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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "w41HoLsbD5lw"
},
"source": [
"#The code used below is from Cuong's repo"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "RIGAqwoR9Em3",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "44409566-22f1-4a6a-f8d0-bb695b04b6b8"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"fatal: destination path 'GI-RVC-models' already exists and is not an empty directory.\n"
]
}
],
"source": [
"!git clone https://huggingface.co/vunhucuongit/GI-RVC-models"
]
},
{
"cell_type": "code",
"source": [
"%cd /content/GI-RVC-models\n",
"!git fetch --all\n",
"!git pull"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6GVGWwopY2qn",
"outputId": "f09c5c25-5366-4553-c915-8e5064d69992"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/GI-RVC-models\n",
"Fetching origin\n",
"\u001b[33mhint: You have divergent branches and need to specify how to reconcile them.\u001b[m\n",
"\u001b[33mhint: You can do so by running one of the following commands sometime before\u001b[m\n",
"\u001b[33mhint: your next pull:\u001b[m\n",
"\u001b[33mhint: \u001b[m\n",
"\u001b[33mhint: git config pull.rebase false # merge (the default strategy)\u001b[m\n",
"\u001b[33mhint: git config pull.rebase true # rebase\u001b[m\n",
"\u001b[33mhint: git config pull.ff only # fast-forward only\u001b[m\n",
"\u001b[33mhint: \u001b[m\n",
"\u001b[33mhint: You can replace \"git config\" with \"git config --global\" to set a default\u001b[m\n",
"\u001b[33mhint: preference for all repositories. You can also pass --rebase, --no-rebase,\u001b[m\n",
"\u001b[33mhint: or --ff-only on the command line to override the configured default per\u001b[m\n",
"\u001b[33mhint: invocation.\u001b[m\n",
"fatal: Need to specify how to reconcile divergent branches.\n"
]
}
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "PQQbI96A9dyZ"
},
"outputs": [],
"source": [
"!python -m pip install -U pip wheel\n",
"%pip install -U ipython"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "uVRmSaNJilqN",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "94948bad-9b3d-4d58-b135-88f6e6f16e82"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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" Downloading scipy-1.9.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (33.7 MB)\n",
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" Obtaining dependency information for gradio==3.36.1 from https://files.pythonhosted.org/packages/98/ad/be1bdac5810d3b8497a8a1361e922180f43ec8634cca28cc6b5de68cb18d/gradio-3.36.1-py3-none-any.whl.metadata\n",
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" Obtaining dependency information for tensorboardX from https://files.pythonhosted.org/packages/44/71/f3e7c9b2ab67e28c572ab4e9d5fa3499e0d252650f96d8a3a03e26677f53/tensorboardX-2.6.2.2-py2.py3-none-any.whl.metadata\n",
" Downloading tensorboardX-2.6.2.2-py2.py3-none-any.whl.metadata (5.8 kB)\n",
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" Obtaining dependency information for torchcrepe from https://files.pythonhosted.org/packages/e0/9a/494062efd4bcd3cda13a632249646e1d7cef1746a6537aecf823c11772a8/torchcrepe-0.0.21-py3-none-any.whl.metadata\n",
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" Obtaining dependency information for onnxruntime from https://files.pythonhosted.org/packages/26/f5/5f0aaf4cbd0017258619a0bfe117e1263035bd501a480eead0799c140025/onnxruntime-1.16.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata\n",
" Downloading onnxruntime-1.16.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.0 kB)\n",
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" Obtaining dependency information for yt_dlp from https://files.pythonhosted.org/packages/70/b4/94e72fd0e1541ab50f8efe224ead550a367da3df1b8aa733bd2d9bde9aed/yt_dlp-2023.9.24-py2.py3-none-any.whl.metadata\n",
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"\u001b[?25hBuilding wheels for collected packages: fairseq, pyworld, ffmpeg, demucs, antlr4-python3-runtime, julius, dora-search, ffmpy, treetable\n",
" Building wheel for fairseq (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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" Stored in directory: /root/.cache/pip/wheels/e4/35/55/9c66f65ec7c83fd6fbc2b9502a0ac81b2448a1196159dacc32\n",
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" Stored in directory: /root/.cache/pip/wheels/35/48/7e/e25bdd25fda4326d47010c157709436a6ee7a1423e18a24195\n",
" Building wheel for ffmpeg (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for ffmpeg: filename=ffmpeg-1.4-py3-none-any.whl size=6082 sha256=0619626703f5b5def11a7ef34dcd20f4598e43dfb7229d0a7f52747b3e64f3a8\n",
" Stored in directory: /root/.cache/pip/wheels/8e/7a/69/cd6aeb83b126a7f04cbe7c9d929028dc52a6e7d525ff56003a\n",
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" Created wheel for demucs: filename=demucs-4.0.1-py3-none-any.whl size=78390 sha256=1d509af8473fa4346d06ffef027c23b62a32382135d38dc3d6c99993a815e06b\n",
" Stored in directory: /root/.cache/pip/wheels/2a/65/a1/6cc0e525a84375af3b09823b3326b0ece53c4e68302c054548\n",
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" Stored in directory: /root/.cache/pip/wheels/a7/20/bd/e1477d664f22d99989fd28ee1a43d6633dddb5cb9e801350d5\n",
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" Stored in directory: /root/.cache/pip/wheels/b9/b2/05/f883527ffcb7f2ead5438a2c23439aa0c881eaa9a4c80256f4\n",
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" Created wheel for dora-search: filename=dora_search-0.1.12-py3-none-any.whl size=75090 sha256=4b7e4dbfbd4fd8927ddcf3035beae39375b44dba08b75fc7f2d5f19a6f8287b5\n",
" Stored in directory: /root/.cache/pip/wheels/b1/c2/c0/bea5cc405497284d584b958f293ef32c23bad42ae5e44d973c\n",
" Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=d66f349cb48666049f8fce5b7bd9315eb081b56a41dd90379af7a03b5e0b8d8b\n",
" Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n",
" Building wheel for treetable (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for treetable: filename=treetable-0.2.5-py3-none-any.whl size=7333 sha256=2800a43978401cace34eb736b56446974e355b3daf0d3bcb9358b23689076528\n",
" Stored in directory: /root/.cache/pip/wheels/72/55/0e/91c3655bdb162446f8a7cd477579397544454a63ae7c599c0c\n",
"Successfully built fairseq pyworld ffmpeg demucs antlr4-python3-runtime julius dora-search ffmpy treetable\n",
"\u001b[33mDEPRECATION: omegaconf 2.0.6 has a non-standard dependency specifier PyYAML>=5.1.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of omegaconf or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
"\u001b[0mInstalling collected packages: rfc3986, pydub, lameenc, ffmpy, ffmpeg, faiss-cpu, brotli, bitarray, antlr4-python3-runtime, websockets, treetable, tensorboardX, submitit, semantic-version, scipy, retrying, pyworld, python-multipart, pycryptodomex, praat-parselmouth, portalocker, orjson, omegaconf, mutagen, markdown-it-py, humanfriendly, h11, einops, colorama, aiofiles, yt_dlp, uvicorn, starlette, sacrebleu, resampy, mdit-py-plugins, hydra-core, huggingface-hub, httpcore, coloredlogs, onnxruntime, librosa, httpx, fastapi, edge-tts, gradio-client, gradio, openunmix, julius, dora-search, torchcrepe, fairseq, demucs\n",
" Attempting uninstall: scipy\n",
" Found existing installation: scipy 1.11.2\n",
" Uninstalling scipy-1.11.2:\n",
" Successfully uninstalled scipy-1.11.2\n",
" Attempting uninstall: markdown-it-py\n",
" Found existing installation: markdown-it-py 3.0.0\n",
" Uninstalling markdown-it-py-3.0.0:\n",
" Successfully uninstalled markdown-it-py-3.0.0\n",
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" Found existing installation: mdit-py-plugins 0.4.0\n",
" Uninstalling mdit-py-plugins-0.4.0:\n",
" Successfully uninstalled mdit-py-plugins-0.4.0\n",
" Attempting uninstall: librosa\n",
" Found existing installation: librosa 0.10.1\n",
" Uninstalling librosa-0.10.1:\n",
" Successfully uninstalled librosa-0.10.1\n",
"Successfully installed aiofiles-23.2.1 antlr4-python3-runtime-4.8 bitarray-2.8.1 brotli-1.1.0 colorama-0.4.6 coloredlogs-15.0.1 demucs-4.0.1 dora-search-0.1.12 edge-tts-6.1.8 einops-0.7.0 fairseq-0.12.2 faiss-cpu-1.7.3 fastapi-0.103.2 ffmpeg-1.4 ffmpy-0.3.1 gradio-3.36.1 gradio-client-0.5.3 h11-0.12.0 httpcore-0.15.0 httpx-0.23.0 huggingface-hub-0.17.3 humanfriendly-10.0 hydra-core-1.0.7 julius-0.2.7 lameenc-1.6.1 librosa-0.9.1 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 mutagen-1.47.0 omegaconf-2.0.6 onnxruntime-1.16.0 openunmix-1.2.1 orjson-3.9.7 portalocker-2.8.2 praat-parselmouth-0.4.3 pycryptodomex-3.19.0 pydub-0.25.1 python-multipart-0.0.6 pyworld-0.3.2 resampy-0.4.2 retrying-1.3.4 rfc3986-1.5.0 sacrebleu-2.3.1 scipy-1.9.3 semantic-version-2.10.0 starlette-0.27.0 submitit-1.4.6 tensorboardX-2.6.2.2 torchcrepe-0.0.21 treetable-0.2.5 uvicorn-0.23.2 websockets-11.0.3 yt_dlp-2023.9.24\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m"
]
}
],
"source": [
"!pip install -r /content/GI-RVC-models/requirements.txt"
]
},
{
"cell_type": "code",
"source": [
"#@title Run Gradio\n",
"%cd /content/GI-RVC-models\n",
"!python app-full.py --colab"
],
"metadata": {
"id": "fW87HQ7uXWqC",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "eeee59bb-a0cd-44a5-b9d1-5e99d82abcef"
},
"execution_count": 20,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/GI-RVC-models\n",
"2023-10-03 08:00:56.866725: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
"To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
"2023-10-03 08:00:57.845883: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
"2023-10-03 08:00:59 | INFO | faiss.loader | Loading faiss with AVX2 support.\n",
"2023-10-03 08:00:59 | INFO | faiss.loader | Successfully loaded faiss with AVX2 support.\n",
"Found GPU Tesla T4\n",
"2023-10-03 08:01:00 | INFO | fairseq.tasks.hubert_pretraining | current directory is /content/GI-RVC-models\n",
"2023-10-03 08:01:00 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': 'metadata', 'fine_tuning': False, 'labels': ['km'], 'label_dir': 'label', 'label_rate': 50.0, 'sample_rate': 16000, 'normalize': False, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False}\n",
"2023-10-03 08:01:00 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50.0, 'extractor_mode': default, 'encoder_layers': 12, 'encoder_embed_dim': 768, 'encoder_ffn_embed_dim': 3072, 'encoder_attention_heads': 12, 'activation_fn': gelu, 'layer_type': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False}\n",
"Traceback (most recent call last):\n",
" File \"/content/GI-RVC-models/app-full.py\", line 339, in <module>\n",
" models = load_model()\n",
" File \"/content/GI-RVC-models/app-full.py\", line 131, in load_model\n",
" cpt = torch.load(f\"weights/{character_name}/{model_name}\", map_location=\"cpu\")\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/serialization.py\", line 791, in load\n",
" with _open_file_like(f, 'rb') as opened_file:\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/serialization.py\", line 271, in _open_file_like\n",
" return _open_file(name_or_buffer, mode)\n",
" File \"/usr/local/lib/python3.10/dist-packages/torch/serialization.py\", line 252, in __init__\n",
" super().__init__(open(name, mode))\n",
"FileNotFoundError: [Errno 2] No such file or directory: 'weights/hutao-jp/hutao-jp.pth'\n"
]
}
]
}
],
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"nbformat": 4,
"nbformat_minor": 0
} |