update

.ipynb_checkpoints/AVA-checkpoint.py

@@ -3,6 +3,7 @@ import os
 import datasets
 import joblib
 from pathlib import Path
+from tqdm import tqdm
 
 
 _BASE_HF_URL = Path("./data")
@@ -37,7 +38,9 @@ class AVA(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
         archives = dl_manager.download(_DATA_URL)
+        print("Init loading Metadata")
         self.DICT_METADATA = Path(self.dl_manager.download_and_extract(_BASE_HF_URL)) / "metadata.pkl"
+        print("Finish loading Metadata")
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -53,7 +56,7 @@ class AVA(datasets.GeneratorBasedBuilder):
         
         idx = 0
         for archive in archives:
-            for path, file in archive:
+            for path, file in tqdm(archive):
                 if path.endswith(".jpg"):
                     # image filepath format: <IMAGE_FILE NAME>_<SYNSET_ID>.JPEG
                     _id = int(os.path.splitext(b[0])[0].split('/')[-1])

AVA.py

@@ -3,6 +3,7 @@ import os
 import datasets
 import joblib
 from pathlib import Path
+from tqdm import tqdm
 
 
 _BASE_HF_URL = Path("./data")
@@ -37,7 +38,9 @@ class AVA(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
         archives = dl_manager.download(_DATA_URL)
+        print("Init loading Metadata")
         self.DICT_METADATA = Path(self.dl_manager.download_and_extract(_BASE_HF_URL)) / "metadata.pkl"
+        print("Finish loading Metadata")
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -53,7 +56,7 @@ class AVA(datasets.GeneratorBasedBuilder):
         
         idx = 0
         for archive in archives:
-            for path, file in archive:
+            for path, file in tqdm(archive):
                 if path.endswith(".jpg"):
                     # image filepath format: <IMAGE_FILE NAME>_<SYNSET_ID>.JPEG
                     _id = int(os.path.splitext(b[0])[0].split('/')[-1])

notebooks/Test.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 10,
    "id": "aef315bf",
    "metadata": {},
    "outputs": [],
@@ -12,63 +12,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "c0ed6498",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Downloading and preparing dataset ava/default to /home/william/.cache/huggingface/datasets/will33am___ava/default/1.0.0/dc18bb43c11395496a83e96a91fdb26162bab200a16d35297b4d6e6ceccb4864...\n"
-     ]
-    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d06e8600ce884a008bc0356e22aaaf97",
+       "model_id": "50a1f0994d194159b8548ee244ce5212",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Downloading data files:   0%|          | 0/1 [00:00<?, ?it/s]"
+       "Downloading builder script:   0%|          | 0.00/2.14k [00:00<?, ?B/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading and preparing dataset ava/default to /home/william/.cache/huggingface/datasets/will33am___ava/default/1.0.0/e506f33c7289f91cd0c33a5e116547fb1344bc64a605d0ea5bef759973b0e1a1...\n"
+     ]
+    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f139bae410ec45eb81a034742f6ea059",
+       "model_id": "58da99a92ec04b9e809dab1dba2a1663",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Computing checksums:   0%|          | 0/1 [00:01<?, ?it/s]"
+       "Downloading data files:   0%|          | 0/1 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "File \u001b[0;32m<timed exec>:1\u001b[0m\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/load.py:1757\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, **config_kwargs)\u001b[0m\n\u001b[1;32m   1754\u001b[0m try_from_hf_gcs \u001b[38;5;241m=\u001b[39m path \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m _PACKAGED_DATASETS_MODULES\n\u001b[1;32m   1756\u001b[0m \u001b[38;5;66;03m# Download and prepare data\u001b[39;00m\n\u001b[0;32m-> 1757\u001b[0m \u001b[43mbuilder_instance\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1758\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1759\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1760\u001b[0m \u001b[43m    \u001b[49m\u001b[43mignore_verifications\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_verifications\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1761\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtry_from_hf_gcs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtry_from_hf_gcs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1762\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnum_proc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_proc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1763\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1765\u001b[0m \u001b[38;5;66;03m# Build dataset for splits\u001b[39;00m\n\u001b[1;32m   1766\u001b[0m keep_in_memory \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m   1767\u001b[0m     keep_in_memory \u001b[38;5;28;01mif\u001b[39;00m keep_in_memory \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m is_small_dataset(builder_instance\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size)\n\u001b[1;32m   1768\u001b[0m )\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/builder.py:860\u001b[0m, in \u001b[0;36mDatasetBuilder.download_and_prepare\u001b[0;34m(self, output_dir, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)\u001b[0m\n\u001b[1;32m    858\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m num_proc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    859\u001b[0m         prepare_split_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnum_proc\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m num_proc\n\u001b[0;32m--> 860\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    861\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    862\u001b[0m \u001b[43m        \u001b[49m\u001b[43mverify_infos\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    863\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_split_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    864\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdownload_and_prepare_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    865\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    866\u001b[0m \u001b[38;5;66;03m# Sync info\u001b[39;00m\n\u001b[1;32m    867\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39mdataset_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msum\u001b[39m(split\u001b[38;5;241m.\u001b[39mnum_bytes \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minfo\u001b[38;5;241m.\u001b[39msplits\u001b[38;5;241m.\u001b[39mvalues())\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/builder.py:1611\u001b[0m, in \u001b[0;36mGeneratorBasedBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verify_infos, **prepare_splits_kwargs)\u001b[0m\n\u001b[1;32m   1610\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_download_and_prepare\u001b[39m(\u001b[38;5;28mself\u001b[39m, dl_manager, verify_infos, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mprepare_splits_kwargs):\n\u001b[0;32m-> 1611\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_download_and_prepare\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1612\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheck_duplicate_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify_infos\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprepare_splits_kwargs\u001b[49m\n\u001b[1;32m   1613\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/builder.py:931\u001b[0m, in \u001b[0;36mDatasetBuilder._download_and_prepare\u001b[0;34m(self, dl_manager, verify_infos, **prepare_split_kwargs)\u001b[0m\n\u001b[1;32m    929\u001b[0m split_dict \u001b[38;5;241m=\u001b[39m SplitDict(dataset_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname)\n\u001b[1;32m    930\u001b[0m split_generators_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_split_generators_kwargs(prepare_split_kwargs)\n\u001b[0;32m--> 931\u001b[0m split_generators \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_split_generators\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdl_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msplit_generators_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    933\u001b[0m \u001b[38;5;66;03m# Checksums verification\u001b[39;00m\n\u001b[1;32m    934\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m verify_infos \u001b[38;5;129;01mand\u001b[39;00m dl_manager\u001b[38;5;241m.\u001b[39mrecord_checksums:\n",
-      "File \u001b[0;32m~/.cache/huggingface/modules/datasets_modules/datasets/will33am--AVA/dc18bb43c11395496a83e96a91fdb26162bab200a16d35297b4d6e6ceccb4864/AVA.py:39\u001b[0m, in \u001b[0;36mAVA._split_generators\u001b[0;34m(self, dl_manager)\u001b[0m\n\u001b[1;32m     37\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_split_generators\u001b[39m(\u001b[38;5;28mself\u001b[39m, dl_manager):\n\u001b[1;32m     38\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Returns SplitGenerators.\"\"\"\u001b[39;00m\n\u001b[0;32m---> 39\u001b[0m     archives \u001b[38;5;241m=\u001b[39m \u001b[43mdl_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_DATA_URL\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     41\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m [\n\u001b[1;32m     42\u001b[0m         datasets\u001b[38;5;241m.\u001b[39mSplitGenerator(\n\u001b[1;32m     43\u001b[0m             name\u001b[38;5;241m=\u001b[39mdatasets\u001b[38;5;241m.\u001b[39mSplit\u001b[38;5;241m.\u001b[39mTRAIN,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     48\u001b[0m         )\n\u001b[1;32m     49\u001b[0m         ]\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/download/download_manager.py:346\u001b[0m, in \u001b[0;36mDownloadManager.download\u001b[0;34m(self, url_or_urls)\u001b[0m\n\u001b[1;32m    343\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdownloaded_paths\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;28mdict\u001b[39m(\u001b[38;5;28mzip\u001b[39m(url_or_urls\u001b[38;5;241m.\u001b[39mflatten(), downloaded_path_or_paths\u001b[38;5;241m.\u001b[39mflatten())))\n\u001b[1;32m    345\u001b[0m start_time \u001b[38;5;241m=\u001b[39m datetime\u001b[38;5;241m.\u001b[39mnow()\n\u001b[0;32m--> 346\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_record_sizes_checksums\u001b[49m\u001b[43m(\u001b[49m\u001b[43murl_or_urls\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdownloaded_path_or_paths\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    347\u001b[0m duration \u001b[38;5;241m=\u001b[39m datetime\u001b[38;5;241m.\u001b[39mnow() \u001b[38;5;241m-\u001b[39m start_time\n\u001b[1;32m    348\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mChecksum Computation took \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mduration\u001b[38;5;241m.\u001b[39mtotal_seconds()\u001b[38;5;250m \u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;241m60\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m min\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/download/download_manager.py:246\u001b[0m, in \u001b[0;36mDownloadManager._record_sizes_checksums\u001b[0;34m(self, url_or_urls, downloaded_path_or_paths)\u001b[0m\n\u001b[1;32m    238\u001b[0m delay \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m\n\u001b[1;32m    239\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m url, path \u001b[38;5;129;01min\u001b[39;00m tqdm(\n\u001b[1;32m    240\u001b[0m     \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mzip\u001b[39m(url_or_urls\u001b[38;5;241m.\u001b[39mflatten(), downloaded_path_or_paths\u001b[38;5;241m.\u001b[39mflatten())),\n\u001b[1;32m    241\u001b[0m     delay\u001b[38;5;241m=\u001b[39mdelay,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    244\u001b[0m ):\n\u001b[1;32m    245\u001b[0m     \u001b[38;5;66;03m# call str to support PathLike objects\u001b[39;00m\n\u001b[0;32m--> 246\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_recorded_sizes_checksums[\u001b[38;5;28mstr\u001b[39m(url)] \u001b[38;5;241m=\u001b[39m \u001b[43mget_size_checksum_dict\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    247\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrecord_checksum\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecord_checksums\u001b[49m\n\u001b[1;32m    248\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    249\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m warn_about_checksums \u001b[38;5;129;01mand\u001b[39;00m _time \u001b[38;5;241m+\u001b[39m delay \u001b[38;5;241m<\u001b[39m time\u001b[38;5;241m.\u001b[39mtime():\n\u001b[1;32m    250\u001b[0m         warn_about_checksums \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
-      "File \u001b[0;32m/opt/conda/envs/hugginface/lib/python3.8/site-packages/datasets/utils/info_utils.py:84\u001b[0m, in \u001b[0;36mget_size_checksum_dict\u001b[0;34m(path, record_checksum)\u001b[0m\n\u001b[1;32m     82\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(path, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m     83\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28miter\u001b[39m(\u001b[38;5;28;01mlambda\u001b[39;00m: f\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m<<\u001b[39m \u001b[38;5;241m20\u001b[39m), \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m---> 84\u001b[0m             \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     85\u001b[0m         checksum \u001b[38;5;241m=\u001b[39m m\u001b[38;5;241m.\u001b[39mhexdigest()\n\u001b[1;32m     86\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
     }
    ],
    "source": [
@@ -79,7 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2f025a25",
+   "id": "34fa96b9",
    "metadata": {},
    "outputs": [],
    "source": []