From 31711e7d98cbe88b587962e471af2ba5759a45f5 Mon Sep 17 00:00:00 2001 From: Kevin Wang <126712357+KevinWang676@users.noreply.github.com> Date: Thu, 31 Aug 2023 00:53:33 -0700 Subject: [PATCH] =?UTF-8?q?=E4=BD=BF=E7=94=A8=20Colaboratory=20=E5=88=9B?= =?UTF-8?q?=E5=BB=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...1\237\263\345\205\213\351\232\206v2.ipynb" | 1195 +++++++++++++++++ 1 file changed, 1195 insertions(+) create mode 100644 "Sambert\344\270\255\346\226\207\345\243\260\351\237\263\345\205\213\351\232\206v2.ipynb" diff --git "a/Sambert\344\270\255\346\226\207\345\243\260\351\237\263\345\205\213\351\232\206v2.ipynb" "b/Sambert\344\270\255\346\226\207\345\243\260\351\237\263\345\205\213\351\232\206v2.ipynb" new file mode 100644 index 0000000..c8328f8 --- /dev/null +++ "b/Sambert\344\270\255\346\226\207\345\243\260\351\237\263\345\205\213\351\232\206v2.ipynb" @@ -0,0 +1,1195 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "machine_shape": "hm", + "gpuType": "V100", + "authorship_tag": "ABX9TyPlHFyW04xkOShGFsrqykJH", + "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": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# 全新中文声音克隆 Voice Cloning for Chinese Speech" + ], + "metadata": { + "id": "Uhhc4_stcdSf" + } + }, + { + "cell_type": "markdown", + "source": [ + "## 配置环境 Set up" + ], + "metadata": { + "id": "qIFF53SWVDe-" + } + }, + { + "cell_type": "code", + "source": [ + "! nvidia-smi # 需要使用GPU运行" + ], + "metadata": { + "id": "4RZJ1P69VKLU", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "42ee2dbc-c527-472c-bd1f-a5ccfa37f5ae" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Thu Aug 31 07:46:44 2023 \n", + "+-----------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 525.105.17 Driver Version: 525.105.17 CUDA Version: 12.0 |\n", + "|-------------------------------+----------------------+----------------------+\n", + "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", + "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", + "| | | MIG M. |\n", + "|===============================+======================+======================|\n", + "| 0 Tesla V100-SXM2... Off | 00000000:00:04.0 Off | 0 |\n", + "| N/A 35C P0 24W / 300W | 0MiB / 16384MiB | 0% Default |\n", + "| | | N/A |\n", + "+-------------------------------+----------------------+----------------------+\n", + " \n", + "+-----------------------------------------------------------------------------+\n", + "| Processes: |\n", + "| GPU GI CI PID Type Process name GPU Memory |\n", + "| ID ID Usage |\n", + "|=============================================================================|\n", + "| No running processes found |\n", + "+-----------------------------------------------------------------------------+\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "! pip install openai-whisper\n", + "! pip install modelscope\n", + "! pip install tts-autolabel -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html\n", + "! pip install typeguard==2.3.1\n", + "! pip install sox\n", + "! pip install bitstring\n", + "! pip install pysptk --no-build-isolation\n", + "! pip install kantts -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html\n", + "! pip install pytorch_wavelets\n", + "! pip install tensorboardX\n", + "! git clone https://github.com/fbcotter/pytorch_wavelets\n", + "! pip install matplotlib\n", + "! pip install numpy==1.22.0" + ], + "metadata": { + "id": "s2aAbOEPaVh6", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "outputId": "604b8cc2-6b7a-4185-f14c-c22a51f0b706" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting openai-whisper\n", + " Downloading openai-whisper-20230314.tar.gz (792 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m792.9/792.9 kB\u001b[0m \u001b[31m7.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", + " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", + " 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This behaviour is the source of the following dependency conflicts.\n", + "pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 13.0.0 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed addict-2.4.0 aliyun-python-sdk-core-2.13.36 aliyun-python-sdk-kms-2.16.1 crcmod-1.7 datasets-2.13.0 dill-0.3.6 einops-0.6.1 huggingface-hub-0.16.4 jmespath-0.10.0 modelscope-1.8.4 multiprocess-0.70.14 oss2-2.18.1 pyarrow-13.0.0 pycryptodome-3.18.0 simplejson-3.19.1 xxhash-3.3.0 yapf-0.40.1\n", + "Looking in links: https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html\n", + "Collecting tts-autolabel\n", + " Downloading https://modelscope.oss-cn-beijing.aliyuncs.com/releases/dependencies/kantts/tts_autolabel-1.1.8-py3-none-any.whl (117 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.3/117.3 kB\u001b[0m \u001b[31m216.0 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already 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This behaviour is the source of the following dependency conflicts.\n", + "pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 13.0.0 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed coloredlogs-15.0.1 humanfriendly-10.0 kaldi-native-fbank-1.18.4 nls-fa-0.1 numpy-1.23.1 onnxruntime-1.15.1 sox-1.4.1 tts-autolabel-1.1.8 ttsfrd-0.2.1 typeguard-2.13.3\n" + ] + }, + { + "output_type": "display_data", + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "numpy" + ] + } + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting typeguard==2.3.1\n", + " Downloading typeguard-2.3.1-py3-none-any.whl (10 kB)\n", + "Installing collected packages: typeguard\n", + " Attempting uninstall: typeguard\n", + " Found existing installation: typeguard 2.13.3\n", + " Uninstalling typeguard-2.13.3:\n", + " Successfully uninstalled typeguard-2.13.3\n", + "Successfully 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size=1137273 sha256=b57158ca005bb75139e737d40ee28c7fb86b5e166def7734f2a1dfd5997e5812\n", + " Stored in directory: /root/.cache/pip/wheels/aa/96/e5/2348f6f568b9888d3505a97dc53287152ffd0440526cc6105d\n", + "Successfully built pysptk\n", + "Installing collected packages: pysptk\n", + "Successfully installed pysptk-0.2.1\n", + "Looking in links: https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html\n", + "Collecting kantts\n", + " Downloading https://modelscope.oss-cn-beijing.aliyuncs.com/releases/dependencies/kantts/kantts-1.0.1-py3-none-any.whl (147 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m147.2/147.2 kB\u001b[0m \u001b[31m212.0 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: librosa>=0.9.2 in /usr/local/lib/python3.10/dist-packages (from kantts) (0.10.1)\n", + "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from kantts) (3.7.1)\n", + 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collected packages: tensorboardX\n", + "Successfully installed tensorboardX-2.6.2.2\n", + "Cloning into 'pytorch_wavelets'...\n", + "remote: Enumerating objects: 978, done.\u001b[K\n", + "remote: Counting objects: 100% (142/142), done.\u001b[K\n", + "remote: Compressing objects: 100% (96/96), done.\u001b[K\n", + "remote: Total 978 (delta 79), reused 91 (delta 46), pack-reused 836\u001b[K\n", + "Receiving objects: 100% (978/978), 6.80 MiB | 7.11 MiB/s, done.\n", + "Resolving deltas: 100% (663/663), done.\n", + "Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (3.7.1)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.1.0)\n", + "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (0.11.0)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (4.42.1)\n", + "Requirement 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This behaviour is the source of the following dependency conflicts.\n", + "librosa 0.10.1 requires numpy!=1.22.0,!=1.22.1,!=1.22.2,>=1.20.3, but you have numpy 1.22.0 which is incompatible.\n", + "pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 13.0.0 which is incompatible.\n", + "plotnine 0.12.2 requires numpy>=1.23.0, but you have numpy 1.22.0 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed numpy-1.22.0\n" + ] + }, + { + "output_type": "display_data", + "data": { + "application/vnd.colab-display-data+json": { + "pip_warning": { + "packages": [ + "numpy" + ] + } + } + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "!apt-get install sox" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "b4uSdumvUcQC", + "outputId": "df09129e-5df0-44cf-bd46-d5589cb1b438" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Reading package lists... Done\n", + "Building dependency tree... Done\n", + "Reading state information... Done\n", + "The following additional packages will be installed:\n", + " libopencore-amrnb0 libopencore-amrwb0 libsox-fmt-alsa libsox-fmt-base\n", + " libsox3 libwavpack1\n", + "Suggested packages:\n", + " libsox-fmt-all\n", + "The following NEW packages will be installed:\n", + " libopencore-amrnb0 libopencore-amrwb0 libsox-fmt-alsa libsox-fmt-base\n", + " libsox3 libwavpack1 sox\n", + "0 upgraded, 7 newly installed, 0 to remove and 16 not upgraded.\n", + "Need to get 617 kB of archives.\n", + "After this operation, 1,760 kB of additional disk space will be used.\n", + "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopencore-amrnb0 amd64 0.1.5-1 [94.8 kB]\n", + "Get:2 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopencore-amrwb0 amd64 0.1.5-1 [49.1 kB]\n", + "Get:3 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libsox3 amd64 14.4.2+git20190427-2+deb11u2build0.22.04.1 [240 kB]\n", + "Get:4 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libsox-fmt-alsa amd64 14.4.2+git20190427-2+deb11u2build0.22.04.1 [11.2 kB]\n", + "Get:5 http://archive.ubuntu.com/ubuntu jammy/main amd64 libwavpack1 amd64 5.4.0-1build2 [83.7 kB]\n", + "Get:6 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 libsox-fmt-base amd64 14.4.2+git20190427-2+deb11u2build0.22.04.1 [33.7 kB]\n", + "Get:7 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 sox amd64 14.4.2+git20190427-2+deb11u2build0.22.04.1 [104 kB]\n", + "Fetched 617 kB in 1s (580 kB/s)\n", + "Selecting previously unselected package libopencore-amrnb0:amd64.\n", + "(Reading database ... 120831 files and directories currently installed.)\n", + "Preparing to unpack .../0-libopencore-amrnb0_0.1.5-1_amd64.deb ...\n", + "Unpacking libopencore-amrnb0:amd64 (0.1.5-1) ...\n", + "Selecting previously unselected package libopencore-amrwb0:amd64.\n", + "Preparing to unpack .../1-libopencore-amrwb0_0.1.5-1_amd64.deb ...\n", + "Unpacking libopencore-amrwb0:amd64 (0.1.5-1) 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"execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Processing /content/pytorch_wavelets\n", + " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from pytorch-wavelets==1.3.0) (1.22.0)\n", + "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from pytorch-wavelets==1.3.0) (1.16.0)\n", + "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from pytorch-wavelets==1.3.0) (2.0.1+cu118)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (3.12.2)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (4.7.1)\n", + "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (1.12)\n", + "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (3.1)\n", + "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (3.1.2)\n", + "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch->pytorch-wavelets==1.3.0) (2.0.0)\n", + "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->pytorch-wavelets==1.3.0) (3.27.2)\n", + "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch->pytorch-wavelets==1.3.0) (16.0.6)\n", + "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->pytorch-wavelets==1.3.0) (2.1.3)\n", + "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->pytorch-wavelets==1.3.0) (1.3.0)\n", + "Building wheels for collected packages: pytorch-wavelets\n", + " Building wheel for pytorch-wavelets (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for pytorch-wavelets: filename=pytorch_wavelets-1.3.0-py3-none-any.whl size=54852 sha256=6db8460229d2f3b684b7c3e8ef429bb0dee02914a30baba28db7994e49ea6ae9\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-2bodt4br/wheels/f6/77/89/ac0462961f441a5dd4d226216613ef64f3eb2c7f2883efcebf\n", + "Successfully built pytorch-wavelets\n", + "Installing collected packages: pytorch-wavelets\n", + " Attempting uninstall: pytorch-wavelets\n", + " Found existing installation: pytorch-wavelets 1.3.0\n", + " Uninstalling pytorch-wavelets-1.3.0:\n", + " Successfully uninstalled pytorch-wavelets-1.3.0\n", + "Successfully installed pytorch-wavelets-1.3.0\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import os\n", + "os._exit(00) # 重启notebook" + ], + "metadata": { + "id": "lO29uxHrVafx" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "import sox" + ], + "metadata": { + "id": "UsOLbeoYFO04" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "## 对音频切片处理" + ], + "metadata": { + "id": "YZqH0DtGcsXJ" + } + }, + { + "cell_type": "code", + "source": [ + "import subprocess\n", + "from pathlib import Path\n", + "import librosa\n", + "from scipy.io import wavfile\n", + "import numpy as np\n", + "import torch\n", + "import csv\n", + "import whisper\n", + "\n", + "def split_long_audio(model, filepaths, save_dir=\"data_dir\", out_sr=44100):\n", + " if isinstance(filepaths, str):\n", + " filepaths = [filepaths]\n", + "\n", + " for file_idx, filepath in enumerate(filepaths):\n", + "\n", + " save_path = Path(save_dir)\n", + " save_path.mkdir(exist_ok=True, parents=True)\n", + "\n", + " print(f\"Transcribing file {file_idx}: '{filepath}' to segments...\")\n", + " result = model.transcribe(filepath, word_timestamps=True, task=\"transcribe\", beam_size=5, best_of=5)\n", + " segments = result['segments']\n", + "\n", + " wav, sr = librosa.load(filepath, sr=None, offset=0, duration=None, mono=True)\n", + " wav, _ = librosa.effects.trim(wav, top_db=20)\n", + " peak = np.abs(wav).max()\n", + " if peak > 1.0:\n", + " wav = 0.98 * wav / peak\n", + " wav2 = librosa.resample(wav, orig_sr=sr, target_sr=out_sr)\n", + " wav2 /= max(wav2.max(), -wav2.min())\n", + "\n", + " for i, seg in enumerate(segments):\n", + " start_time = seg['start']\n", + " end_time = seg['end']\n", + " wav_seg = wav2[int(start_time * out_sr):int(end_time * out_sr)]\n", + " wav_seg_name = f\"{file_idx}_{i}.wav\"\n", + " out_fpath = save_path / wav_seg_name\n", + " wavfile.write(out_fpath, rate=out_sr, data=(wav_seg * np.iinfo(np.int16).max).astype(np.int16))" + ], + "metadata": { + "id": "NdoD-ZnIaWhN" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "whisper_size = \"medium\"\n", + "whisper_model = whisper.load_model(whisper_size)" + ], + "metadata": { + "id": "yXrxpjEGaWlT", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "5fa21ff1-9b8b-4e5a-c45f-c97951ea12e2" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "100%|██████████████████████████████████████| 1.42G/1.42G [00:08<00:00, 190MiB/s]\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## 需要新建两个文件夹，分别是：\"output_training_data\", \"pretrain_work_dir\"" + ], + "metadata": { + "id": "ccQC4ZcWbtXy" + } + }, + { + "cell_type": "code", + "source": [ + "from modelscope.tools import run_auto_label\n", + "\n", + "import os\n", + "from modelscope.models.audio.tts import SambertHifigan\n", + "from modelscope.pipelines import pipeline\n", + "from modelscope.utils.constant import Tasks\n", + "\n", + "from modelscope.metainfo import Trainers\n", + "from modelscope.trainers import build_trainer\n", + "from modelscope.utils.audio.audio_utils import TtsTrainType\n", + "\n", + "pretrained_model_id = 'damo/speech_personal_sambert-hifigan_nsf_tts_zh-cn_pretrain_16k'\n", + "\n", + "dataset_id = \"./output_training_data/\"\n", + "pretrain_work_dir = \"./pretrain_work_dir/\"\n", + "\n" + ], + "metadata": { + "id": "X6U1kIM8ouSs", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "7edf72aa-df6e-465c-90a8-4114beb17112" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "2023-08-31 07:49:43,205 - modelscope - INFO - PyTorch version 2.0.1+cu118 Found.\n", + "2023-08-31 07:49:43,208 - modelscope - INFO - TensorFlow version 2.12.0 Found.\n", + "2023-08-31 07:49:43,209 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer\n", + "2023-08-31 07:49:43,212 - modelscope - INFO - No valid ast index found from /root/.cache/modelscope/ast_indexer, generating ast index from prebuilt!\n", + "2023-08-31 07:49:43,268 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 0b679d299d0b8626e3c5221da77c0ae7 and a total number of 902 components indexed\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "def auto_label(audio):\n", + " try:\n", + " split_long_audio(whisper_model, audio, \"test_wavs\")\n", + " os.makedirs(\"output_training_data\", exist_ok=True)\n", + " input_wav = \"./test_wavs/\"\n", + " output_data = \"./output_training_data/\"\n", + " ret, report = run_auto_label(input_wav=input_wav, work_dir=output_data, resource_revision=\"v1.0.7\")\n", + "\n", + " except Exception:\n", + " pass\n", + " return \"标注成功\"" + ], + "metadata": { + "id": "uq5Jdd7umcvj" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def train(a):\n", + " try:\n", + " os.makedirs(\"pretrain_work_dir\", exist_ok=True)\n", + "\n", + " train_info = {\n", + " TtsTrainType.TRAIN_TYPE_SAMBERT: { # 配置训练AM（sambert）模型\n", + " 'train_steps': 52, # 训练多少个step\n", + " 'save_interval_steps': 50, # 每训练多少个step保存一次checkpoint\n", + " 'log_interval': 10 # 每训练多少个step打印一次训练日志\n", + " }\n", + " }\n", + "\n", + " # 配置训练参数，指定数据集，临时工作目录和train_info\n", + " kwargs = dict(\n", + " model=pretrained_model_id, # 指定要finetune的模型\n", + " model_revision = \"v1.0.6\",\n", + " work_dir=pretrain_work_dir, # 指定临时工作目录\n", + " train_dataset=dataset_id, # 指定数据集id\n", + " train_type=train_info # 指定要训练类型及参数\n", + " )\n", + "\n", + " trainer = build_trainer(Trainers.speech_kantts_trainer,\n", + " default_args=kwargs)\n", + "\n", + " trainer.train()\n", + "\n", + " except Exception:\n", + " pass\n", + "\n", + " return \"训练完成\"\n" + ], + "metadata": { + "id": "36jXpTLyoO3s" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "\n", + "def infer(text):\n", + "\n", + " model_dir = os.path.abspath(\"./pretrain_work_dir\")\n", + "\n", + " custom_infer_abs = {\n", + " 'voice_name':\n", + " 'F7',\n", + " 'am_ckpt':\n", + " os.path.join(model_dir, 'tmp_am', 'ckpt'),\n", + " 'am_config':\n", + " os.path.join(model_dir, 'tmp_am', 'config.yaml'),\n", + " 'voc_ckpt':\n", + " os.path.join(model_dir, 'orig_model', 'basemodel_16k', 'hifigan', 'ckpt'),\n", + " 'voc_config':\n", + " os.path.join(model_dir, 'orig_model', 'basemodel_16k', 'hifigan',\n", + " 'config.yaml'),\n", + " 'audio_config':\n", + " os.path.join(model_dir, 'data', 'audio_config.yaml'),\n", + " 'se_file':\n", + " os.path.join(model_dir, 'data', 'se', 'se.npy')\n", + " }\n", + " kwargs = {'custom_ckpt': custom_infer_abs}\n", + "\n", + " model_id = SambertHifigan(os.path.join(model_dir, \"orig_model\"), **kwargs)\n", + "\n", + " inference = pipeline(task=Tasks.text_to_speech, model=model_id)\n", + " output = inference(input=text)\n", + "\n", + " filename = str(random.randint(1, 1000000000000))\n", + "\n", + " with open(filename + \"myfile.wav\", mode='bx') as f:\n", + " f.write(output[\"output_wav\"])\n", + " return filename + \"myfile.wav\"\n" + ], + "metadata": { + "id": "qw7KYommooFU" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "pip install gradio" + ], + "metadata": { + "id": "GNJhguT6q4ej", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "cba0f880-4dc5-40a1-9fa5-2d2c42b556a4" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting gradio\n", + " Downloading gradio-3.41.2-py3-none-any.whl (20.1 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m20.1/20.1 MB\u001b[0m \u001b[31m42.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hCollecting aiofiles<24.0,>=22.0 (from gradio)\n", + " Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n", + "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n", + "Collecting fastapi (from gradio)\n", + " Downloading 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exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5.0,>=3.0->httpcore<0.18.0,>=0.15.0->httpx->gradio) (1.1.3)\n", + "Building wheels for collected packages: ffmpy\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=050e26280ad1f47f4cc51ef4bd0044dadd4befcb088f21983acc55ff71a10c87\n", + " Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n", + "Successfully built ffmpy\n", + "Installing collected packages: pydub, ffmpy, websockets, semantic-version, python-multipart, orjson, h11, aiofiles, uvicorn, starlette, httpcore, httpx, fastapi, gradio-client, gradio\n", + "Successfully installed aiofiles-23.2.1 fastapi-0.103.0 ffmpy-0.3.1 gradio-3.41.2 gradio-client-0.5.0 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 orjson-3.9.5 pydub-0.25.1 python-multipart-0.0.6 semantic-version-2.10.0 starlette-0.27.0 uvicorn-0.23.2 websockets-11.0.3\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import gradio as gr" + ], + "metadata": { + "id": "e30tBe6vtzGU" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "app = gr.Blocks()\n", + "\n", + "with app:\n", + " gr.Markdown(\"#
🥳🎶🎡 - Sambert中文声音克隆
\")\n", + " gr.Markdown(\"##
🌟 - 训练3分钟，推理5秒钟，中英自然发音
\")\n", + " gr.Markdown(\"###
🌊 - 更多精彩应用，敬请关注[滔滔AI](http://www.talktalkai.com)；滔滔AI，为爱滔滔！💕
\")\n", + "\n", + " with gr.Row():\n", + " inp1 = gr.Audio(type=\"filepath\", label=\"请上传一段音频\")\n", + " out1 = gr.Textbox(label=\"标注情况\", lines=1, interactive=False)\n", + "\n", + " out2 = gr.Textbox(label=\"训练情况\", lines=1, interactive=False)\n", + " inp2 = gr.Textbox(label=\"文本\", lines=3)\n", + " out3 = gr.Audio(type=\"filepath\", label=\"合成的音频\")\n", + " btn1 = gr.Button(\"标注数据\")\n", + " btn2 = gr.Button(\"训练\")\n", + " btn3 = gr.Button(\"推理\")\n", + "\n", + " btn1.click(auto_label, inp1, out1)\n", + " btn2.click(train, out1, out2)\n", + " btn3.click(infer, inp2, out3)\n", + "\n", + " gr.Markdown(\"###
注意❗：请不要生成会对个人以及组织造成侵害的内容，此程序仅供科研、学习及个人娱乐使用。
\")\n", + " gr.HTML('''\n", + "
\n", + "

🌊🏞️🎶 - 江水东流急，滔滔无尽声。 明·顾璘\n", + "

\n", + "
\n", + " ''')\n", + "app.launch(show_error=True)" + ], + "metadata": { + "id": "P03LT9IOrq2C", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 617 + }, + "outputId": "1a0453cf-b81e-442b-e1fe-130dea4be07a" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n", + "Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "application/javascript": [ + "(async (port, path, width, height, cache, element) => {\n", + " if (!google.colab.kernel.accessAllowed && !cache) {\n", + " return;\n", + " }\n", + " element.appendChild(document.createTextNode(''));\n", + " const url = await google.colab.kernel.proxyPort(port, {cache});\n", + "\n", + " const external_link = document.createElement('div');\n", + " external_link.innerHTML = `\n", + "
\n", + " Running on \n", + " https://localhost:${port}${path}\n", + " \n", + "
\n", + " `;\n", + " element.appendChild(external_link);\n", + "\n", + " const iframe = document.createElement('iframe');\n", + " iframe.src = new URL(path, url).toString();\n", + " iframe.height = height;\n", + " iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n", + " iframe.width = width;\n", + " iframe.style.border = 0;\n", + " element.appendChild(iframe);\n", + " })(7860, \"/\", \"100%\", 500, false, window.element)" + ] + }, + "metadata": {} + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [] + }, + "metadata": {}, + "execution_count": 12 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#infer(\"欢迎使用滔滔智能的声音克隆产品\")" + ], + "metadata": { + "id": "YCm0L5U9tmP9" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "onmCp6Ou2Lqb" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file