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Add example file and colab notebook #15

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f1c22a8
Add example file
piwawa Jun 10, 2024
bbc00b9
Create Output files are placed here
piwawa Jun 10, 2024
a47fd89
Add Colab notebook
piwawa Jun 10, 2024
212b1cf
Update BandSplitRNN_colab.ipynb
piwawa Jun 10, 2024
4cf65d2
使用 Colab 创建而成
piwawa Jun 10, 2024
0052998
Add test result
piwawa Jun 10, 2024
f40d006
使用 Colab 创建而成
piwawa Jun 10, 2024
ad48dac
Update README.md
piwawa Jun 10, 2024
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252 changes: 252 additions & 0 deletions BandSplitRNN_colab.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4",
"authorship_tag": "ABX9TyMLq7MF871ot43o47kcKnrw",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/piwawa/BandSplitRNN-PyTorch/blob/main/BandSplitRNN_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "wysmkjgFIL47",
"outputId": "0252932f-dac1-4faa-b381-c93ef2a3d79f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'BandSplitRNN-Pytorch'...\n",
"remote: Enumerating objects: 573, done.\u001b[K\n",
"remote: Counting objects: 100% (197/197), done.\u001b[K\n",
"remote: Compressing objects: 100% (50/50), done.\u001b[K\n",
"remote: Total 573 (delta 165), reused 147 (delta 147), pack-reused 376\u001b[K\n",
"Receiving objects: 100% (573/573), 26.56 MiB | 22.15 MiB/s, done.\n",
"Resolving deltas: 100% (345/345), done.\n"
]
}
],
"source": [
"!git clone https://github.com/piwawa/BandSplitRNN-Pytorch"
]
},
{
"cell_type": "code",
"source": [
"%cd BandSplitRNN-Pytorch/src"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "NJfFC62AKnXY",
"outputId": "0895d15e-fdd1-4c79-930f-ead87464e4c9"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/BandSplitRNN-Pytorch/src\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!nvcc -V"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "aCUnN-LRLHHp",
"outputId": "890feeed-a8ec-4c6c-cceb-51ecb03d5293"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"nvcc: NVIDIA (R) Cuda compiler driver\n",
"Copyright (c) 2005-2023 NVIDIA Corporation\n",
"Built on Tue_Aug_15_22:02:13_PDT_2023\n",
"Cuda compilation tools, release 12.2, V12.2.140\n",
"Build cuda_12.2.r12.2/compiler.33191640_0\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!pip install omegaconf hydra-core pytorch_lightning"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "wqAn8pA5JPCJ",
"outputId": "b983a144-b0f1-4afc-9f39-b1e3b27f01f0"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: omegaconf in /usr/local/lib/python3.10/dist-packages (2.3.0)\n",
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"Collecting pytorch_lightning\n",
" Downloading pytorch_lightning-2.2.5-py3-none-any.whl (802 kB)\n",
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"Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.13.0->pytorch_lightning)\n",
" Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
"Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.13.0->pytorch_lightning)\n",
" Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
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" Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
"Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.13.0->pytorch_lightning)\n",
" Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
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" Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
"Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.13.0->pytorch_lightning)\n",
" Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
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" Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
"Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.13.0->pytorch_lightning)\n",
" Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
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"Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>=2022.5.0->pytorch_lightning) (1.4.1)\n",
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"Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.13.0->pytorch_lightning) (1.3.0)\n",
"Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, lightning-utilities, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, torchmetrics, pytorch_lightning\n",
"Successfully installed lightning-utilities-0.11.2 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 pytorch_lightning-2.2.5 torchmetrics-1.4.0.post0\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!gdown --id 14FzOPUcf4BKym1kCRqRH1PeJWSvv4qHE -O saved_models/vocals/vocals_v2.pt"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "WsBywmpnJGNS",
"outputId": "8dde40b2-b388-4eca-8906-8dae72f0b76f"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/usr/local/lib/python3.10/dist-packages/gdown/__main__.py:132: FutureWarning: Option `--id` was deprecated in version 4.3.1 and will be removed in 5.0. You don't need to pass it anymore to use a file ID.\n",
" warnings.warn(\n",
"Downloading...\n",
"From (original): https://drive.google.com/uc?id=14FzOPUcf4BKym1kCRqRH1PeJWSvv4qHE\n",
"From (redirected): https://drive.google.com/uc?id=14FzOPUcf4BKym1kCRqRH1PeJWSvv4qHE&confirm=t&uuid=c84c0534-a5e2-44a3-a676-57b6c99cbe6b\n",
"To: /content/BandSplitRNN-Pytorch/src/saved_models/vocals/vocals_v2.pt\n",
"100% 130M/130M [00:01<00:00, 81.8MB/s]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# replace -i parameter to your own audio, the result will be plated to \"BandSplitRNN-PyTorch/output\"\n",
"!python3 inference.py -i \"../example/谭咏麟-《讲不出再见》 .mp3\" -o ../output/ -t vocals -c saved_models/vocals/vocals_v2.pt -d cuda"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9TozDFxwJfcf",
"outputId": "35b5d4f5-2436-4c99-c871-9e107998924a"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"100% 49/49 [01:19<00:00, 1.61s/it]\n"
]
}
]
}
]
}
2 changes: 2 additions & 0 deletions README.md
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# BandSplitRNN Pytorch

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/piwawa/BandSplitRNN-PyTorch/blob/main/BandSplitRNN_colab.ipynb)

Unofficial PyTorch implementation of the paper [Music Source Separation with Band-split RNN](https://arxiv.org/pdf/2209.15174.pdf).

![architecture](images/architecture.png)
Expand Down
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1 change: 1 addition & 0 deletions output/Output files are placed here
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