA]ごめん、怒らないで[JA]
+./custom_character_voice/amitaro/processed_63.wav|amitaro|[JA]勘弁してよ[JA]
+./custom_character_voice/amitaro/processed_64.wav|amitaro|[JA]もう意地悪[JA]
+./custom_character_voice/amitaro/processed_65.wav|amitaro|[JA]どうかなぁ?[JA]
+./custom_character_voice/amitaro/processed_66.wav|amitaro|[JA]このような結果になりました[JA]
+./custom_character_voice/amitaro/processed_67.wav|amitaro|[JA]こんなんでいいのかなぁ[JA]
+./custom_character_voice/amitaro/processed_68.wav|amitaro|[JA]うん、初めてなのに上出来だよ[JA]
+./custom_character_voice/amitaro/processed_69.wav|amitaro|[JA]ど、どうしよう…[JA]
+./custom_character_voice/amitaro/processed_70.wav|amitaro|[JA]3、2、1、0[JA]
+./custom_character_voice/amitaro/processed_71.wav|amitaro|[JA]あ、あれ?もう終わり?[JA]
+./custom_character_voice/amitaro/processed_72.wav|amitaro|[JA]秋の交通安全運動週間です[JA]
+./custom_character_voice/amitaro/processed_73.wav|amitaro|[JA]そろそろ本当に休んでください[JA]
+./custom_character_voice/amitaro/processed_74.wav|amitaro|[JA]わわわわわわわ![JA]
+./custom_character_voice/amitaro/processed_75.wav|amitaro|[JA]あんまり難しく考えすぎるといろいろ大変だしね しっかり反省したらパパッと次行こう[JA]
+./custom_character_voice/amitaro/processed_76.wav|amitaro|[JA]だからこれがこうでこういうことだよね[JA]
diff --git a/text/LICENSE b/text/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..91483e2db24fbcf6e03a6d0d8ce3c5fdf2ba0301
--- /dev/null
+++ b/text/LICENSE
@@ -0,0 +1,19 @@
+Copyright (c) 2017 Keith Ito
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
diff --git a/text/__init__.py b/text/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e6798ed7f69b50aa9f8dd1d1013c4266d0866105
--- /dev/null
+++ b/text/__init__.py
@@ -0,0 +1,60 @@
+""" from https://github.com/keithito/tacotron """
+from text import cleaners
+from text.symbols import symbols
+
+
+# Mappings from symbol to numeric ID and vice versa:
+_symbol_to_id = {s: i for i, s in enumerate(symbols)}
+_id_to_symbol = {i: s for i, s in enumerate(symbols)}
+
+
+def text_to_sequence(text, symbols, cleaner_names):
+  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
+    Args:
+      text: string to convert to a sequence
+      cleaner_names: names of the cleaner functions to run the text through
+    Returns:
+      List of integers corresponding to the symbols in the text
+  '''
+  sequence = []
+  symbol_to_id = {s: i for i, s in enumerate(symbols)}
+  clean_text = _clean_text(text, cleaner_names)
+  print(clean_text)
+  print(f" length:{len(clean_text)}")
+  for symbol in clean_text:
+    if symbol not in symbol_to_id.keys():
+      continue
+    symbol_id = symbol_to_id[symbol]
+    sequence += [symbol_id]
+  print(f" length:{len(sequence)}")
+  return sequence
+
+
+def cleaned_text_to_sequence(cleaned_text, symbols):
+  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
+    Args:
+      text: string to convert to a sequence
+    Returns:
+      List of integers corresponding to the symbols in the text
+  '''
+  symbol_to_id = {s: i for i, s in enumerate(symbols)}
+  sequence = [symbol_to_id[symbol] for symbol in cleaned_text if symbol in symbol_to_id.keys()]
+  return sequence
+
+
+def sequence_to_text(sequence):
+  '''Converts a sequence of IDs back to a string'''
+  result = ''
+  for symbol_id in sequence:
+    s = _id_to_symbol[symbol_id]
+    result += s
+  return result
+
+
+def _clean_text(text, cleaner_names):
+  for name in cleaner_names:
+    cleaner = getattr(cleaners, name)
+    if not cleaner:
+      raise Exception('Unknown cleaner: %s' % name)
+    text = cleaner(text)
+  return text
diff --git a/text/cantonese.py b/text/cantonese.py
new file mode 100644
index 0000000000000000000000000000000000000000..4edf7e5d557dc480ba1e105ba9948f85b0861a1c
--- /dev/null
+++ b/text/cantonese.py
@@ -0,0 +1,59 @@
+import re
+import cn2an
+import opencc
+
+
+converter = opencc.OpenCC('jyutjyu')
+
+# List of (Latin alphabet, ipa) pairs:
+_latin_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('A', 'ei˥'),
+    ('B', 'biː˥'),
+    ('C', 'siː˥'),
+    ('D', 'tiː˥'),
+    ('E', 'iː˥'),
+    ('F', 'e˥fuː˨˩'),
+    ('G', 'tsiː˥'),
+    ('H', 'ɪk̚˥tsʰyː˨˩'),
+    ('I', 'ɐi˥'),
+    ('J', 'tsei˥'),
+    ('K', 'kʰei˥'),
+    ('L', 'e˥llou˨˩'),
+    ('M', 'ɛːm˥'),
+    ('N', 'ɛːn˥'),
+    ('O', 'ou˥'),
+    ('P', 'pʰiː˥'),
+    ('Q', 'kʰiːu˥'),
+    ('R', 'aː˥lou˨˩'),
+    ('S', 'ɛː˥siː˨˩'),
+    ('T', 'tʰiː˥'),
+    ('U', 'juː˥'),
+    ('V', 'wiː˥'),
+    ('W', 'tʊk̚˥piː˥juː˥'),
+    ('X', 'ɪk̚˥siː˨˩'),
+    ('Y', 'waːi˥'),
+    ('Z', 'iː˨sɛːt̚˥')
+]]
+
+
+def number_to_cantonese(text):
+    return re.sub(r'\d+(?:\.?\d+)?', lambda x: cn2an.an2cn(x.group()), text)
+
+
+def latin_to_ipa(text):
+    for regex, replacement in _latin_to_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def cantonese_to_ipa(text):
+    text = number_to_cantonese(text.upper())
+    text = converter.convert(text).replace('-','').replace('$',' ')
+    text = re.sub(r'[A-Z]', lambda x: latin_to_ipa(x.group())+' ', text)
+    text = re.sub(r'[、；：]', '，', text)
+    text = re.sub(r'\s*，\s*', ', ', text)
+    text = re.sub(r'\s*。\s*', '. ', text)
+    text = re.sub(r'\s*？\s*', '? ', text)
+    text = re.sub(r'\s*！\s*', '! ', text)
+    text = re.sub(r'\s*$', '', text)
+    return text
diff --git a/text/cleaners.py b/text/cleaners.py
new file mode 100644
index 0000000000000000000000000000000000000000..adc6fd88f8fc87b1d1d8b8a6d7970cd214b65b6f
--- /dev/null
+++ b/text/cleaners.py
@@ -0,0 +1,129 @@
+import re
+from text.japanese import japanese_to_romaji_with_accent, japanese_to_ipa, japanese_to_ipa2, japanese_to_ipa3
+from text.korean import latin_to_hangul, number_to_hangul, divide_hangul, korean_to_lazy_ipa, korean_to_ipa
+from text.mandarin import number_to_chinese, chinese_to_bopomofo, latin_to_bopomofo, chinese_to_romaji, chinese_to_lazy_ipa, chinese_to_ipa, chinese_to_ipa2
+from text.sanskrit import devanagari_to_ipa
+from text.english import english_to_lazy_ipa, english_to_ipa2, english_to_lazy_ipa2
+from text.thai import num_to_thai, latin_to_thai
+# from text.shanghainese import shanghainese_to_ipa
+# from text.cantonese import cantonese_to_ipa
+# from text.ngu_dialect import ngu_dialect_to_ipa
+
+
+def japanese_cleaners(text):
+    text = japanese_to_romaji_with_accent(text)
+    text = re.sub(r'([A-Za-z])$', r'\1.', text)
+    return text
+
+
+def japanese_cleaners2(text):
+    return japanese_cleaners(text).replace('ts', 'ʦ').replace('...', '…')
+
+
+def korean_cleaners(text):
+    '''Pipeline for Korean text'''
+    text = latin_to_hangul(text)
+    text = number_to_hangul(text)
+    text = divide_hangul(text)
+    text = re.sub(r'([\u3131-\u3163])$', r'\1.', text)
+    return text
+
+
+def chinese_cleaners(text):
+    '''Pipeline for Chinese text'''
+    text = text.replace("[ZH]", "")
+    text = number_to_chinese(text)
+    text = chinese_to_bopomofo(text)
+    text = latin_to_bopomofo(text)
+    text = re.sub(r'([ˉˊˇˋ˙])$', r'\1。', text)
+    return text
+
+
+def zh_ja_mixture_cleaners(text):
+    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
+                  lambda x: chinese_to_romaji(x.group(1))+' ', text)
+    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_romaji_with_accent(
+        x.group(1)).replace('ts', 'ʦ').replace('u', 'ɯ').replace('...', '…')+' ', text)
+    text = re.sub(r'\s+$', '', text)
+    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+    return text
+
+
+def sanskrit_cleaners(text):
+    text = text.replace('॥', '।').replace('ॐ', 'ओम्')
+    text = re.sub(r'([^।])$', r'\1।', text)
+    return text
+
+
+def cjks_cleaners(text):
+    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
+                  lambda x: chinese_to_lazy_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[JA\](.*?)\[JA\]',
+                  lambda x: japanese_to_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[KO\](.*?)\[KO\]',
+                  lambda x: korean_to_lazy_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[SA\](.*?)\[SA\]',
+                  lambda x: devanagari_to_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[EN\](.*?)\[EN\]',
+                  lambda x: english_to_lazy_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\s+$', '', text)
+    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+    return text
+
+
+def cjke_cleaners(text):
+    text = re.sub(r'\[ZH\](.*?)\[ZH\]', lambda x: chinese_to_lazy_ipa(x.group(1)).replace(
+        'ʧ', 'tʃ').replace('ʦ', 'ts').replace('ɥan', 'ɥæn')+' ', text)
+    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_ipa(x.group(1)).replace('ʧ', 'tʃ').replace(
+        'ʦ', 'ts').replace('ɥan', 'ɥæn').replace('ʥ', 'dz')+' ', text)
+    text = re.sub(r'\[KO\](.*?)\[KO\]',
+                  lambda x: korean_to_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: english_to_ipa2(x.group(1)).replace('ɑ', 'a').replace(
+        'ɔ', 'o').replace('ɛ', 'e').replace('ɪ', 'i').replace('ʊ', 'u')+' ', text)
+    text = re.sub(r'\s+$', '', text)
+    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+    return text
+
+
+def cjke_cleaners2(text):
+    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
+                  lambda x: chinese_to_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[JA\](.*?)\[JA\]',
+                  lambda x: japanese_to_ipa2(x.group(1))+' ', text)
+    text = re.sub(r'\[KO\](.*?)\[KO\]',
+                  lambda x: korean_to_ipa(x.group(1))+' ', text)
+    text = re.sub(r'\[EN\](.*?)\[EN\]',
+                  lambda x: english_to_ipa2(x.group(1))+' ', text)
+    text = re.sub(r'\s+$', '', text)
+    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+    return text
+
+
+def thai_cleaners(text):
+    text = num_to_thai(text)
+    text = latin_to_thai(text)
+    return text
+
+
+# def shanghainese_cleaners(text):
+#     text = shanghainese_to_ipa(text)
+#     text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+#     return text
+
+
+# def chinese_dialect_cleaners(text):
+#     text = re.sub(r'\[ZH\](.*?)\[ZH\]',
+#                   lambda x: chinese_to_ipa2(x.group(1))+' ', text)
+#     text = re.sub(r'\[JA\](.*?)\[JA\]',
+#                   lambda x: japanese_to_ipa3(x.group(1)).replace('Q', 'ʔ')+' ', text)
+#     text = re.sub(r'\[SH\](.*?)\[SH\]', lambda x: shanghainese_to_ipa(x.group(1)).replace('1', '˥˧').replace('5',
+#                   '˧˧˦').replace('6', '˩˩˧').replace('7', '˥').replace('8', '˩˨').replace('ᴀ', 'ɐ').replace('ᴇ', 'e')+' ', text)
+#     text = re.sub(r'\[GD\](.*?)\[GD\]',
+#                   lambda x: cantonese_to_ipa(x.group(1))+' ', text)
+#     text = re.sub(r'\[EN\](.*?)\[EN\]',
+#                   lambda x: english_to_lazy_ipa2(x.group(1))+' ', text)
+#     text = re.sub(r'\[([A-Z]{2})\](.*?)\[\1\]', lambda x: ngu_dialect_to_ipa(x.group(2), x.group(
+#         1)).replace('ʣ', 'dz').replace('ʥ', 'dʑ').replace('ʦ', 'ts').replace('ʨ', 'tɕ')+' ', text)
+#     text = re.sub(r'\s+$', '', text)
+#     text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
+#     return text
diff --git a/text/english.py b/text/english.py
new file mode 100644
index 0000000000000000000000000000000000000000..736a53a7bc66cfdd776aa1fa01439f1e6e46f1c9
--- /dev/null
+++ b/text/english.py
@@ -0,0 +1,188 @@
+""" from https://github.com/keithito/tacotron """
+
+'''
+Cleaners are transformations that run over the input text at both training and eval time.
+
+Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
+hyperparameter. Some cleaners are English-specific. You'll typically want to use:
+  1. "english_cleaners" for English text
+  2. "transliteration_cleaners" for non-English text that can be transliterated to ASCII using
+     the Unidecode library (https://pypi.python.org/pypi/Unidecode)
+  3. "basic_cleaners" if you do not want to transliterate (in this case, you should also update
+     the symbols in symbols.py to match your data).
+'''
+
+
+# Regular expression matching whitespace:
+
+
+import re
+import inflect
+from unidecode import unidecode
+import eng_to_ipa as ipa
+_inflect = inflect.engine()
+_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
+_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
+_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
+_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
+_ordinal_re = re.compile(r'[0-9]+(st|nd|rd|th)')
+_number_re = re.compile(r'[0-9]+')
+
+# List of (regular expression, replacement) pairs for abbreviations:
+_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('mrs', 'misess'),
+    ('mr', 'mister'),
+    ('dr', 'doctor'),
+    ('st', 'saint'),
+    ('co', 'company'),
+    ('jr', 'junior'),
+    ('maj', 'major'),
+    ('gen', 'general'),
+    ('drs', 'doctors'),
+    ('rev', 'reverend'),
+    ('lt', 'lieutenant'),
+    ('hon', 'honorable'),
+    ('sgt', 'sergeant'),
+    ('capt', 'captain'),
+    ('esq', 'esquire'),
+    ('ltd', 'limited'),
+    ('col', 'colonel'),
+    ('ft', 'fort'),
+]]
+
+
+# List of (ipa, lazy ipa) pairs:
+_lazy_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('r', 'ɹ'),
+    ('æ', 'e'),
+    ('ɑ', 'a'),
+    ('ɔ', 'o'),
+    ('ð', 'z'),
+    ('θ', 's'),
+    ('ɛ', 'e'),
+    ('ɪ', 'i'),
+    ('ʊ', 'u'),
+    ('ʒ', 'ʥ'),
+    ('ʤ', 'ʥ'),
+    ('ˈ', '↓'),
+]]
+
+# List of (ipa, lazy ipa2) pairs:
+_lazy_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('r', 'ɹ'),
+    ('ð', 'z'),
+    ('θ', 's'),
+    ('ʒ', 'ʑ'),
+    ('ʤ', 'dʑ'),
+    ('ˈ', '↓'),
+]]
+
+# List of (ipa, ipa2) pairs
+_ipa_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('r', 'ɹ'),
+    ('ʤ', 'dʒ'),
+    ('ʧ', 'tʃ')
+]]
+
+
+def expand_abbreviations(text):
+    for regex, replacement in _abbreviations:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def collapse_whitespace(text):
+    return re.sub(r'\s+', ' ', text)
+
+
+def _remove_commas(m):
+    return m.group(1).replace(',', '')
+
+
+def _expand_decimal_point(m):
+    return m.group(1).replace('.', ' point ')
+
+
+def _expand_dollars(m):
+    match = m.group(1)
+    parts = match.split('.')
+    if len(parts) > 2:
+        return match + ' dollars'  # Unexpected format
+    dollars = int(parts[0]) if parts[0] else 0
+    cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
+    if dollars and cents:
+        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
+        cent_unit = 'cent' if cents == 1 else 'cents'
+        return '%s %s, %s %s' % (dollars, dollar_unit, cents, cent_unit)
+    elif dollars:
+        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
+        return '%s %s' % (dollars, dollar_unit)
+    elif cents:
+        cent_unit = 'cent' if cents == 1 else 'cents'
+        return '%s %s' % (cents, cent_unit)
+    else:
+        return 'zero dollars'
+
+
+def _expand_ordinal(m):
+    return _inflect.number_to_words(m.group(0))
+
+
+def _expand_number(m):
+    num = int(m.group(0))
+    if num > 1000 and num < 3000:
+        if num == 2000:
+            return 'two thousand'
+        elif num > 2000 and num < 2010:
+            return 'two thousand ' + _inflect.number_to_words(num % 100)
+        elif num % 100 == 0:
+            return _inflect.number_to_words(num // 100) + ' hundred'
+        else:
+            return _inflect.number_to_words(num, andword='', zero='oh', group=2).replace(', ', ' ')
+    else:
+        return _inflect.number_to_words(num, andword='')
+
+
+def normalize_numbers(text):
+    text = re.sub(_comma_number_re, _remove_commas, text)
+    text = re.sub(_pounds_re, r'\1 pounds', text)
+    text = re.sub(_dollars_re, _expand_dollars, text)
+    text = re.sub(_decimal_number_re, _expand_decimal_point, text)
+    text = re.sub(_ordinal_re, _expand_ordinal, text)
+    text = re.sub(_number_re, _expand_number, text)
+    return text
+
+
+def mark_dark_l(text):
+    return re.sub(r'l([^aeiouæɑɔəɛɪʊ ]*(?: |$))', lambda x: 'ɫ'+x.group(1), text)
+
+
+def english_to_ipa(text):
+    text = unidecode(text).lower()
+    text = expand_abbreviations(text)
+    text = normalize_numbers(text)
+    phonemes = ipa.convert(text)
+    phonemes = collapse_whitespace(phonemes)
+    return phonemes
+
+
+def english_to_lazy_ipa(text):
+    text = english_to_ipa(text)
+    for regex, replacement in _lazy_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def english_to_ipa2(text):
+    text = english_to_ipa(text)
+    text = mark_dark_l(text)
+    for regex, replacement in _ipa_to_ipa2:
+        text = re.sub(regex, replacement, text)
+    return text.replace('...', '…')
+
+
+def english_to_lazy_ipa2(text):
+    text = english_to_ipa(text)
+    for regex, replacement in _lazy_ipa2:
+        text = re.sub(regex, replacement, text)
+    return text
diff --git a/text/japanese.py b/text/japanese.py
new file mode 100644
index 0000000000000000000000000000000000000000..7430cec6df2a17460325962dfd5479fa836cfc21
--- /dev/null
+++ b/text/japanese.py
@@ -0,0 +1,153 @@
+import re
+from unidecode import unidecode
+import pyopenjtalk
+
+
+# Regular expression matching Japanese without punctuation marks:
+_japanese_characters = re.compile(
+    r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
+
+# Regular expression matching non-Japanese characters or punctuation marks:
+_japanese_marks = re.compile(
+    r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
+
+# List of (symbol, Japanese) pairs for marks:
+_symbols_to_japanese = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('％', 'パーセント')
+]]
+
+# List of (romaji, ipa) pairs for marks:
+_romaji_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('ts', 'ʦ'),
+    ('u', 'ɯ'),
+    ('j', 'ʥ'),
+    ('y', 'j'),
+    ('ni', 'n^i'),
+    ('nj', 'n^'),
+    ('hi', 'çi'),
+    ('hj', 'ç'),
+    ('f', 'ɸ'),
+    ('I', 'i*'),
+    ('U', 'ɯ*'),
+    ('r', 'ɾ')
+]]
+
+# List of (romaji, ipa2) pairs for marks:
+_romaji_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('u', 'ɯ'),
+    ('ʧ', 'tʃ'),
+    ('j', 'dʑ'),
+    ('y', 'j'),
+    ('ni', 'n^i'),
+    ('nj', 'n^'),
+    ('hi', 'çi'),
+    ('hj', 'ç'),
+    ('f', 'ɸ'),
+    ('I', 'i*'),
+    ('U', 'ɯ*'),
+    ('r', 'ɾ')
+]]
+
+# List of (consonant, sokuon) pairs:
+_real_sokuon = [(re.compile('%s' % x[0]), x[1]) for x in [
+    (r'Q([↑↓]*[kg])', r'k#\1'),
+    (r'Q([↑↓]*[tdjʧ])', r't#\1'),
+    (r'Q([↑↓]*[sʃ])', r's\1'),
+    (r'Q([↑↓]*[pb])', r'p#\1')
+]]
+
+# List of (consonant, hatsuon) pairs:
+_real_hatsuon = [(re.compile('%s' % x[0]), x[1]) for x in [
+    (r'N([↑↓]*[pbm])', r'm\1'),
+    (r'N([↑↓]*[ʧʥj])', r'n^\1'),
+    (r'N([↑↓]*[tdn])', r'n\1'),
+    (r'N([↑↓]*[kg])', r'ŋ\1')
+]]
+
+
+def symbols_to_japanese(text):
+    for regex, replacement in _symbols_to_japanese:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def japanese_to_romaji_with_accent(text):
+    '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
+    text = symbols_to_japanese(text)
+    sentences = re.split(_japanese_marks, text)
+    marks = re.findall(_japanese_marks, text)
+    text = ''
+    for i, sentence in enumerate(sentences):
+        if re.match(_japanese_characters, sentence):
+            if text != '':
+                text += ' '
+            labels = pyopenjtalk.extract_fullcontext(sentence)
+            for n, label in enumerate(labels):
+                phoneme = re.search(r'\-([^\+]*)\+', label).group(1)
+                if phoneme not in ['sil', 'pau']:
+                    text += phoneme.replace('ch', 'ʧ').replace('sh',
+                                                               'ʃ').replace('cl', 'Q')
+                else:
+                    continue
+                # n_moras = int(re.search(r'/F:(\d+)_', label).group(1))
+                a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
+                a2 = int(re.search(r"\+(\d+)\+", label).group(1))
+                a3 = int(re.search(r"\+(\d+)/", label).group(1))
+                if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil', 'pau']:
+                    a2_next = -1
+                else:
+                    a2_next = int(
+                        re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
+                # Accent phrase boundary
+                if a3 == 1 and a2_next == 1:
+                    text += ' '
+                # Falling
+                elif a1 == 0 and a2_next == a2 + 1:
+                    text += '↓'
+                # Rising
+                elif a2 == 1 and a2_next == 2:
+                    text += '↑'
+        if i < len(marks):
+            text += unidecode(marks[i]).replace(' ', '')
+    return text
+
+
+def get_real_sokuon(text):
+    for regex, replacement in _real_sokuon:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def get_real_hatsuon(text):
+    for regex, replacement in _real_hatsuon:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def japanese_to_ipa(text):
+    text = japanese_to_romaji_with_accent(text).replace('...', '…')
+    text = re.sub(
+        r'([aiueo])\1+', lambda x: x.group(0)[0]+'ː'*(len(x.group(0))-1), text)
+    text = get_real_sokuon(text)
+    text = get_real_hatsuon(text)
+    for regex, replacement in _romaji_to_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def japanese_to_ipa2(text):
+    text = japanese_to_romaji_with_accent(text).replace('...', '…')
+    text = get_real_sokuon(text)
+    text = get_real_hatsuon(text)
+    for regex, replacement in _romaji_to_ipa2:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def japanese_to_ipa3(text):
+    text = japanese_to_ipa2(text).replace('n^', 'ȵ').replace(
+        'ʃ', 'ɕ').replace('*', '\u0325').replace('#', '\u031a')
+    text = re.sub(
+        r'([aiɯeo])\1+', lambda x: x.group(0)[0]+'ː'*(len(x.group(0))-1), text)
+    text = re.sub(r'((?:^|\s)(?:ts|tɕ|[kpt]))', r'\1ʰ', text)
+    return text
diff --git a/text/korean.py b/text/korean.py
new file mode 100644
index 0000000000000000000000000000000000000000..d6368c1e43e3dfe7abf4621cf1e70009125bdca9
--- /dev/null
+++ b/text/korean.py
@@ -0,0 +1,210 @@
+import re
+from jamo import h2j, j2hcj
+import ko_pron
+
+
+# This is a list of Korean classifiers preceded by pure Korean numerals.
+_korean_classifiers = '군데 권 개 그루 닢 대 두 마리 모 모금 뭇 발 발짝 방 번 벌 보루 살 수 술 시 쌈 움큼 정 짝 채 척 첩 축 켤레 톨 통'
+
+# List of (hangul, hangul divided) pairs:
+_hangul_divided = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('ㄳ', 'ㄱㅅ'),
+    ('ㄵ', 'ㄴㅈ'),
+    ('ㄶ', 'ㄴㅎ'),
+    ('ㄺ', 'ㄹㄱ'),
+    ('ㄻ', 'ㄹㅁ'),
+    ('ㄼ', 'ㄹㅂ'),
+    ('ㄽ', 'ㄹㅅ'),
+    ('ㄾ', 'ㄹㅌ'),
+    ('ㄿ', 'ㄹㅍ'),
+    ('ㅀ', 'ㄹㅎ'),
+    ('ㅄ', 'ㅂㅅ'),
+    ('ㅘ', 'ㅗㅏ'),
+    ('ㅙ', 'ㅗㅐ'),
+    ('ㅚ', 'ㅗㅣ'),
+    ('ㅝ', 'ㅜㅓ'),
+    ('ㅞ', 'ㅜㅔ'),
+    ('ㅟ', 'ㅜㅣ'),
+    ('ㅢ', 'ㅡㅣ'),
+    ('ㅑ', 'ㅣㅏ'),
+    ('ㅒ', 'ㅣㅐ'),
+    ('ㅕ', 'ㅣㅓ'),
+    ('ㅖ', 'ㅣㅔ'),
+    ('ㅛ', 'ㅣㅗ'),
+    ('ㅠ', 'ㅣㅜ')
+]]
+
+# List of (Latin alphabet, hangul) pairs:
+_latin_to_hangul = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('a', '에이'),
+    ('b', '비'),
+    ('c', '시'),
+    ('d', '디'),
+    ('e', '이'),
+    ('f', '에프'),
+    ('g', '지'),
+    ('h', '에이치'),
+    ('i', '아이'),
+    ('j', '제이'),
+    ('k', '케이'),
+    ('l', '엘'),
+    ('m', '엠'),
+    ('n', '엔'),
+    ('o', '오'),
+    ('p', '피'),
+    ('q', '큐'),
+    ('r', '아르'),
+    ('s', '에스'),
+    ('t', '티'),
+    ('u', '유'),
+    ('v', '브이'),
+    ('w', '더블유'),
+    ('x', '엑스'),
+    ('y', '와이'),
+    ('z', '제트')
+]]
+
+# List of (ipa, lazy ipa) pairs:
+_ipa_to_lazy_ipa = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('t͡ɕ','ʧ'),
+    ('d͡ʑ','ʥ'),
+    ('ɲ','n^'),
+    ('ɕ','ʃ'),
+    ('ʷ','w'),
+    ('ɭ','l`'),
+    ('ʎ','ɾ'),
+    ('ɣ','ŋ'),
+    ('ɰ','ɯ'),
+    ('ʝ','j'),
+    ('ʌ','ə'),
+    ('ɡ','g'),
+    ('\u031a','#'),
+    ('\u0348','='),
+    ('\u031e',''),
+    ('\u0320',''),
+    ('\u0339','')
+]]
+
+
+def latin_to_hangul(text):
+    for regex, replacement in _latin_to_hangul:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def divide_hangul(text):
+    text = j2hcj(h2j(text))
+    for regex, replacement in _hangul_divided:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def hangul_number(num, sino=True):
+    '''Reference https://github.com/Kyubyong/g2pK'''
+    num = re.sub(',', '', num)
+
+    if num == '0':
+        return '영'
+    if not sino and num == '20':
+        return '스무'
+
+    digits = '123456789'
+    names = '일이삼사오육칠팔구'
+    digit2name = {d: n for d, n in zip(digits, names)}
+
+    modifiers = '한 두 세 네 다섯 여섯 일곱 여덟 아홉'
+    decimals = '열 스물 서른 마흔 쉰 예순 일흔 여든 아흔'
+    digit2mod = {d: mod for d, mod in zip(digits, modifiers.split())}
+    digit2dec = {d: dec for d, dec in zip(digits, decimals.split())}
+
+    spelledout = []
+    for i, digit in enumerate(num):
+        i = len(num) - i - 1
+        if sino:
+            if i == 0:
+                name = digit2name.get(digit, '')
+            elif i == 1:
+                name = digit2name.get(digit, '') + '십'
+                name = name.replace('일십', '십')
+        else:
+            if i == 0:
+                name = digit2mod.get(digit, '')
+            elif i == 1:
+                name = digit2dec.get(digit, '')
+        if digit == '0':
+            if i % 4 == 0:
+                last_three = spelledout[-min(3, len(spelledout)):]
+                if ''.join(last_three) == '':
+                    spelledout.append('')
+                    continue
+            else:
+                spelledout.append('')
+                continue
+        if i == 2:
+            name = digit2name.get(digit, '') + '백'
+            name = name.replace('일백', '백')
+        elif i == 3:
+            name = digit2name.get(digit, '') + '천'
+            name = name.replace('일천', '천')
+        elif i == 4:
+            name = digit2name.get(digit, '') + '만'
+            name = name.replace('일만', '만')
+        elif i == 5:
+            name = digit2name.get(digit, '') + '십'
+            name = name.replace('일십', '십')
+        elif i == 6:
+            name = digit2name.get(digit, '') + '백'
+            name = name.replace('일백', '백')
+        elif i == 7:
+            name = digit2name.get(digit, '') + '천'
+            name = name.replace('일천', '천')
+        elif i == 8:
+            name = digit2name.get(digit, '') + '억'
+        elif i == 9:
+            name = digit2name.get(digit, '') + '십'
+        elif i == 10:
+            name = digit2name.get(digit, '') + '백'
+        elif i == 11:
+            name = digit2name.get(digit, '') + '천'
+        elif i == 12:
+            name = digit2name.get(digit, '') + '조'
+        elif i == 13:
+            name = digit2name.get(digit, '') + '십'
+        elif i == 14:
+            name = digit2name.get(digit, '') + '백'
+        elif i == 15:
+            name = digit2name.get(digit, '') + '천'
+        spelledout.append(name)
+    return ''.join(elem for elem in spelledout)
+
+
+def number_to_hangul(text):
+    '''Reference https://github.com/Kyubyong/g2pK'''
+    tokens = set(re.findall(r'(\d[\d,]*)([\uac00-\ud71f]+)', text))
+    for token in tokens:
+        num, classifier = token
+        if classifier[:2] in _korean_classifiers or classifier[0] in _korean_classifiers:
+            spelledout = hangul_number(num, sino=False)
+        else:
+            spelledout = hangul_number(num, sino=True)
+        text = text.replace(f'{num}{classifier}', f'{spelledout}{classifier}')
+    # digit by digit for remaining digits
+    digits = '0123456789'
+    names = '영일이삼사오육칠팔구'
+    for d, n in zip(digits, names):
+        text = text.replace(d, n)
+    return text
+
+
+def korean_to_lazy_ipa(text):
+    text = latin_to_hangul(text)
+    text = number_to_hangul(text)
+    text=re.sub('[\uac00-\ud7af]+',lambda x:ko_pron.romanise(x.group(0),'ipa').split('] ~ [')[0],text)
+    for regex, replacement in _ipa_to_lazy_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def korean_to_ipa(text):
+    text = korean_to_lazy_ipa(text)
+    return text.replace('ʧ','tʃ').replace('ʥ','dʑ')
diff --git a/text/mandarin.py b/text/mandarin.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cad78fbec12c9c0f44e744fb37d0a8d37ae3f8a
--- /dev/null
+++ b/text/mandarin.py
@@ -0,0 +1,326 @@
+import os
+import sys
+import re
+from pypinyin import lazy_pinyin, BOPOMOFO
+import jieba
+import cn2an
+import logging
+
+
+# List of (Latin alphabet, bopomofo) pairs:
+_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('a', 'ㄟˉ'),
+    ('b', 'ㄅㄧˋ'),
+    ('c', 'ㄙㄧˉ'),
+    ('d', 'ㄉㄧˋ'),
+    ('e', 'ㄧˋ'),
+    ('f', 'ㄝˊㄈㄨˋ'),
+    ('g', 'ㄐㄧˋ'),
+    ('h', 'ㄝˇㄑㄩˋ'),
+    ('i', 'ㄞˋ'),
+    ('j', 'ㄐㄟˋ'),
+    ('k', 'ㄎㄟˋ'),
+    ('l', 'ㄝˊㄛˋ'),
+    ('m', 'ㄝˊㄇㄨˋ'),
+    ('n', 'ㄣˉ'),
+    ('o', 'ㄡˉ'),
+    ('p', 'ㄆㄧˉ'),
+    ('q', 'ㄎㄧㄡˉ'),
+    ('r', 'ㄚˋ'),
+    ('s', 'ㄝˊㄙˋ'),
+    ('t', 'ㄊㄧˋ'),
+    ('u', 'ㄧㄡˉ'),
+    ('v', 'ㄨㄧˉ'),
+    ('w', 'ㄉㄚˋㄅㄨˋㄌㄧㄡˋ'),
+    ('x', 'ㄝˉㄎㄨˋㄙˋ'),
+    ('y', 'ㄨㄞˋ'),
+    ('z', 'ㄗㄟˋ')
+]]
+
+# List of (bopomofo, romaji) pairs:
+_bopomofo_to_romaji = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('ㄅㄛ', 'p⁼wo'),
+    ('ㄆㄛ', 'pʰwo'),
+    ('ㄇㄛ', 'mwo'),
+    ('ㄈㄛ', 'fwo'),
+    ('ㄅ', 'p⁼'),
+    ('ㄆ', 'pʰ'),
+    ('ㄇ', 'm'),
+    ('ㄈ', 'f'),
+    ('ㄉ', 't⁼'),
+    ('ㄊ', 'tʰ'),
+    ('ㄋ', 'n'),
+    ('ㄌ', 'l'),
+    ('ㄍ', 'k⁼'),
+    ('ㄎ', 'kʰ'),
+    ('ㄏ', 'h'),
+    ('ㄐ', 'ʧ⁼'),
+    ('ㄑ', 'ʧʰ'),
+    ('ㄒ', 'ʃ'),
+    ('ㄓ', 'ʦ`⁼'),
+    ('ㄔ', 'ʦ`ʰ'),
+    ('ㄕ', 's`'),
+    ('ㄖ', 'ɹ`'),
+    ('ㄗ', 'ʦ⁼'),
+    ('ㄘ', 'ʦʰ'),
+    ('ㄙ', 's'),
+    ('ㄚ', 'a'),
+    ('ㄛ', 'o'),
+    ('ㄜ', 'ə'),
+    ('ㄝ', 'e'),
+    ('ㄞ', 'ai'),
+    ('ㄟ', 'ei'),
+    ('ㄠ', 'au'),
+    ('ㄡ', 'ou'),
+    ('ㄧㄢ', 'yeNN'),
+    ('ㄢ', 'aNN'),
+    ('ㄧㄣ', 'iNN'),
+    ('ㄣ', 'əNN'),
+    ('ㄤ', 'aNg'),
+    ('ㄧㄥ', 'iNg'),
+    ('ㄨㄥ', 'uNg'),
+    ('ㄩㄥ', 'yuNg'),
+    ('ㄥ', 'əNg'),
+    ('ㄦ', 'əɻ'),
+    ('ㄧ', 'i'),
+    ('ㄨ', 'u'),
+    ('ㄩ', 'ɥ'),
+    ('ˉ', '→'),
+    ('ˊ', '↑'),
+    ('ˇ', '↓↑'),
+    ('ˋ', '↓'),
+    ('˙', ''),
+    ('，', ','),
+    ('。', '.'),
+    ('！', '!'),
+    ('？', '?'),
+    ('—', '-')
+]]
+
+# List of (romaji, ipa) pairs:
+_romaji_to_ipa = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('ʃy', 'ʃ'),
+    ('ʧʰy', 'ʧʰ'),
+    ('ʧ⁼y', 'ʧ⁼'),
+    ('NN', 'n'),
+    ('Ng', 'ŋ'),
+    ('y', 'j'),
+    ('h', 'x')
+]]
+
+# List of (bopomofo, ipa) pairs:
+_bopomofo_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('ㄅㄛ', 'p⁼wo'),
+    ('ㄆㄛ', 'pʰwo'),
+    ('ㄇㄛ', 'mwo'),
+    ('ㄈㄛ', 'fwo'),
+    ('ㄅ', 'p⁼'),
+    ('ㄆ', 'pʰ'),
+    ('ㄇ', 'm'),
+    ('ㄈ', 'f'),
+    ('ㄉ', 't⁼'),
+    ('ㄊ', 'tʰ'),
+    ('ㄋ', 'n'),
+    ('ㄌ', 'l'),
+    ('ㄍ', 'k⁼'),
+    ('ㄎ', 'kʰ'),
+    ('ㄏ', 'x'),
+    ('ㄐ', 'tʃ⁼'),
+    ('ㄑ', 'tʃʰ'),
+    ('ㄒ', 'ʃ'),
+    ('ㄓ', 'ts`⁼'),
+    ('ㄔ', 'ts`ʰ'),
+    ('ㄕ', 's`'),
+    ('ㄖ', 'ɹ`'),
+    ('ㄗ', 'ts⁼'),
+    ('ㄘ', 'tsʰ'),
+    ('ㄙ', 's'),
+    ('ㄚ', 'a'),
+    ('ㄛ', 'o'),
+    ('ㄜ', 'ə'),
+    ('ㄝ', 'ɛ'),
+    ('ㄞ', 'aɪ'),
+    ('ㄟ', 'eɪ'),
+    ('ㄠ', 'ɑʊ'),
+    ('ㄡ', 'oʊ'),
+    ('ㄧㄢ', 'jɛn'),
+    ('ㄩㄢ', 'ɥæn'),
+    ('ㄢ', 'an'),
+    ('ㄧㄣ', 'in'),
+    ('ㄩㄣ', 'ɥn'),
+    ('ㄣ', 'ən'),
+    ('ㄤ', 'ɑŋ'),
+    ('ㄧㄥ', 'iŋ'),
+    ('ㄨㄥ', 'ʊŋ'),
+    ('ㄩㄥ', 'jʊŋ'),
+    ('ㄥ', 'əŋ'),
+    ('ㄦ', 'əɻ'),
+    ('ㄧ', 'i'),
+    ('ㄨ', 'u'),
+    ('ㄩ', 'ɥ'),
+    ('ˉ', '→'),
+    ('ˊ', '↑'),
+    ('ˇ', '↓↑'),
+    ('ˋ', '↓'),
+    ('˙', ''),
+    ('，', ','),
+    ('。', '.'),
+    ('！', '!'),
+    ('？', '?'),
+    ('—', '-')
+]]
+
+# List of (bopomofo, ipa2) pairs:
+_bopomofo_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('ㄅㄛ', 'pwo'),
+    ('ㄆㄛ', 'pʰwo'),
+    ('ㄇㄛ', 'mwo'),
+    ('ㄈㄛ', 'fwo'),
+    ('ㄅ', 'p'),
+    ('ㄆ', 'pʰ'),
+    ('ㄇ', 'm'),
+    ('ㄈ', 'f'),
+    ('ㄉ', 't'),
+    ('ㄊ', 'tʰ'),
+    ('ㄋ', 'n'),
+    ('ㄌ', 'l'),
+    ('ㄍ', 'k'),
+    ('ㄎ', 'kʰ'),
+    ('ㄏ', 'h'),
+    ('ㄐ', 'tɕ'),
+    ('ㄑ', 'tɕʰ'),
+    ('ㄒ', 'ɕ'),
+    ('ㄓ', 'tʂ'),
+    ('ㄔ', 'tʂʰ'),
+    ('ㄕ', 'ʂ'),
+    ('ㄖ', 'ɻ'),
+    ('ㄗ', 'ts'),
+    ('ㄘ', 'tsʰ'),
+    ('ㄙ', 's'),
+    ('ㄚ', 'a'),
+    ('ㄛ', 'o'),
+    ('ㄜ', 'ɤ'),
+    ('ㄝ', 'ɛ'),
+    ('ㄞ', 'aɪ'),
+    ('ㄟ', 'eɪ'),
+    ('ㄠ', 'ɑʊ'),
+    ('ㄡ', 'oʊ'),
+    ('ㄧㄢ', 'jɛn'),
+    ('ㄩㄢ', 'yæn'),
+    ('ㄢ', 'an'),
+    ('ㄧㄣ', 'in'),
+    ('ㄩㄣ', 'yn'),
+    ('ㄣ', 'ən'),
+    ('ㄤ', 'ɑŋ'),
+    ('ㄧㄥ', 'iŋ'),
+    ('ㄨㄥ', 'ʊŋ'),
+    ('ㄩㄥ', 'jʊŋ'),
+    ('ㄥ', 'ɤŋ'),
+    ('ㄦ', 'əɻ'),
+    ('ㄧ', 'i'),
+    ('ㄨ', 'u'),
+    ('ㄩ', 'y'),
+    ('ˉ', '˥'),
+    ('ˊ', '˧˥'),
+    ('ˇ', '˨˩˦'),
+    ('ˋ', '˥˩'),
+    ('˙', ''),
+    ('，', ','),
+    ('。', '.'),
+    ('！', '!'),
+    ('？', '?'),
+    ('—', '-')
+]]
+
+
+def number_to_chinese(text):
+    numbers = re.findall(r'\d+(?:\.?\d+)?', text)
+    for number in numbers:
+        text = text.replace(number, cn2an.an2cn(number), 1)
+    return text
+
+
+def chinese_to_bopomofo(text):
+    text = text.replace('、', '，').replace('；', '，').replace('：', '，')
+    words = jieba.lcut(text, cut_all=False)
+    text = ''
+    for word in words:
+        bopomofos = lazy_pinyin(word, BOPOMOFO)
+        if not re.search('[\u4e00-\u9fff]', word):
+            text += word
+            continue
+        for i in range(len(bopomofos)):
+            bopomofos[i] = re.sub(r'([\u3105-\u3129])$', r'\1ˉ', bopomofos[i])
+        if text != '':
+            text += ' '
+        text += ''.join(bopomofos)
+    return text
+
+
+def latin_to_bopomofo(text):
+    for regex, replacement in _latin_to_bopomofo:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def bopomofo_to_romaji(text):
+    for regex, replacement in _bopomofo_to_romaji:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def bopomofo_to_ipa(text):
+    for regex, replacement in _bopomofo_to_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def bopomofo_to_ipa2(text):
+    for regex, replacement in _bopomofo_to_ipa2:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def chinese_to_romaji(text):
+    text = number_to_chinese(text)
+    text = chinese_to_bopomofo(text)
+    text = latin_to_bopomofo(text)
+    text = bopomofo_to_romaji(text)
+    text = re.sub('i([aoe])', r'y\1', text)
+    text = re.sub('u([aoəe])', r'w\1', text)
+    text = re.sub('([ʦsɹ]`[⁼ʰ]?)([→↓↑ ]+|$)',
+                  r'\1ɹ`\2', text).replace('ɻ', 'ɹ`')
+    text = re.sub('([ʦs][⁼ʰ]?)([→↓↑ ]+|$)', r'\1ɹ\2', text)
+    return text
+
+
+def chinese_to_lazy_ipa(text):
+    text = chinese_to_romaji(text)
+    for regex, replacement in _romaji_to_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def chinese_to_ipa(text):
+    text = number_to_chinese(text)
+    text = chinese_to_bopomofo(text)
+    text = latin_to_bopomofo(text)
+    text = bopomofo_to_ipa(text)
+    text = re.sub('i([aoe])', r'j\1', text)
+    text = re.sub('u([aoəe])', r'w\1', text)
+    text = re.sub('([sɹ]`[⁼ʰ]?)([→↓↑ ]+|$)',
+                  r'\1ɹ`\2', text).replace('ɻ', 'ɹ`')
+    text = re.sub('([s][⁼ʰ]?)([→↓↑ ]+|$)', r'\1ɹ\2', text)
+    return text
+
+
+def chinese_to_ipa2(text):
+    text = number_to_chinese(text)
+    text = chinese_to_bopomofo(text)
+    text = latin_to_bopomofo(text)
+    text = bopomofo_to_ipa2(text)
+    text = re.sub(r'i([aoe])', r'j\1', text)
+    text = re.sub(r'u([aoəe])', r'w\1', text)
+    text = re.sub(r'([ʂɹ]ʰ?)([˩˨˧˦˥ ]+|$)', r'\1ʅ\2', text)
+    text = re.sub(r'(sʰ?)([˩˨˧˦˥ ]+|$)', r'\1ɿ\2', text)
+    return text
diff --git a/text/ngu_dialect.py b/text/ngu_dialect.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb1831d9bddc646961fbaf06465a0ac08663b11c
--- /dev/null
+++ b/text/ngu_dialect.py
@@ -0,0 +1,30 @@
+import re
+import opencc
+
+
+dialects = {'SZ': 'suzhou', 'WX': 'wuxi', 'CZ': 'changzhou', 'HZ': 'hangzhou',
+            'SX': 'shaoxing', 'NB': 'ningbo', 'JJ': 'jingjiang', 'YX': 'yixing',
+            'JD': 'jiading', 'ZR': 'zhenru', 'PH': 'pinghu', 'TX': 'tongxiang',
+            'JS': 'jiashan', 'HN': 'xiashi', 'LP': 'linping', 'XS': 'xiaoshan',
+            'FY': 'fuyang', 'RA': 'ruao', 'CX': 'cixi', 'SM': 'sanmen',
+            'TT': 'tiantai', 'WZ': 'wenzhou', 'SC': 'suichang', 'YB': 'youbu'}
+
+converters = {}
+
+for dialect in dialects.values():
+    try:
+        converters[dialect] = opencc.OpenCC(dialect)
+    except:
+        pass
+
+
+def ngu_dialect_to_ipa(text, dialect):
+    dialect = dialects[dialect]
+    text = converters[dialect].convert(text).replace('-','').replace('$',' ')
+    text = re.sub(r'[、；：]', '，', text)
+    text = re.sub(r'\s*，\s*', ', ', text)
+    text = re.sub(r'\s*。\s*', '. ', text)
+    text = re.sub(r'\s*？\s*', '? ', text)
+    text = re.sub(r'\s*！\s*', '! ', text)
+    text = re.sub(r'\s*$', '', text)
+    return text
diff --git a/text/sanskrit.py b/text/sanskrit.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf39b6c72edd82d5b090322c6579f676b26e3dd2
--- /dev/null
+++ b/text/sanskrit.py
@@ -0,0 +1,62 @@
+import re
+from indic_transliteration import sanscript
+
+
+# List of (iast, ipa) pairs:
+_iast_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('a', 'ə'),
+    ('ā', 'aː'),
+    ('ī', 'iː'),
+    ('ū', 'uː'),
+    ('ṛ', 'ɹ`'),
+    ('ṝ', 'ɹ`ː'),
+    ('ḷ', 'l`'),
+    ('ḹ', 'l`ː'),
+    ('e', 'eː'),
+    ('o', 'oː'),
+    ('k', 'k⁼'),
+    ('k⁼h', 'kʰ'),
+    ('g', 'g⁼'),
+    ('g⁼h', 'gʰ'),
+    ('ṅ', 'ŋ'),
+    ('c', 'ʧ⁼'),
+    ('ʧ⁼h', 'ʧʰ'),
+    ('j', 'ʥ⁼'),
+    ('ʥ⁼h', 'ʥʰ'),
+    ('ñ', 'n^'),
+    ('ṭ', 't`⁼'),
+    ('t`⁼h', 't`ʰ'),
+    ('ḍ', 'd`⁼'),
+    ('d`⁼h', 'd`ʰ'),
+    ('ṇ', 'n`'),
+    ('t', 't⁼'),
+    ('t⁼h', 'tʰ'),
+    ('d', 'd⁼'),
+    ('d⁼h', 'dʰ'),
+    ('p', 'p⁼'),
+    ('p⁼h', 'pʰ'),
+    ('b', 'b⁼'),
+    ('b⁼h', 'bʰ'),
+    ('y', 'j'),
+    ('ś', 'ʃ'),
+    ('ṣ', 's`'),
+    ('r', 'ɾ'),
+    ('l̤', 'l`'),
+    ('h', 'ɦ'),
+    ("'", ''),
+    ('~', '^'),
+    ('ṃ', '^')
+]]
+
+
+def devanagari_to_ipa(text):
+    text = text.replace('ॐ', 'ओम्')
+    text = re.sub(r'\s*।\s*$', '.', text)
+    text = re.sub(r'\s*।\s*', ', ', text)
+    text = re.sub(r'\s*॥', '.', text)
+    text = sanscript.transliterate(text, sanscript.DEVANAGARI, sanscript.IAST)
+    for regex, replacement in _iast_to_ipa:
+        text = re.sub(regex, replacement, text)
+    text = re.sub('(.)[`ː]*ḥ', lambda x: x.group(0)
+                  [:-1]+'h'+x.group(1)+'*', text)
+    return text
diff --git a/text/shanghainese.py b/text/shanghainese.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b2cd225472d197af323ed7ff29d0d7254896d33
--- /dev/null
+++ b/text/shanghainese.py
@@ -0,0 +1,64 @@
+import re
+import cn2an
+import opencc
+
+
+converter = opencc.OpenCC('zaonhe')
+
+# List of (Latin alphabet, ipa) pairs:
+_latin_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
+    ('A', 'ᴇ'),
+    ('B', 'bi'),
+    ('C', 'si'),
+    ('D', 'di'),
+    ('E', 'i'),
+    ('F', 'ᴇf'),
+    ('G', 'dʑi'),
+    ('H', 'ᴇtɕʰ'),
+    ('I', 'ᴀi'),
+    ('J', 'dʑᴇ'),
+    ('K', 'kʰᴇ'),
+    ('L', 'ᴇl'),
+    ('M', 'ᴇm'),
+    ('N', 'ᴇn'),
+    ('O', 'o'),
+    ('P', 'pʰi'),
+    ('Q', 'kʰiu'),
+    ('R', 'ᴀl'),
+    ('S', 'ᴇs'),
+    ('T', 'tʰi'),
+    ('U', 'ɦiu'),
+    ('V', 'vi'),
+    ('W', 'dᴀbɤliu'),
+    ('X', 'ᴇks'),
+    ('Y', 'uᴀi'),
+    ('Z', 'zᴇ')
+]]
+
+
+def _number_to_shanghainese(num):
+    num = cn2an.an2cn(num).replace('一十','十').replace('二十', '廿').replace('二', '两')
+    return re.sub(r'((?:^|[^三四五六七八九])十|廿)两', r'\1二', num)
+
+
+def number_to_shanghainese(text):
+    return re.sub(r'\d+(?:\.?\d+)?', lambda x: _number_to_shanghainese(x.group()), text)
+
+
+def latin_to_ipa(text):
+    for regex, replacement in _latin_to_ipa:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def shanghainese_to_ipa(text):
+    text = number_to_shanghainese(text.upper())
+    text = converter.convert(text).replace('-','').replace('$',' ')
+    text = re.sub(r'[A-Z]', lambda x: latin_to_ipa(x.group())+' ', text)
+    text = re.sub(r'[、；：]', '，', text)
+    text = re.sub(r'\s*，\s*', ', ', text)
+    text = re.sub(r'\s*。\s*', '. ', text)
+    text = re.sub(r'\s*？\s*', '? ', text)
+    text = re.sub(r'\s*！\s*', '! ', text)
+    text = re.sub(r'\s*$', '', text)
+    return text
diff --git a/text/symbols.py b/text/symbols.py
new file mode 100644
index 0000000000000000000000000000000000000000..651d4810ad10c66560eb768a0f370a0ebc62fa77
--- /dev/null
+++ b/text/symbols.py
@@ -0,0 +1,76 @@
+'''
+Defines the set of symbols used in text input to the model.
+'''
+
+# japanese_cleaners
+# _pad        = '_'
+# _punctuation = ',.!?-'
+# _letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
+
+
+'''# japanese_cleaners2
+_pad        = '_'
+_punctuation = ',.!?-~…'
+_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
+'''
+
+
+'''# korean_cleaners
+_pad        = '_'
+_punctuation = ',.!?…~'
+_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
+'''
+
+'''# chinese_cleaners
+_pad        = '_'
+_punctuation = '，。！？—…'
+_letters = 'ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩˉˊˇˋ˙ '
+'''
+
+# # zh_ja_mixture_cleaners
+# _pad        = '_'
+# _punctuation = ',.!?-~…'
+# _letters = 'AEINOQUabdefghijklmnoprstuvwyzʃʧʦɯɹəɥ⁼ʰ`→↓↑ '
+
+
+'''# sanskrit_cleaners
+_pad        = '_'
+_punctuation = '।'
+_letters = 'ँंःअआइईउऊऋएऐओऔकखगघङचछजझञटठडढणतथदधनपफबभमयरलळवशषसहऽािीुूृॄेैोौ्ॠॢ '
+'''
+
+'''# cjks_cleaners
+_pad        = '_'
+_punctuation = ',.!?-~…'
+_letters = 'NQabdefghijklmnopstuvwxyzʃʧʥʦɯɹəɥçɸɾβŋɦː⁼ʰ`^#*=→↓↑ '
+'''
+
+'''# thai_cleaners
+_pad        = '_'
+_punctuation = '.!? '
+_letters = 'กขฃคฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลวศษสหฬอฮฯะัาำิีึืุูเแโใไๅๆ็่้๊๋์'
+'''
+
+# # cjke_cleaners2
+_pad        = '_'
+_punctuation = ',.!?-~…'
+_letters = 'NQabdefghijklmnopstuvwxyzɑæʃʑçɯɪɔɛɹðəɫɥɸʊɾʒθβŋɦ⁼ʰ`^#*=ˈˌ→↓↑ '
+
+
+'''# shanghainese_cleaners
+_pad        = '_'
+_punctuation = ',.!?…'
+_letters = 'abdfghiklmnopstuvyzøŋȵɑɔɕəɤɦɪɿʑʔʰ̩̃ᴀᴇ15678 '
+'''
+
+'''# chinese_dialect_cleaners
+_pad        = '_'
+_punctuation = ',.!?~…─'
+_letters = '#Nabdefghijklmnoprstuvwxyzæçøŋœȵɐɑɒɓɔɕɗɘəɚɛɜɣɤɦɪɭɯɵɷɸɻɾɿʂʅʊʋʌʏʑʔʦʮʰʷˀː˥˦˧˨˩̥̩̃̚ᴀᴇ↑↓∅ⱼ '
+'''
+
+# Export all symbols:
+symbols = [_pad] + list(_punctuation) + list(_letters)
+
+# Special symbol ids
+SPACE_ID = symbols.index(" ")
diff --git a/text/thai.py b/text/thai.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a4232466b812fca0ef3257823cb184b8009951d
--- /dev/null
+++ b/text/thai.py
@@ -0,0 +1,44 @@
+import re
+from num_thai.thainumbers import NumThai
+
+
+num = NumThai()
+
+# List of (Latin alphabet, Thai) pairs:
+_latin_to_thai = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('a', 'เอ'),
+    ('b','บี'),
+    ('c','ซี'),
+    ('d','ดี'),
+    ('e','อี'),
+    ('f','เอฟ'),
+    ('g','จี'),
+    ('h','เอช'),
+    ('i','ไอ'),
+    ('j','เจ'),
+    ('k','เค'),
+    ('l','แอล'),
+    ('m','เอ็ม'),
+    ('n','เอ็น'),
+    ('o','โอ'),
+    ('p','พี'),
+    ('q','คิว'),
+    ('r','แอร์'),
+    ('s','เอส'),
+    ('t','ที'),
+    ('u','ยู'),
+    ('v','วี'),
+    ('w','ดับเบิลยู'),
+    ('x','เอ็กซ์'),
+    ('y','วาย'),
+    ('z','ซี')
+]]
+
+
+def num_to_thai(text):
+    return re.sub(r'(?:\d+(?:,?\d+)?)+(?:\.\d+(?:,?\d+)?)?', lambda x: ''.join(num.NumberToTextThai(float(x.group(0).replace(',', '')))), text)
+
+def latin_to_thai(text):
+    for regex, replacement in _latin_to_thai:
+        text = re.sub(regex, replacement, text)
+    return text
diff --git a/transforms.py b/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..a92f0e420295bd8c14c1447476f07becc3ad4704
--- /dev/null
+++ b/transforms.py
@@ -0,0 +1,193 @@
+import torch
+from torch.nn import functional as F
+
+import numpy as np
+
+
+DEFAULT_MIN_BIN_WIDTH = 1e-3
+DEFAULT_MIN_BIN_HEIGHT = 1e-3
+DEFAULT_MIN_DERIVATIVE = 1e-3
+
+
+def piecewise_rational_quadratic_transform(inputs, 
+                                           unnormalized_widths,
+                                           unnormalized_heights,
+                                           unnormalized_derivatives,
+                                           inverse=False,
+                                           tails=None, 
+                                           tail_bound=1.,
+                                           min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                                           min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                                           min_derivative=DEFAULT_MIN_DERIVATIVE):
+
+    if tails is None:
+        spline_fn = rational_quadratic_spline
+        spline_kwargs = {}
+    else:
+        spline_fn = unconstrained_rational_quadratic_spline
+        spline_kwargs = {
+            'tails': tails,
+            'tail_bound': tail_bound
+        }
+
+    outputs, logabsdet = spline_fn(
+            inputs=inputs,
+            unnormalized_widths=unnormalized_widths,
+            unnormalized_heights=unnormalized_heights,
+            unnormalized_derivatives=unnormalized_derivatives,
+            inverse=inverse,
+            min_bin_width=min_bin_width,
+            min_bin_height=min_bin_height,
+            min_derivative=min_derivative,
+            **spline_kwargs
+    )
+    return outputs, logabsdet
+
+
+def searchsorted(bin_locations, inputs, eps=1e-6):
+    bin_locations[..., -1] += eps
+    return torch.sum(
+        inputs[..., None] >= bin_locations,
+        dim=-1
+    ) - 1
+
+
+def unconstrained_rational_quadratic_spline(inputs,
+                                            unnormalized_widths,
+                                            unnormalized_heights,
+                                            unnormalized_derivatives,
+                                            inverse=False,
+                                            tails='linear',
+                                            tail_bound=1.,
+                                            min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                                            min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                                            min_derivative=DEFAULT_MIN_DERIVATIVE):
+    inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
+    outside_interval_mask = ~inside_interval_mask
+
+    outputs = torch.zeros_like(inputs)
+    logabsdet = torch.zeros_like(inputs)
+
+    if tails == 'linear':
+        unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
+        constant = np.log(np.exp(1 - min_derivative) - 1)
+        unnormalized_derivatives[..., 0] = constant
+        unnormalized_derivatives[..., -1] = constant
+
+        outputs[outside_interval_mask] = inputs[outside_interval_mask]
+        logabsdet[outside_interval_mask] = 0
+    else:
+        raise RuntimeError('{} tails are not implemented.'.format(tails))
+
+    outputs[inside_interval_mask], logabsdet[inside_interval_mask] = rational_quadratic_spline(
+        inputs=inputs[inside_interval_mask],
+        unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
+        unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
+        unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
+        inverse=inverse,
+        left=-tail_bound, right=tail_bound, bottom=-tail_bound, top=tail_bound,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative
+    )
+
+    return outputs, logabsdet
+
+def rational_quadratic_spline(inputs,
+                              unnormalized_widths,
+                              unnormalized_heights,
+                              unnormalized_derivatives,
+                              inverse=False,
+                              left=0., right=1., bottom=0., top=1.,
+                              min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+                              min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+                              min_derivative=DEFAULT_MIN_DERIVATIVE):
+    if torch.min(inputs) < left or torch.max(inputs) > right:
+        raise ValueError('Input to a transform is not within its domain')
+
+    num_bins = unnormalized_widths.shape[-1]
+
+    if min_bin_width * num_bins > 1.0:
+        raise ValueError('Minimal bin width too large for the number of bins')
+    if min_bin_height * num_bins > 1.0:
+        raise ValueError('Minimal bin height too large for the number of bins')
+
+    widths = F.softmax(unnormalized_widths, dim=-1)
+    widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
+    cumwidths = torch.cumsum(widths, dim=-1)
+    cumwidths = F.pad(cumwidths, pad=(1, 0), mode='constant', value=0.0)
+    cumwidths = (right - left) * cumwidths + left
+    cumwidths[..., 0] = left
+    cumwidths[..., -1] = right
+    widths = cumwidths[..., 1:] - cumwidths[..., :-1]
+
+    derivatives = min_derivative + F.softplus(unnormalized_derivatives)
+
+    heights = F.softmax(unnormalized_heights, dim=-1)
+    heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
+    cumheights = torch.cumsum(heights, dim=-1)
+    cumheights = F.pad(cumheights, pad=(1, 0), mode='constant', value=0.0)
+    cumheights = (top - bottom) * cumheights + bottom
+    cumheights[..., 0] = bottom
+    cumheights[..., -1] = top
+    heights = cumheights[..., 1:] - cumheights[..., :-1]
+
+    if inverse:
+        bin_idx = searchsorted(cumheights, inputs)[..., None]
+    else:
+        bin_idx = searchsorted(cumwidths, inputs)[..., None]
+
+    input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
+    input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
+
+    input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
+    delta = heights / widths
+    input_delta = delta.gather(-1, bin_idx)[..., 0]
+
+    input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
+    input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
+
+    input_heights = heights.gather(-1, bin_idx)[..., 0]
+
+    if inverse:
+        a = (((inputs - input_cumheights) * (input_derivatives
+                                             + input_derivatives_plus_one
+                                             - 2 * input_delta)
+              + input_heights * (input_delta - input_derivatives)))
+        b = (input_heights * input_derivatives
+             - (inputs - input_cumheights) * (input_derivatives
+                                              + input_derivatives_plus_one
+                                              - 2 * input_delta))
+        c = - input_delta * (inputs - input_cumheights)
+
+        discriminant = b.pow(2) - 4 * a * c
+        assert (discriminant >= 0).all()
+
+        root = (2 * c) / (-b - torch.sqrt(discriminant))
+        outputs = root * input_bin_widths + input_cumwidths
+
+        theta_one_minus_theta = root * (1 - root)
+        denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+                                     * theta_one_minus_theta)
+        derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * root.pow(2)
+                                                     + 2 * input_delta * theta_one_minus_theta
+                                                     + input_derivatives * (1 - root).pow(2))
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, -logabsdet
+    else:
+        theta = (inputs - input_cumwidths) / input_bin_widths
+        theta_one_minus_theta = theta * (1 - theta)
+
+        numerator = input_heights * (input_delta * theta.pow(2)
+                                     + input_derivatives * theta_one_minus_theta)
+        denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+                                     * theta_one_minus_theta)
+        outputs = input_cumheights + numerator / denominator
+
+        derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * theta.pow(2)
+                                                     + 2 * input_delta * theta_one_minus_theta
+                                                     + input_derivatives * (1 - theta).pow(2))
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, logabsdet
diff --git a/utils.py b/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..648ae27340be844c0926e0aaf5c0fc2a46ea7edf
--- /dev/null
+++ b/utils.py
@@ -0,0 +1,434 @@
+import os
+import glob
+import sys
+import argparse
+import logging
+import json
+import subprocess
+import numpy as np
+from scipy.io.wavfile import read
+import torch
+import regex as re
+
+MATPLOTLIB_FLAG = False
+
+logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
+logger = logging
+
+
+
+zh_pattern = re.compile(r'[\u4e00-\u9fa5]')
+en_pattern = re.compile(r'[a-zA-Z]')
+jp_pattern = re.compile(r'[\u3040-\u30ff\u31f0-\u31ff]')
+kr_pattern = re.compile(r'[\uac00-\ud7af\u1100-\u11ff\u3130-\u318f\ua960-\ua97f]')
+num_pattern=re.compile(r'[0-9]')
+comma=r"(?<=[.。!！?？；;，,、:：'\"‘“”’()（）《》「」~——])"    #向前匹配但固定长度
+tags={'ZH':'[ZH]','EN':'[EN]','JP':'[JA]','KR':'[KR]'}
+
+def tag_cjke(text):
+    '''为中英日韩加tag,中日正则分不开，故先分句分离中日再识别，以应对大部分情况'''
+    sentences = re.split(r"([.。!！?？；;，,、:：'\"‘“”’()（）【】《》「」~——]+ *(?![0-9]))", text) #分句，排除小数点
+    sentences.append("")
+    sentences = ["".join(i) for i in zip(sentences[0::2],sentences[1::2])]
+    # print(sentences)
+    prev_lang=None
+    tagged_text = ""
+    for s in sentences:
+        #全为符号跳过
+        nu = re.sub(r'[\s\p{P}]+', '', s, flags=re.U).strip()   
+        if len(nu)==0:
+            continue
+        s = re.sub(r'[()（）《》「」【】‘“”’]+', '', s)
+        jp=re.findall(jp_pattern, s)
+        #本句含日语字符判断为日语
+        if len(jp)>0:  
+            prev_lang,tagged_jke=tag_jke(s,prev_lang)
+            tagged_text +=tagged_jke
+        else:
+            prev_lang,tagged_cke=tag_cke(s,prev_lang)
+            tagged_text +=tagged_cke
+    return tagged_text
+
+def tag_jke(text,prev_sentence=None):
+    '''为英日韩加tag'''
+    # 初始化标记变量
+    tagged_text = ""
+    prev_lang = None
+    tagged=0
+    # 遍历文本
+    for char in text:
+        # 判断当前字符属于哪种语言
+        if jp_pattern.match(char):
+            lang = "JP"
+        elif zh_pattern.match(char):
+            lang = "JP"
+        elif kr_pattern.match(char):
+            lang = "KR"
+        elif en_pattern.match(char):
+            lang = "EN"
+        # elif num_pattern.match(char):
+        #     lang = prev_sentence
+        else:
+            lang = None
+            tagged_text += char
+            continue
+        # 如果当前语言与上一个语言不同，就添加标记
+        if lang != prev_lang:
+            tagged=1
+            if prev_lang==None: # 开头
+                tagged_text =tags[lang]+tagged_text
+            else:
+                tagged_text =tagged_text+tags[prev_lang]+tags[lang]
+
+            # 重置标记变量
+            prev_lang = lang
+
+        # 添加当前字符到标记文本中
+        tagged_text += char
+    
+    # 在最后一个语言的结尾添加对应的标记
+    if prev_lang:
+            tagged_text += tags[prev_lang]
+    if not tagged:
+        prev_lang=prev_sentence
+        tagged_text =tags[prev_lang]+tagged_text+tags[prev_lang]
+
+    return prev_lang,tagged_text
+
+def tag_cke(text,prev_sentence=None):
+    '''为中英韩加tag'''
+    # 初始化标记变量
+    tagged_text = ""
+    prev_lang = None
+    # 是否全略过未标签
+    tagged=0
+    
+    # 遍历文本
+    for char in text:
+        # 判断当前字符属于哪种语言
+        if zh_pattern.match(char):
+            lang = "ZH"
+        elif kr_pattern.match(char):
+            lang = "KR"
+        elif en_pattern.match(char):
+            lang = "EN"
+        # elif num_pattern.match(char):
+        #     lang = prev_sentence
+        else:
+            # 略过
+            lang = None
+            tagged_text += char
+            continue
+
+        # 如果当前语言与上一个语言不同，添加标记
+        if lang != prev_lang:
+            tagged=1
+            if prev_lang==None: # 开头
+                tagged_text =tags[lang]+tagged_text
+            else:
+                tagged_text =tagged_text+tags[prev_lang]+tags[lang]
+
+            # 重置标记变量
+            prev_lang = lang
+
+        # 添加当前字符到标记文本中
+        tagged_text += char
+    
+    # 在最后一个语言的结尾添加对应的标记
+    if prev_lang:
+            tagged_text += tags[prev_lang]
+    # 未标签则继承上一句标签
+    if tagged==0:
+        prev_lang=prev_sentence
+        tagged_text =tags[prev_lang]+tagged_text+tags[prev_lang]
+    return prev_lang,tagged_text
+
+
+
+def load_checkpoint(checkpoint_path, model, optimizer=None, drop_speaker_emb=False):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
+    iteration = checkpoint_dict['iteration']
+    learning_rate = checkpoint_dict['learning_rate']
+    if optimizer is not None:
+        optimizer.load_state_dict(checkpoint_dict['optimizer'])
+    saved_state_dict = checkpoint_dict['model']
+    if hasattr(model, 'module'):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    new_state_dict = {}
+    for k, v in state_dict.items():
+        try:
+            if k == 'emb_g.weight':
+                if drop_speaker_emb:
+                    new_state_dict[k] = v
+                    continue
+                v[:saved_state_dict[k].shape[0], :] = saved_state_dict[k]
+                new_state_dict[k] = v
+            else:
+                new_state_dict[k] = saved_state_dict[k]
+        except:
+            logger.info("%s is not in the checkpoint" % k)
+            new_state_dict[k] = v
+    if hasattr(model, 'module'):
+        model.module.load_state_dict(new_state_dict)
+    else:
+        model.load_state_dict(new_state_dict)
+    logger.info("Loaded checkpoint '{}' (iteration {})".format(
+        checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info("Saving model and optimizer state at iteration {} to {}".format(
+        iteration, checkpoint_path))
+    if hasattr(model, 'module'):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    torch.save({'model': state_dict,
+                'iteration': iteration,
+                'optimizer': optimizer.state_dict() if optimizer is not None else None,
+                'learning_rate': learning_rate}, checkpoint_path)
+
+
+def summarize(writer, global_step, scalars={}, histograms={}, images={}, audios={}, audio_sampling_rate=22050):
+    for k, v in scalars.items():
+        writer.add_scalar(k, v, global_step)
+    for k, v in histograms.items():
+        writer.add_histogram(k, v, global_step)
+    for k, v in images.items():
+        writer.add_image(k, v, global_step, dataformats='HWC')
+    for k, v in audios.items():
+        writer.add_audio(k, v, global_step, audio_sampling_rate)
+
+
+def extract_digits(f):
+    digits = "".join(filter(str.isdigit, f))
+    return int(digits) if digits else -1
+
+
+def latest_checkpoint_path(dir_path, regex="G_[0-9]*.pth"):
+    f_list = glob.glob(os.path.join(dir_path, regex))
+    f_list.sort(key=lambda f: extract_digits(f))
+    x = f_list[-1]
+    print(f"latest_checkpoint_path:{x}")
+    return x
+
+
+def oldest_checkpoint_path(dir_path, regex="G_[0-9]*.pth", preserved=4):
+    f_list = glob.glob(os.path.join(dir_path, regex))
+    f_list.sort(key=lambda f: extract_digits(f))
+    if len(f_list) > preserved:
+        x = f_list[0]
+        print(f"oldest_checkpoint_path:{x}")
+        return x
+    return ""
+
+
+def plot_spectrogram_to_numpy(spectrogram):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger('matplotlib')
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(10, 2))
+    im = ax.imshow(spectrogram, aspect="auto", origin="lower",
+                   interpolation='none')
+    plt.colorbar(im, ax=ax)
+    plt.xlabel("Frames")
+    plt.ylabel("Channels")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def plot_alignment_to_numpy(alignment, info=None):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger('matplotlib')
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    im = ax.imshow(alignment.transpose(), aspect='auto', origin='lower',
+                   interpolation='none')
+    fig.colorbar(im, ax=ax)
+    xlabel = 'Decoder timestep'
+    if info is not None:
+        xlabel += '\n\n' + info
+    plt.xlabel(xlabel)
+    plt.ylabel('Encoder timestep')
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def load_wav_to_torch(full_path):
+    sampling_rate, data = read(full_path)
+    return torch.FloatTensor(data.astype(np.float32)), sampling_rate
+
+
+def load_filepaths_and_text(filename, split="|"):
+    with open(filename, encoding='utf-8') as f:
+        filepaths_and_text = [line.strip().split(split) for line in f]
+    return filepaths_and_text
+
+
+def str2bool(v):
+    if isinstance(v, bool):
+        return v
+    if v.lower() in ('yes', 'true', 't', 'y', '1'):
+        return True
+    elif v.lower() in ('no', 'false', 'f', 'n', '0'):
+        return False
+    else:
+        raise argparse.ArgumentTypeError('Boolean value expected.')
+
+
+def get_hparams(init=True):
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-c', '--config', type=str, default="./configs/modified_finetune_speaker.json",
+                        help='JSON file for configuration')
+    parser.add_argument('-m', '--model', type=str, default="pretrained_models",
+                        help='Model name')
+    parser.add_argument('-n', '--max_epochs', type=int, default=50,
+                        help='finetune epochs')
+    parser.add_argument('--cont', type=str2bool, default=False, help='whether to continue training on the latest checkpoint')
+    parser.add_argument('--drop_speaker_embed', type=str2bool, default=False, help='whether to drop existing characters')
+    parser.add_argument('--train_with_pretrained_model', type=str2bool, default=True,
+                        help='whether to train with pretrained model')
+    parser.add_argument('--preserved', type=int, default=4,
+                        help='Number of preserved models')
+
+    args = parser.parse_args()
+    model_dir = os.path.join("./", args.model)
+
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+
+    config_path = args.config
+    config_save_path = os.path.join(model_dir, "config.json")
+    if init:
+        with open(config_path, "r") as f:
+            data = f.read()
+        with open(config_save_path, "w") as f:
+            f.write(data)
+    else:
+        with open(config_save_path, "r") as f:
+            data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = model_dir
+    hparams.max_epochs = args.max_epochs
+    hparams.cont = args.cont
+    hparams.drop_speaker_embed = args.drop_speaker_embed
+    hparams.train_with_pretrained_model = args.train_with_pretrained_model
+    hparams.preserved = args.preserved
+    return hparams
+
+
+def get_hparams_from_dir(model_dir):
+    config_save_path = os.path.join(model_dir, "config.json")
+    with open(config_save_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = model_dir
+    return hparams
+
+
+def get_hparams_from_file(config_path):
+    with open(config_path, "r", encoding="utf-8") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    return hparams
+
+
+def check_git_hash(model_dir):
+    source_dir = os.path.dirname(os.path.realpath(__file__))
+    if not os.path.exists(os.path.join(source_dir, ".git")):
+        logger.warn("{} is not a git repository, therefore hash value comparison will be ignored.".format(
+            source_dir
+        ))
+        return
+
+    cur_hash = subprocess.getoutput("git rev-parse HEAD")
+
+    path = os.path.join(model_dir, "githash")
+    if os.path.exists(path):
+        saved_hash = open(path).read()
+        if saved_hash != cur_hash:
+            logger.warn("git hash values are different. {}(saved) != {}(current)".format(
+                saved_hash[:8], cur_hash[:8]))
+    else:
+        open(path, "w").write(cur_hash)
+
+
+def get_logger(model_dir, filename="train.log"):
+    global logger
+    logger = logging.getLogger(os.path.basename(model_dir))
+    logger.setLevel(logging.DEBUG)
+
+    formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    h = logging.FileHandler(os.path.join(model_dir, filename))
+    h.setLevel(logging.DEBUG)
+    h.setFormatter(formatter)
+    logger.addHandler(h)
+    return logger
+
+
+class HParams():
+    def __init__(self, **kwargs):
+        for k, v in kwargs.items():
+            if type(v) == dict:
+                v = HParams(**v)
+            self[k] = v
+
+    def keys(self):
+        return self.__dict__.keys()
+
+    def items(self):
+        return self.__dict__.items()
+
+    def values(self):
+        return self.__dict__.values()
+
+    def __len__(self):
+        return len(self.__dict__)
+
+    def __getitem__(self, key):
+        return getattr(self, key)
+
+    def __setitem__(self, key, value):
+        return setattr(self, key, value)
+
+    def __contains__(self, key):
+        return key in self.__dict__
+
+    def __repr__(self):
+        return self.__dict__.__repr__()
\ No newline at end of file