diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 00000000..4dc68c6f --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,2 @@ +# Changelog + diff --git a/README.md b/README.md index 55537877..cca1cb53 100644 --- a/README.md +++ b/README.md @@ -171,7 +171,7 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision - 👏🏻 2021.12.10: PaddleSpeech CLI is available for Audio Classification, Automatic Speech Recognition, Speech Translation (English to Chinese) and Text-to-Speech. ### Community -- Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation. +- Scan the QR code below with your Wechat (reply【语音】after your friend's application is approved), you can access to official technical exchange group. Look forward to your participation.
diff --git a/README_cn.md b/README_cn.md index d947356b..ddf189c3 100644 --- a/README_cn.md +++ b/README_cn.md @@ -175,7 +175,7 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme - 👏🏻 2021.12.10: PaddleSpeech CLI 上线！覆盖了声音分类、语音识别、语音翻译（英译中）以及语音合成。 ### 技术交流群 -微信扫描二维码加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。 +微信扫描二维码（好友申请通过后回复【语音】）加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
diff --git a/docs/source/install.md b/docs/source/install.md index 05f9471e..bdeb37ce 100644 --- a/docs/source/install.md +++ b/docs/source/install.md @@ -6,7 +6,7 @@ There are 3 ways to use `PaddleSpeech`. According to the degree of difficulty, t |:---- |:----------------------------------------------------------- |:----| | Easy | (1) Use command-line functions of PaddleSpeech.
(2) Experience PaddleSpeech on Ai Studio. | Linux, Mac(not support M1 chip)，Windows | | Medium | Support major functions ，such as using the` ready-made `examples and using PaddleSpeech to train your model. | Linux | -| Hard | Support full function of Paddlespeech，including training n-gram language model, Montreal-Forced-Aligner, and so on. And you are more able to be a developer! | Ubuntu | +| Hard | Support full function of Paddlespeech, including using join ctc decoder with kaldi, training n-gram language model, Montreal-Forced-Aligner, and so on. And you are more able to be a developer! | Ubuntu | ## Prerequisites - Python >= 3.7 @@ -52,12 +52,19 @@ sudo apt install build-essential conda install -y -c gcc_linux-64=8.4.0 gxx_linux-64=8.4.0 ``` ### Install PaddleSpeech -You can use the following command: +Some users may fail to install `kaldiio` due to the default download source, you can install `pytest-runner` at first； +```bash +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple +``` +Then you can use the following commands: ```bash pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple pip install paddlespeech -i https://pypi.tuna.tsinghua.edu.cn/simple ``` > If you encounter problem with downloading **nltk_data** while using paddlespeech, it maybe due to your poor network, we suggest you download the [nltk_data](https://paddlespeech.bj.bcebos.com/Parakeet/tools/nltk_data.tar.gz) provided by us, and extract it to your `${HOME}`. + +> If you fail to install paddlespeech-ctcdecoders, it doesn't matter. + ## Medium: Get the Major Functions (Support Linux) If you want to get the major function of `paddlespeech`, you need to do following steps: ### Git clone PaddleSpeech @@ -117,6 +124,8 @@ python3 -m pip install paddlepaddle-gpu==2.2.0 -i https://mirror.baidu.com/pypi/ ### Install PaddleSpeech You can install `paddlespeech` by the following command，then you can use the `ready-made` examples in `paddlespeech` : ```bash +# Some users may fail to install `kaldiio` due to the default download source, you can install `pytest-runner` at first； +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple # Make sure you are in the root directory of PaddleSpeech pip install . -i https://pypi.tuna.tsinghua.edu.cn/simple ``` @@ -182,8 +191,11 @@ conda activate tools/venv conda install -y -c conda-forge sox libsndfile swig bzip2 libflac bc ``` ### Install PaddlePaddle +Some users may fail to install `kaldiio` due to the default download source, you can install `pytest-runner` at first； +```bash +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple +``` Make sure you have GPU and the paddlepaddle version is right. For example, for CUDA 10.2, CuDNN7.5 install paddle 2.2.0: - ```bash python3 -m pip install paddlepaddle-gpu==2.2.0 -i https://mirror.baidu.com/pypi/simple ``` diff --git a/docs/source/install_cn.md b/docs/source/install_cn.md index 7d414b0c..55fef93d 100644 --- a/docs/source/install_cn.md +++ b/docs/source/install_cn.md @@ -5,7 +5,7 @@ | :--- | :----------------------------------------------------------- | :------------------ | | 简单 | (1) 使用 PaddleSpeech 的命令行功能.
(2) 在 Aistudio上体验 PaddleSpeech. | Linux, Mac(不支持M1芯片)，Windows | | 中等 | 支持 PaddleSpeech 主要功能，比如使用已有 examples 中的模型和使用 PaddleSpeech 来训练自己的模型. | Linux | -| 困难 | 支持 PaddleSpeech 的各项功能，包含训练语言模型,使用强制对齐等。并且你更能成为一名开发者！ | Ubuntu | +| 困难 | 支持 PaddleSpeech 的各项功能，包含结合kaldi使用 join ctc decoder 方式解码，训练语言模型,使用强制对齐等。并且你更能成为一名开发者！ | Ubuntu | ## 先决条件 - Python >= 3.7 - 最新版本的 PaddlePaddle (请看 [安装向导](https://www.paddlepaddle.org.cn/documentation/docs/en/beginners_guide/index_en.html)) @@ -49,12 +49,19 @@ sudo apt install build-essential conda install -y -c gcc_linux-64=8.4.0 gxx_linux-64=8.4.0 ``` ### 安装 PaddleSpeech -你可以使用如下命令： +部分用户系统由于默认源的问题，安装中会出现kaldiio安转出错的问题，建议首先安装pytest-runner: +```bash +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple +``` +然后你可以使用如下命令： ```bash pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple pip install paddlespeech -i https://pypi.tuna.tsinghua.edu.cn/simple ``` > 如果您在使用 paddlespeech 的过程中遇到关于下载 **nltk_data** 的问题，可能是您的网络不佳，我们建议您下载我们提供的 [nltk_data](https://paddlespeech.bj.bcebos.com/Parakeet/tools/nltk_data.tar.gz) 并解压缩到您的 `${HOME}` 目录下。 + +> 如果出现 paddlespeech-ctcdecoders 无法安装的问题，无须担心，这不影响使用。 + ## 中等： 获取主要功能（支持 Linux） 如果你想要使用 `paddlespeech` 的主要功能。你需要完成以下几个步骤 ### Git clone PaddleSpeech @@ -111,6 +118,8 @@ python3 -m pip install paddlepaddle-gpu==2.2.0 -i https://mirror.baidu.com/pypi/ ### 安装 PaddleSpeech 最后安装 `paddlespeech`，这样你就可以使用 `paddlespeech`中已有的 examples： ```bash +# 部分用户系统由于默认源的问题，安装中会出现kaldiio安转出错的问题，建议首先安装pytest-runner: +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple # 请确保目前处于PaddleSpeech项目的根目录 pip install . -i https://pypi.tuna.tsinghua.edu.cn/simple ``` @@ -176,6 +185,11 @@ conda install -y -c conda-forge sox libsndfile swig bzip2 libflac bc python3 -m pip install paddlepaddle-gpu==2.2.0 -i https://mirror.baidu.com/pypi/simple ``` ### 用开发者模式安装 PaddleSpeech +部分用户系统由于默认源的问题，安装中会出现kaldiio安转出错的问题，建议首先安装pytest-runner: +```bash +pip install pytest-runner -i https://pypi.tuna.tsinghua.edu.cn/simple +``` +然后安装 PaddleSpeech： ```bash pip install -e .[develop] -i https://pypi.tuna.tsinghua.edu.cn/simple ``` diff --git a/docs/topic/gan_vocoder/gan_vocoder.ipynb b/docs/topic/gan_vocoder/gan_vocoder.ipynb index d214a81e..edb4eeb1 100644 --- a/docs/topic/gan_vocoder/gan_vocoder.ipynb +++ b/docs/topic/gan_vocoder/gan_vocoder.ipynb @@ -21,7 +21,11 @@ "|FB-RAWs|Filter Bank Random Window Discriminators|\n", "\n", "

\n", - "csmsc 数据集上 GAN Vocoder 整体对比\n", + "csmsc 数据集上 GAN Vocoder 整体对比如下， \n ", + "\n", + "测试机器：1 x Tesla V100-32G 40 core Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz\n ", + "\n", + "测试环境：Python 3.7.0, paddlepaddle 2.2.0\n", "\n", "Model|Date|Input|Generator
Loss|Discriminator
Loss|Need
Finetune|Training
Steps|Finetune
Steps|Batch
Size|ips
(gen only)
(gen + dis)|Static Model
Size (gen)|RTF
(GPU)|\n", ":-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|:-----:|\n", diff --git a/docs/topic/package_release/python_package_release.md b/docs/topic/package_release/python_package_release.md new file mode 100644 index 00000000..38250962 --- /dev/null +++ b/docs/topic/package_release/python_package_release.md @@ -0,0 +1,159 @@ +# 发包方法 + + + +## conda 代替系统依赖 + +conda可以用来代替一些 apt-get 安装的系统依赖，这样可以让项目适用于除了 ubuntu 以外的系统。 + +使用 conda 可以安装 sox, libsndfile，swig等 paddlespeech 需要的依赖： + +```bash +conda install -y -c conda-forge sox libsndfile +``` + +部分系统会缺少libbzip2库，这个 paddlespeech 也是需要的，这也可以用 conda 安装： + +```bash +conda install -y -c bzip2 +``` + +conda也可以安装linux的C++的依赖： + +```bash +conda install -y -c gcc_linux-64=8.4.0 gxx_linux-64=8.4.0 +``` + +#### 剩余问题：使用conda环境编译kenlm失败。目前在conda环境下编译kenlm会出现链接失败的问题 + +目前知道需要的依赖： + +```bash +conda install -c conda-forge eigen boost cmake +``` + + + +## python 编包方法 + +#### 创建 pypi的账号 + +创建 pypi 账号 + +#### 下载 twine + +``` +pip install twine +``` + +#### python 编包 + +编写好python包的setup.py, 然后使用如下命令编wheel包： + +```bash +python setup.py bdist_wheel +``` + +如果要编源码包，用如下命令： + +```bash +python setup.py sdist +``` + +#### 上传包 + +```bash +twine upload dist/wheel包 +``` + +输入账号和密码后就可以上传wheel包了 + +#### 关于python 包的发包信息 + +主要可以参考这个[文档](https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/?highlight=find_packages) + + + +## Manylinux 降低含有 C++ 依赖的 pip 包的 glibc 依赖 + +为了让有C++依赖的 pip wheel 包可以适用于更多的 linux 系统，需要降低其本身的 glibc 的依赖。这就需要让 pip wheel 包在 manylinux 的 docker 下编包。关于查看系统的 glibc 版本，可以使用命令：`ldd --version`。 + +### Manylinux + +关于Many Linux，主要可以参考 Github 项目的说明[ github many linux](https://github.com/pypa/manylinux)。 +manylinux1 支持 Centos5以上， manylinux2010 支持 Centos 6 以上，manylinux2014 支持Centos 7 以上。 +目前使用 manylinux2010 基本可以满足所有的 linux 生产环境需求。（不建议使用manylinux1，系统较老，难度较大） + +### 拉取 manylinux2010 + +```bash +docker pull quay.io/pypa/manylinux1_x86_64 +``` + +### 使用 manylinux2010 + +启动 manylinux2010 docker。 + +```bash +docker run -it xxxxxx +``` + +在 Many Linux 2010 的docker环境自带 swig 和各种类型的 python 版本。这里注意不要自己下载conda 来安装环境来编译 pip 包，要用 docker 本身的环境来编包。 +设置python： + +```bash +export PATH="/opt/python/cp37-cp37m/bin/:$PATH" +#export PATH="/opt/python/cp38-cp38/bin/:$PATH" +#export PATH="/opt/python/cp39-cp39/bin/:$PATH" +``` + +随后正常编包，编包后需要使用 [auditwheel](https://github.com/pypa/auditwheel) 来降低编好的wheel包的版本。 +显示 wheel 包的 glibc 依赖版本 + +```bash +auditwheel show wheel包 +``` + +降低 wheel包的版本 + +```bash +auditwheel repair wheel包 +``` + + + +## 区分 install 模式和 develop 模式 + +可以在setup.py 中划分 install 的依赖（基本依赖）和 develop 的依赖 （开发者额外依赖）。 setup_info 中 `install_requires` 设置 install 的依赖，而在 `extras_require` 中设置 `develop` key为 develop的依赖。 +普通安装可以使用： + +```bash +pip install . +``` + +另外使用 pip 安装已发的包也是使用普通安装的： + +``` +pip install paddlespeech +``` + +而开发者可以使用如下方式安装，这样不仅会安装install的依赖，也会安装develop的依赖， 即：最后安装的依赖=install依赖 + develop依赖： + +```bash +pip install -e .[develop] +``` + + + +## python 包的动态安装 + +可以使用 pip包来实现动态安装： + +```python +import pip +if int(pip.__version__.split('.')[0]) > 9: + from pip._internal import main + else: + from pip import main + main(['install', package_name]) +``` diff --git a/examples/csmsc/voc3/finetune.sh b/examples/csmsc/voc3/finetune.sh index 4ab10e5b..ca7958cf 100755 --- a/examples/csmsc/voc3/finetune.sh +++ b/examples/csmsc/voc3/finetune.sh @@ -15,11 +15,13 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then --fastspeech2-stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \ --dur-file=durations.txt \ --output-dir=dump_finetune \ - --phones-dict=fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt + --phones-dict=fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt \ + --dataset=baker \ + --rootdir=~/datasets/BZNSYP/ fi if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then - python3 local/link_wav.py \ + python3 link_wav.py \ --old-dump-dir=dump \ --dump-dir=dump_finetune fi diff --git a/examples/csmsc/voc5/finetune.sh b/examples/csmsc/voc5/finetune.sh index 4ab10e5b..ca7958cf 100755 --- a/examples/csmsc/voc5/finetune.sh +++ b/examples/csmsc/voc5/finetune.sh @@ -15,11 +15,13 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then --fastspeech2-stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \ --dur-file=durations.txt \ --output-dir=dump_finetune \ - --phones-dict=fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt + --phones-dict=fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt \ + --dataset=baker \ + --rootdir=~/datasets/BZNSYP/ fi if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then - python3 local/link_wav.py \ + python3 link_wav.py \ --old-dump-dir=dump \ --dump-dir=dump_finetune fi diff --git a/examples/csmsc/voc5/local/link_wav.py b/examples/csmsc/voc5/local/link_wav.py deleted file mode 100644 index c81e0d4b..00000000 --- a/examples/csmsc/voc5/local/link_wav.py +++ /dev/null @@ -1,85 +0,0 @@ -# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# 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, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import argparse -import os -from operator import itemgetter -from pathlib import Path - -import jsonlines -import numpy as np - - -def main(): - # parse config and args - parser = argparse.ArgumentParser( - description="Preprocess audio and then extract features .") - - parser.add_argument( - "--old-dump-dir", - default=None, - type=str, - help="directory to dump feature files.") - parser.add_argument( - "--dump-dir", - type=str, - required=True, - help="directory to finetune dump feature files.") - args = parser.parse_args() - - old_dump_dir = Path(args.old_dump_dir).expanduser() - old_dump_dir = old_dump_dir.resolve() - dump_dir = Path(args.dump_dir).expanduser() - # use absolute path - dump_dir = dump_dir.resolve() - dump_dir.mkdir(parents=True, exist_ok=True) - - assert old_dump_dir.is_dir() - assert dump_dir.is_dir() - - for sub in ["train", "dev", "test"]: - # 把 old_dump_dir 里面的 *-wave.npy 软连接到 dump_dir 的对应位置 - output_dir = dump_dir / sub - output_dir.mkdir(parents=True, exist_ok=True) - results = [] - for name in os.listdir(output_dir / "raw"): - # 003918_feats.npy - utt_id = name.split("_")[0] - mel_path = output_dir / ("raw/" + name) - gen_mel = np.load(mel_path) - wave_name = utt_id + "_wave.npy" - wav = np.load(old_dump_dir / sub / ("raw/" + wave_name)) - os.symlink(old_dump_dir / sub / ("raw/" + wave_name), - output_dir / ("raw/" + wave_name)) - num_sample = wav.shape[0] - num_frames = gen_mel.shape[0] - wav_path = output_dir / ("raw/" + wave_name) - - record = { - "utt_id": utt_id, - "num_samples": num_sample, - "num_frames": num_frames, - "feats": str(mel_path), - "wave": str(wav_path), - } - results.append(record) - - results.sort(key=itemgetter("utt_id")) - - with jsonlines.open(output_dir / "raw/metadata.jsonl", 'w') as writer: - for item in results: - writer.write(item) - - -if __name__ == "__main__": - main() diff --git a/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py b/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py index e25e4030..fb8b321c 100644 --- a/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py +++ b/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py @@ -149,13 +149,13 @@ class DeepSpeech2Model(nn.Layer): """Compute Model loss Args: - audio (Tenosr): [B, T, D] + audio (Tensor): [B, T, D] audio_len (Tensor): [B] text (Tensor): [B, U] text_len (Tensor): [B] Returns: - loss (Tenosr): [1] + loss (Tensor): [1] """ eouts, eouts_len = self.encoder(audio, audio_len) loss = self.decoder(eouts, eouts_len, text, text_len) diff --git a/examples/vctk/tts3/README.md b/examples/vctk/tts3/README.md index 83c9eb66..74c1086a 100644 --- a/examples/vctk/tts3/README.md +++ b/examples/vctk/tts3/README.md @@ -95,16 +95,16 @@ optional arguments: ### Synthesizing We use [parallel wavegan](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/vctk/voc1) as the neural vocoder. -Download pretrained parallel wavegan model from [pwg_vctk_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.5.zip)and unzip it. +Download pretrained parallel wavegan model from [pwg_vctk_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.1.1.zip) and unzip it. ```bash -unzip pwg_vctk_ckpt_0.5.zip +unzip pwg_vctk_ckpt_0.1.1.zip ``` Parallel WaveGAN checkpoint contains files listed below. ```text -pwg_vctk_ckpt_0.5 -├── pwg_default.yaml # default config used to train parallel wavegan -├── pwg_snapshot_iter_1000000.pdz # generator parameters of parallel wavegan -└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +pwg_vctk_ckpt_0.1.1 +├── default.yaml # default config used to train parallel wavegan +├── snapshot_iter_1500000.pdz # generator parameters of parallel wavegan +└── feats_stats.npy # statistics used to normalize spectrogram when training parallel wavegan ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash diff --git a/examples/vctk/tts3/local/synthesize.sh b/examples/vctk/tts3/local/synthesize.sh index a8aef034..8381af46 100755 --- a/examples/vctk/tts3/local/synthesize.sh +++ b/examples/vctk/tts3/local/synthesize.sh @@ -12,9 +12,9 @@ python3 ${BIN_DIR}/../synthesize.py \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/speech_stats.npy \ --voc=pwgan_vctk \ - --voc_config=pwg_vctk_ckpt_0.5/pwg_default.yaml \ - --voc_ckpt=pwg_vctk_ckpt_0.5/pwg_snapshot_iter_1000000.pdz \ - --voc_stat=pwg_vctk_ckpt_0.5/pwg_stats.npy \ + --voc_config=pwg_vctk_ckpt_0.1.1/default.yaml \ + --voc_ckpt=pwg_vctk_ckpt_0.1.1/snapshot_iter_1500000.pdz \ + --voc_stat=pwg_vctk_ckpt_0.1.1/feats_stats.npy \ --test_metadata=dump/test/norm/metadata.jsonl \ --output_dir=${train_output_path}/test \ --phones_dict=dump/phone_id_map.txt \ diff --git a/examples/vctk/tts3/local/synthesize_e2e.sh b/examples/vctk/tts3/local/synthesize_e2e.sh index 954e8cb9..51bb9e19 100755 --- a/examples/vctk/tts3/local/synthesize_e2e.sh +++ b/examples/vctk/tts3/local/synthesize_e2e.sh @@ -12,9 +12,9 @@ python3 ${BIN_DIR}/../synthesize_e2e.py \ --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ --am_stat=dump/train/speech_stats.npy \ --voc=pwgan_vctk \ - --voc_config=pwg_vctk_ckpt_0.5/pwg_default.yaml \ - --voc_ckpt=pwg_vctk_ckpt_0.5/pwg_snapshot_iter_1000000.pdz \ - --voc_stat=pwg_vctk_ckpt_0.5/pwg_stats.npy \ + --voc_config=pwg_vctk_ckpt_0.1.1/default.yaml \ + --voc_ckpt=pwg_vctk_ckpt_0.1.1/snapshot_iter_1500000.pdz \ + --voc_stat=pwg_vctk_ckpt_0.1.1/feats_stats.npy \ --lang=en \ --text=${BIN_DIR}/../sentences_en.txt \ --output_dir=${train_output_path}/test_e2e \ diff --git a/examples/vctk/voc1/README.md b/examples/vctk/voc1/README.md index ae5a8f37..4714f28d 100644 --- a/examples/vctk/voc1/README.md +++ b/examples/vctk/voc1/README.md @@ -132,15 +132,15 @@ optional arguments: 5. `--ngpu` is the number of gpus to use, if ngpu == 0, use cpu. ## Pretrained Model -Pretrained models can be downloaded here [pwg_vctk_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.5.zip). +Pretrained models can be downloaded here [pwg_vctk_ckpt_0.1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.1.1.zip). Parallel WaveGAN checkpoint contains files listed below. ```text -pwg_vctk_ckpt_0.5 -├── pwg_default.yaml # default config used to train parallel wavegan -├── pwg_snapshot_iter_1000000.pdz # generator parameters of parallel wavegan -└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +pwg_vctk_ckpt_0.1.1 +├── default.yaml # default config used to train parallel wavegan +├── snapshot_iter_1500000.pdz # generator parameters of parallel wavegan +└── feats_stats.npy # statistics used to normalize spectrogram when training parallel wavegan ``` ## Acknowledgement We adapted some code from https://github.com/kan-bayashi/ParallelWaveGAN. diff --git a/examples/vctk/voc1/conf/default.yaml b/examples/vctk/voc1/conf/default.yaml index aa382e21..59ce3825 100644 --- a/examples/vctk/voc1/conf/default.yaml +++ b/examples/vctk/voc1/conf/default.yaml @@ -70,7 +70,7 @@ lambda_adv: 4.0 # Loss balancing coefficient. ########################################################### # DATA LOADER SETTING # ########################################################### -batch_size: 8 # Batch size. +batch_size: 6 # Batch size. batch_max_steps: 24000 # Length of each audio in batch. Make sure dividable by n_shift. num_workers: 2 # Number of workers in DataLoader. @@ -100,7 +100,7 @@ discriminator_grad_norm: 1 # Discriminator's gradient norm. # INTERVAL SETTING # ########################################################### discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator. -train_max_steps: 1000000 # Number of training steps. +train_max_steps: 1500000 # Number of training steps. save_interval_steps: 5000 # Interval steps to save checkpoint. eval_interval_steps: 1000 # Interval steps to evaluate the network. diff --git a/paddleaudio/CHANGELOG.md b/paddleaudio/CHANGELOG.md new file mode 100644 index 00000000..4dc68c6f --- /dev/null +++ b/paddleaudio/CHANGELOG.md @@ -0,0 +1,2 @@ +# Changelog + diff --git a/paddlespeech/cli/asr/infer.py b/paddlespeech/cli/asr/infer.py index db1e8341..8de96476 100644 --- a/paddlespeech/cli/asr/infer.py +++ b/paddlespeech/cli/asr/infer.py @@ -31,6 +31,7 @@ from ..log import logger from ..utils import cli_register from ..utils import download_and_decompress from ..utils import MODEL_HOME +from ..utils import stats_wrapper from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer from paddlespeech.s2t.transform.transformation import Transformation from paddlespeech.s2t.utils.dynamic_import import dynamic_import @@ -425,6 +426,7 @@ class ASRExecutor(BaseExecutor): logger.exception(e) return False + @stats_wrapper def __call__(self, audio_file: os.PathLike, model: str='conformer_wenetspeech', diff --git a/paddlespeech/cli/cls/infer.py b/paddlespeech/cli/cls/infer.py index c31ad361..52bc1972 100644 --- a/paddlespeech/cli/cls/infer.py +++ b/paddlespeech/cli/cls/infer.py @@ -26,6 +26,7 @@ from ..log import logger from ..utils import cli_register from ..utils import download_and_decompress from ..utils import MODEL_HOME +from ..utils import stats_wrapper from paddleaudio import load from paddleaudio.features import LogMelSpectrogram from paddlespeech.s2t.utils.dynamic_import import dynamic_import @@ -245,6 +246,7 @@ class CLSExecutor(BaseExecutor): logger.exception(e) return False + @stats_wrapper def __call__(self, audio_file: os.PathLike, model: str='panns_cnn14', diff --git a/paddlespeech/cli/st/infer.py b/paddlespeech/cli/st/infer.py index 553b025f..d6bd6304 100644 --- a/paddlespeech/cli/st/infer.py +++ b/paddlespeech/cli/st/infer.py @@ -30,6 +30,7 @@ from ..log import logger from ..utils import cli_register from ..utils import download_and_decompress from ..utils import MODEL_HOME +from ..utils import stats_wrapper from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer from paddlespeech.s2t.utils.dynamic_import import dynamic_import from paddlespeech.s2t.utils.utility import UpdateConfig @@ -334,6 +335,7 @@ class STExecutor(BaseExecutor): logger.exception(e) return False + @stats_wrapper def __call__(self, audio_file: os.PathLike, model: str='fat_st_ted', diff --git a/paddlespeech/cli/text/infer.py b/paddlespeech/cli/text/infer.py index da9c5fe0..1cef8fcf 100644 --- a/paddlespeech/cli/text/infer.py +++ b/paddlespeech/cli/text/infer.py @@ -26,6 +26,7 @@ from ..log import logger from ..utils import cli_register from ..utils import download_and_decompress from ..utils import MODEL_HOME +from ..utils import stats_wrapper __all__ = ['TextExecutor'] @@ -272,6 +273,7 @@ class TextExecutor(BaseExecutor): logger.exception(e) return False + @stats_wrapper def __call__( self, text: str, diff --git a/paddlespeech/cli/tts/infer.py b/paddlespeech/cli/tts/infer.py index 75470e89..a39a5c4e 100644 --- a/paddlespeech/cli/tts/infer.py +++ b/paddlespeech/cli/tts/infer.py @@ -29,6 +29,7 @@ from ..log import logger from ..utils import cli_register from ..utils import download_and_decompress from ..utils import MODEL_HOME +from ..utils import stats_wrapper from paddlespeech.s2t.utils.dynamic_import import dynamic_import from paddlespeech.t2s.frontend import English from paddlespeech.t2s.frontend.zh_frontend import Frontend @@ -155,15 +156,15 @@ pretrained_models = { }, "pwgan_vctk-en": { 'url': - 'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.5.zip', + 'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_vctk_ckpt_0.1.1.zip', 'md5': - '322ca688aec9b127cec2788b65aa3d52', + 'b3da1defcde3e578be71eb284cb89f2c', 'config': - 'pwg_default.yaml', + 'default.yaml', 'ckpt': - 'pwg_snapshot_iter_1000000.pdz', + 'snapshot_iter_1500000.pdz', 'speech_stats': - 'pwg_stats.npy', + 'feats_stats.npy', }, # mb_melgan "mb_melgan_csmsc-zh": { @@ -645,6 +646,7 @@ class TTSExecutor(BaseExecutor): logger.exception(e) return False + @stats_wrapper def __call__(self, text: str, am: str='fastspeech2_csmsc', diff --git a/paddlespeech/cli/utils.py b/paddlespeech/cli/utils.py index ee31b771..63b670c8 100644 --- a/paddlespeech/cli/utils.py +++ b/paddlespeech/cli/utils.py @@ -11,22 +11,36 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. +import hashlib +import inspect +import json import os import tarfile +import threading +import time +import uuid import zipfile from typing import Any from typing import Dict +import paddle +import paddleaudio +import requests +import yaml from paddle.framework import load from . import download +from .. import __version__ from .entry import commands +requests.adapters.DEFAULT_RETRIES = 3 + __all__ = [ 'cli_register', 'get_command', 'download_and_decompress', 'load_state_dict_from_url', + 'stats_wrapper', ] @@ -101,6 +115,13 @@ def download_and_decompress(archive: Dict[str, str], path: str) -> os.PathLike: if not os.path.isdir(uncompress_path): download._decompress(filepath) else: + StatsWorker( + task='download', + version=__version__, + extra_info={ + 'download_url': archive['url'], + 'paddle_version': paddle.__version__ + }).start() uncompress_path = download.get_path_from_url(archive['url'], path, archive['md5']) @@ -146,3 +167,171 @@ def _get_sub_home(directory): PPSPEECH_HOME = _get_paddlespcceh_home() MODEL_HOME = _get_sub_home('models') +CONF_HOME = _get_sub_home('conf') + + +def _md5(text: str): + '''Calculate the md5 value of the input text.''' + md5code = hashlib.md5(text.encode()) + return md5code.hexdigest() + + +class ConfigCache: + def __init__(self): + self._data = {} + self._initialize() + self.file = os.path.join(CONF_HOME, 'cache.yaml') + if not os.path.exists(self.file): + self.flush() + return + + with open(self.file, 'r') as file: + try: + cfg = yaml.load(file, Loader=yaml.FullLoader) + self._data.update(cfg) + except: + self.flush() + + @property + def cache_info(self): + return self._data['cache_info'] + + def _initialize(self): + # Set default configuration values. + cache_info = _md5(str(uuid.uuid1())[-12:]) + "-" + str(int(time.time())) + self._data['cache_info'] = cache_info + + def flush(self): + '''Flush the current configuration into the configuration file.''' + with open(self.file, 'w') as file: + cfg = json.loads(json.dumps(self._data)) + yaml.dump(cfg, file) + + +stats_api = "http://paddlepaddle.org.cn/paddlehub/stat" +cache_info = ConfigCache().cache_info + + +class StatsWorker(threading.Thread): + def __init__(self, + task="asr", + model=None, + version=__version__, + extra_info={}): + threading.Thread.__init__(self) + self._task = task + self._model = model + self._version = version + self._extra_info = extra_info + + def run(self): + params = { + 'task': self._task, + 'version': self._version, + 'from': 'ppspeech' + } + if self._model: + params['model'] = self._model + + self._extra_info.update({ + 'cache_info': cache_info, + }) + params.update({"extra": json.dumps(self._extra_info)}) + + try: + requests.get(stats_api, params) + except Exception: + pass + + return + + +def _note_one_stat(cls_name, params={}): + task = cls_name.replace('Executor', '').lower() # XXExecutor + extra_info = { + 'paddle_version': paddle.__version__, + } + + if 'model' in params: + model = params['model'] + else: + model = None + + if 'audio_file' in params: + try: + _, sr = paddleaudio.load(params['audio_file']) + except Exception: + sr = -1 + + if task == 'asr': + extra_info.update({ + 'lang': params['lang'], + 'inp_sr': sr, + 'model_sr': params['sample_rate'], + }) + elif task == 'st': + extra_info.update({ + 'lang': + params['src_lang'] + '-' + params['tgt_lang'], + 'inp_sr': + sr, + 'model_sr': + params['sample_rate'], + }) + elif task == 'tts': + model = params['am'] + extra_info.update({ + 'lang': params['lang'], + 'vocoder': params['voc'], + }) + elif task == 'cls': + extra_info.update({ + 'inp_sr': sr, + }) + elif task == 'text': + extra_info.update({ + 'sub_task': params['task'], + 'lang': params['lang'], + }) + else: + return + + StatsWorker( + task=task, + model=model, + version=__version__, + extra_info=extra_info, ).start() + + +def _parse_args(func, *args, **kwargs): + # FullArgSpec(args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations) + argspec = inspect.getfullargspec(func) + + keys = argspec[0] + if keys[0] == 'self': # Remove self pointer. + keys = keys[1:] + + default_values = argspec[3] + values = [None] * (len(keys) - len(default_values)) + values.extend(list(default_values)) + params = dict(zip(keys, values)) + + for idx, v in enumerate(args): + params[keys[idx]] = v + for k, v in kwargs.items(): + params[k] = v + + return params + + +def stats_wrapper(executor_func): + def _warpper(self, *args, **kwargs): + try: + _note_one_stat( + type(self).__name__, _parse_args(executor_func, *args, + **kwargs)) + except Exception: + pass + return executor_func(self, *args, **kwargs) + + return _warpper diff --git a/paddlespeech/s2t/decoders/ctcdecoder/scorer_deprecated.py b/paddlespeech/s2t/decoders/ctcdecoder/scorer_deprecated.py index d81fb2e3..362098fe 100644 --- a/paddlespeech/s2t/decoders/ctcdecoder/scorer_deprecated.py +++ b/paddlespeech/s2t/decoders/ctcdecoder/scorer_deprecated.py @@ -62,7 +62,7 @@ class Scorer(object): """Evaluation function, gathering all the different scores and return the final one. - :param sentence: The input sentence for evalutation + :param sentence: The input sentence for evaluation :type sentence: str :param log: Whether return the score in log representation. :type log: bool diff --git a/paddlespeech/s2t/decoders/ctcdecoder/swig/ctc_beam_search_decoder.cpp b/paddlespeech/s2t/decoders/ctcdecoder/swig/ctc_beam_search_decoder.cpp index 8469a194..663c52bb 100644 --- a/paddlespeech/s2t/decoders/ctcdecoder/swig/ctc_beam_search_decoder.cpp +++ b/paddlespeech/s2t/decoders/ctcdecoder/swig/ctc_beam_search_decoder.cpp @@ -183,7 +183,7 @@ std::vector> ctc_beam_search_decoder( std::sort( prefixes.begin(), prefixes.begin() + num_prefixes, prefix_compare); - // compute aproximate ctc score as the return score, without affecting the + // compute approximate ctc score as the return score, without affecting the // return order of decoding result. To delete when decoder gets stable. for (size_t i = 0; i < beam_size && i < prefixes.size(); ++i) { double approx_ctc = prefixes[i]->score; diff --git a/paddlespeech/s2t/decoders/ctcdecoder/swig/decoder_utils.cpp b/paddlespeech/s2t/decoders/ctcdecoder/swig/decoder_utils.cpp index 5d69ad03..e86c2240 100644 --- a/paddlespeech/s2t/decoders/ctcdecoder/swig/decoder_utils.cpp +++ b/paddlespeech/s2t/decoders/ctcdecoder/swig/decoder_utils.cpp @@ -26,7 +26,7 @@ std::vector> get_pruned_log_probs( for (size_t i = 0; i < prob_step.size(); ++i) { prob_idx.push_back(std::pair(i, prob_step[i])); } - // pruning of vacobulary + // pruning of vocabulary size_t cutoff_len = prob_step.size(); if (cutoff_prob < 1.0 || cutoff_top_n < cutoff_len) { std::sort(prob_idx.begin(), diff --git a/paddlespeech/s2t/decoders/ctcdecoder/swig/scorer.cpp b/paddlespeech/s2t/decoders/ctcdecoder/swig/scorer.cpp index 7bd6542d..7c9a75d5 100644 --- a/paddlespeech/s2t/decoders/ctcdecoder/swig/scorer.cpp +++ b/paddlespeech/s2t/decoders/ctcdecoder/swig/scorer.cpp @@ -223,7 +223,7 @@ void Scorer::fill_dictionary(bool add_space) { * This gets rid of "epsilon" transitions in the FST. * These are transitions that don't require a string input to be taken. - * Getting rid of them is necessary to make the FST determinisitc, but + * Getting rid of them is necessary to make the FST deterministic, but * can greatly increase the size of the FST */ fst::RmEpsilon(&dictionary); diff --git a/paddlespeech/s2t/decoders/scorers/ctc.py b/paddlespeech/s2t/decoders/scorers/ctc.py index ace80bd3..81d8b078 100644 --- a/paddlespeech/s2t/decoders/scorers/ctc.py +++ b/paddlespeech/s2t/decoders/scorers/ctc.py @@ -154,7 +154,7 @@ class CTCPrefixScorer(BatchPartialScorerInterface): Args: state: The states of hyps - Returns: exteded state + Returns: extended state """ new_state = [] diff --git a/paddlespeech/s2t/decoders/scorers/ctc_prefix_score.py b/paddlespeech/s2t/decoders/scorers/ctc_prefix_score.py index 13429d49..78b8fe36 100644 --- a/paddlespeech/s2t/decoders/scorers/ctc_prefix_score.py +++ b/paddlespeech/s2t/decoders/scorers/ctc_prefix_score.py @@ -11,7 +11,7 @@ class CTCPrefixScorePD(): which is based on Algorithm 2 in WATANABE et al. "HYBRID CTC/ATTENTION ARCHITECTURE FOR END-TO-END SPEECH RECOGNITION," - but extended to efficiently compute the label probablities for multiple + but extended to efficiently compute the label probabilities for multiple hypotheses simultaneously See also Seki et al. "Vectorized Beam Search for CTC-Attention-Based Speech Recognition," In INTERSPEECH (pp. 3825-3829), 2019. @@ -272,7 +272,7 @@ class CTCPrefixScore(): which is based on Algorithm 2 in WATANABE et al. "HYBRID CTC/ATTENTION ARCHITECTURE FOR END-TO-END SPEECH RECOGNITION," - but extended to efficiently compute the probablities of multiple labels + but extended to efficiently compute the probabilities of multiple labels simultaneously """ diff --git a/paddlespeech/s2t/exps/u2/model.py b/paddlespeech/s2t/exps/u2/model.py index 6ab671ee..992be5cd 100644 --- a/paddlespeech/s2t/exps/u2/model.py +++ b/paddlespeech/s2t/exps/u2/model.py @@ -238,7 +238,9 @@ class U2Trainer(Trainer): preprocess_conf=config.preprocess_config, n_iter_processes=config.num_workers, subsampling_factor=1, - num_encs=1) + num_encs=1, + dist_sampler=False, + shortest_first=False) self.valid_loader = BatchDataLoader( json_file=config.dev_manifest, @@ -257,7 +259,9 @@ class U2Trainer(Trainer): preprocess_conf=config.preprocess_config, n_iter_processes=config.num_workers, subsampling_factor=1, - num_encs=1) + num_encs=1, + dist_sampler=False, + shortest_first=False) logger.info("Setup train/valid Dataloader!") else: decode_batch_size = config.get('decode', dict()).get( diff --git a/paddlespeech/s2t/io/dataloader.py b/paddlespeech/s2t/io/dataloader.py index 455303f7..920de34f 100644 --- a/paddlespeech/s2t/io/dataloader.py +++ b/paddlespeech/s2t/io/dataloader.py @@ -78,7 +78,8 @@ class BatchDataLoader(): load_aux_input: bool=False, load_aux_output: bool=False, num_encs: int=1, - dist_sampler: bool=False): + dist_sampler: bool=False, + shortest_first: bool=False): self.json_file = json_file self.train_mode = train_mode self.use_sortagrad = sortagrad == -1 or sortagrad > 0 @@ -97,6 +98,7 @@ class BatchDataLoader(): self.load_aux_input = load_aux_input self.load_aux_output = load_aux_output self.dist_sampler = dist_sampler + self.shortest_first = shortest_first # read json data with jsonlines.open(json_file, 'r') as reader: @@ -113,7 +115,7 @@ class BatchDataLoader(): maxlen_out, minibatches, # for debug min_batch_size=mini_batch_size, - shortest_first=self.use_sortagrad, + shortest_first=self.shortest_first or self.use_sortagrad, count=batch_count, batch_bins=batch_bins, batch_frames_in=batch_frames_in, @@ -149,13 +151,13 @@ class BatchDataLoader(): self.reader) if self.dist_sampler: - self.sampler = DistributedBatchSampler( + self.batch_sampler = DistributedBatchSampler( dataset=self.dataset, batch_size=1, shuffle=not self.use_sortagrad if self.train_mode else False, drop_last=False, ) else: - self.sampler = BatchSampler( + self.batch_sampler = BatchSampler( dataset=self.dataset, batch_size=1, shuffle=not self.use_sortagrad if self.train_mode else False, @@ -163,7 +165,7 @@ class BatchDataLoader(): self.dataloader = DataLoader( dataset=self.dataset, - batch_sampler=self.sampler, + batch_sampler=self.batch_sampler, collate_fn=batch_collate, num_workers=self.n_iter_processes, ) @@ -194,5 +196,6 @@ class BatchDataLoader(): echo += f"load_aux_input: {self.load_aux_input}, " echo += f"load_aux_output: {self.load_aux_output}, " echo += f"dist_sampler: {self.dist_sampler}, " + echo += f"shortest_first: {self.shortest_first}, " echo += f"file: {self.json_file}" return echo diff --git a/paddlespeech/s2t/models/ds2/deepspeech2.py b/paddlespeech/s2t/models/ds2/deepspeech2.py index a478ba82..4a4d67ce 100644 --- a/paddlespeech/s2t/models/ds2/deepspeech2.py +++ b/paddlespeech/s2t/models/ds2/deepspeech2.py @@ -151,13 +151,13 @@ class DeepSpeech2Model(nn.Layer): """Compute Model loss Args: - audio (Tenosr): [B, T, D] + audio (Tensors): [B, T, D] audio_len (Tensor): [B] text (Tensor): [B, U] text_len (Tensor): [B] Returns: - loss (Tenosr): [1] + loss (Tensor): [1] """ eouts, eouts_len = self.encoder(audio, audio_len) loss = self.decoder(eouts, eouts_len, text, text_len) diff --git a/paddlespeech/s2t/models/ds2_online/deepspeech2.py b/paddlespeech/s2t/models/ds2_online/deepspeech2.py index 7d463755..5e4981c0 100644 --- a/paddlespeech/s2t/models/ds2_online/deepspeech2.py +++ b/paddlespeech/s2t/models/ds2_online/deepspeech2.py @@ -279,13 +279,13 @@ class DeepSpeech2ModelOnline(nn.Layer): """Compute Model loss Args: - audio (Tenosr): [B, T, D] + audio (Tensor): [B, T, D] audio_len (Tensor): [B] text (Tensor): [B, U] text_len (Tensor): [B] Returns: - loss (Tenosr): [1] + loss (Tensor): [1] """ eouts, eouts_len, final_state_h_box, final_state_c_box = self.encoder( audio, audio_len, None, None) diff --git a/paddlespeech/s2t/models/u2/u2.py b/paddlespeech/s2t/models/u2/u2.py index d920a200..ff4012e8 100644 --- a/paddlespeech/s2t/models/u2/u2.py +++ b/paddlespeech/s2t/models/u2/u2.py @@ -680,8 +680,8 @@ class U2BaseModel(ASRInterface, nn.Layer): """u2 decoding. Args: - feats (Tenosr): audio features, (B, T, D) - feats_lengths (Tenosr): (B) + feats (Tensor): audio features, (B, T, D) + feats_lengths (Tensor): (B) text_feature (TextFeaturizer): text feature object. decoding_method (str): decoding mode, e.g. 'attention', 'ctc_greedy_search', diff --git a/paddlespeech/s2t/models/u2_st/u2_st.py b/paddlespeech/s2t/models/u2_st/u2_st.py index 2aa0b347..79ca423f 100644 --- a/paddlespeech/s2t/models/u2_st/u2_st.py +++ b/paddlespeech/s2t/models/u2_st/u2_st.py @@ -478,8 +478,8 @@ class U2STBaseModel(nn.Layer): """u2 decoding. Args: - feats (Tenosr): audio features, (B, T, D) - feats_lengths (Tenosr): (B) + feats (Tensor): audio features, (B, T, D) + feats_lengths (Tensor): (B) text_feature (TextFeaturizer): text feature object. decoding_method (str): decoding mode, e.g. 'fullsentence', diff --git a/paddlespeech/s2t/modules/ctc.py b/paddlespeech/s2t/modules/ctc.py index ffc9f038..1f983807 100644 --- a/paddlespeech/s2t/modules/ctc.py +++ b/paddlespeech/s2t/modules/ctc.py @@ -39,10 +39,6 @@ except ImportError: except Exception as e: logger.info("paddlespeech_ctcdecoders not installed!") -#try: -#except Exception as e: -# logger.info("ctcdecoder not installed!") - __all__ = ['CTCDecoder'] @@ -85,10 +81,10 @@ class CTCDecoderBase(nn.Layer): Args: hs_pad (Tensor): batch of padded hidden state sequences (B, Tmax, D) hlens (Tensor): batch of lengths of hidden state sequences (B) - ys_pad (Tenosr): batch of padded character id sequence tensor (B, Lmax) + ys_pad (Tensor): batch of padded character id sequence tensor (B, Lmax) ys_lens (Tensor): batch of lengths of character sequence (B) Returns: - loss (Tenosr): ctc loss value, scalar. + loss (Tensor): ctc loss value, scalar. """ logits = self.ctc_lo(self.dropout(hs_pad)) loss = self.criterion(logits, ys_pad, hlens, ys_lens) @@ -256,8 +252,8 @@ class CTCDecoder(CTCDecoderBase): """ctc decoding with probs. Args: - probs (Tenosr): activation after softmax - logits_lens (Tenosr): audio output lens + probs (Tensor): activation after softmax + logits_lens (Tensor): audio output lens vocab_list ([type]): [description] decoding_method ([type]): [description] lang_model_path ([type]): [description] diff --git a/paddlespeech/s2t/modules/mask.py b/paddlespeech/s2t/modules/mask.py index d6b63761..1f66c015 100644 --- a/paddlespeech/s2t/modules/mask.py +++ b/paddlespeech/s2t/modules/mask.py @@ -54,7 +54,7 @@ def make_pad_mask(lengths: paddle.Tensor) -> paddle.Tensor: [0, 0, 0, 1, 1], [0, 0, 1, 1, 1]] """ - # (TODO: Hui Zhang): jit not support Tenosr.dim() and Tensor.ndim + # (TODO: Hui Zhang): jit not support Tensor.dim() and Tensor.ndim # assert lengths.dim() == 1 batch_size = int(lengths.shape[0]) max_len = int(lengths.max()) diff --git a/paddlespeech/s2t/training/scheduler.py b/paddlespeech/s2t/training/scheduler.py index 0222246e..b22f7ef8 100644 --- a/paddlespeech/s2t/training/scheduler.py +++ b/paddlespeech/s2t/training/scheduler.py @@ -67,18 +67,19 @@ class WarmupLR(LRScheduler): super().__init__(learning_rate, last_epoch, verbose) def __repr__(self): - return f"{self.__class__.__name__}(warmup_steps={self.warmup_steps})" + return f"{self.__class__.__name__}(warmup_steps={self.warmup_steps}, lr={self.base_lr}, last_epoch={self.last_epoch})" def get_lr(self): + # self.last_epoch start from zero step_num = self.last_epoch + 1 return self.base_lr * self.warmup_steps**0.5 * min( step_num**-0.5, step_num * self.warmup_steps**-1.5) def set_step(self, step: int=None): ''' - It will update the learning rate in optimizer according to current ``epoch`` . + It will update the learning rate in optimizer according to current ``epoch`` . The new learning rate will take effect on next ``optimizer.step`` . - + Args: step (int, None): specify current epoch. Default: None. Auto-increment from last_epoch=-1. Returns: @@ -94,7 +95,7 @@ class ConstantLR(LRScheduler): learning_rate (float): The initial learning rate. It is a python float number. last_epoch (int, optional): The index of last epoch. Can be set to restart training. Default: -1, means initial learning rate. verbose (bool, optional): If ``True``, prints a message to stdout for each update. Default: ``False`` . - + Returns: ``ConstantLR`` instance to schedule learning rate. """ diff --git a/paddlespeech/s2t/training/trainer.py b/paddlespeech/s2t/training/trainer.py index 4b2011ec..cac5e570 100644 --- a/paddlespeech/s2t/training/trainer.py +++ b/paddlespeech/s2t/training/trainer.py @@ -222,7 +222,7 @@ class Trainer(): batch_sampler = self.train_loader.batch_sampler if isinstance(batch_sampler, paddle.io.DistributedBatchSampler): logger.debug( - f"train_loader.batch_sample set epoch: {self.epoch}") + f"train_loader.batch_sample.set_epoch: {self.epoch}") batch_sampler.set_epoch(self.epoch) def before_train(self): diff --git a/paddlespeech/s2t/utils/dynamic_import.py b/paddlespeech/s2t/utils/dynamic_import.py index 50bd73a6..bd738edf 100644 --- a/paddlespeech/s2t/utils/dynamic_import.py +++ b/paddlespeech/s2t/utils/dynamic_import.py @@ -57,7 +57,7 @@ def filter_valid_args(args: Dict[Text, Any], valid_keys: List[Text]): return new_args -def filter_out_tenosr(args: Dict[Text, Any]): +def filter_out_tensor(args: Dict[Text, Any]): return {key: val for key, val in args.items() if not has_tensor(val)} @@ -65,5 +65,5 @@ def instance_class(module_class, args: Dict[Text, Any]): valid_keys = inspect.signature(module_class).parameters.keys() new_args = filter_valid_args(args, valid_keys) logger.info( - f"Instance: {module_class.__name__} {filter_out_tenosr(new_args)}.") + f"Instance: {module_class.__name__} {filter_out_tensor(new_args)}.") return module_class(**new_args) diff --git a/paddlespeech/t2s/exps/fastspeech2/gen_gta_mel.py b/paddlespeech/t2s/exps/fastspeech2/gen_gta_mel.py index fa46fd55..4ddd19f7 100644 --- a/paddlespeech/t2s/exps/fastspeech2/gen_gta_mel.py +++ b/paddlespeech/t2s/exps/fastspeech2/gen_gta_mel.py @@ -21,6 +21,8 @@ import numpy as np import paddle import yaml from yacs.config import CfgNode +from tqdm import tqdm +import os from paddlespeech.t2s.datasets.preprocess_utils import get_phn_dur from paddlespeech.t2s.datasets.preprocess_utils import merge_silence @@ -30,6 +32,8 @@ from paddlespeech.t2s.modules.normalizer import ZScore def evaluate(args, fastspeech2_config): + rootdir = Path(args.rootdir).expanduser() + assert rootdir.is_dir() # construct dataset for evaluation with open(args.phones_dict, "r") as f: @@ -41,9 +45,16 @@ def evaluate(args, fastspeech2_config): for phn, id in phn_id: phone_dict[phn] = int(id) + if args.speaker_dict: + with open(args.speaker_dict, 'rt') as f: + spk_id_list = [line.strip().split() for line in f.readlines()] + spk_num = len(spk_id_list) + else: + spk_num=None + odim = fastspeech2_config.n_mels model = FastSpeech2( - idim=vocab_size, odim=odim, **fastspeech2_config["model"]) + idim=vocab_size, odim=odim, **fastspeech2_config["model"], spk_num=spk_num) model.set_state_dict( paddle.load(args.fastspeech2_checkpoint)["main_params"]) @@ -65,7 +76,34 @@ def evaluate(args, fastspeech2_config): sentences, speaker_set = get_phn_dur(args.dur_file) merge_silence(sentences) - for i, utt_id in enumerate(sentences): + if args.dataset == "baker": + wav_files = sorted(list((rootdir / "Wave").rglob("*.wav"))) + # split data into 3 sections + num_train = 9800 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + elif args.dataset == "aishell3": + sub_num_dev = 5 + wav_dir = rootdir / "train" / "wav" + train_wav_files = [] + dev_wav_files = [] + test_wav_files = [] + for speaker in os.listdir(wav_dir): + wav_files = sorted(list((wav_dir / speaker).rglob("*.wav"))) + if len(wav_files) > 100: + train_wav_files += wav_files[:-sub_num_dev * 2] + dev_wav_files += wav_files[-sub_num_dev * 2:-sub_num_dev] + test_wav_files += wav_files[-sub_num_dev:] + else: + train_wav_files += wav_files + + train_wav_files = [os.path.basename(str(str_path)) for str_path in train_wav_files] + dev_wav_files = [os.path.basename(str(str_path)) for str_path in dev_wav_files] + test_wav_files = [os.path.basename(str(str_path)) for str_path in test_wav_files] + + for i, utt_id in enumerate(tqdm(sentences)): phones = sentences[utt_id][0] durations = sentences[utt_id][1] speaker = sentences[utt_id][2] @@ -82,21 +120,30 @@ def evaluate(args, fastspeech2_config): phone_ids = [phone_dict[phn] for phn in phones] phone_ids = paddle.to_tensor(np.array(phone_ids)) + + if args.speaker_dict: + speaker_id = int([item[1] for item in spk_id_list if speaker == item[0]][0]) + speaker_id = paddle.to_tensor(speaker_id) + else: + speaker_id = None + durations = paddle.to_tensor(np.array(durations)) # 生成的和真实的可能有 1, 2 帧的差距，但是 batch_fn 会修复 # split data into 3 sections - if args.dataset == "baker": - num_train = 9800 - num_dev = 100 - if i in range(0, num_train): + + wav_path = utt_id + ".wav" + + if wav_path in train_wav_files: sub_output_dir = output_dir / ("train/raw") - elif i in range(num_train, num_train + num_dev): + elif wav_path in dev_wav_files: sub_output_dir = output_dir / ("dev/raw") - else: + elif wav_path in test_wav_files: sub_output_dir = output_dir / ("test/raw") + sub_output_dir.mkdir(parents=True, exist_ok=True) + with paddle.no_grad(): - mel = fastspeech2_inference(phone_ids, durations=durations) + mel = fastspeech2_inference(phone_ids, durations=durations, spk_id=speaker_id) np.save(sub_output_dir / (utt_id + "_feats.npy"), mel) @@ -109,6 +156,8 @@ def main(): default="baker", type=str, help="name of dataset, should in {baker, ljspeech, vctk} now") + parser.add_argument( + "--rootdir", default=None, type=str, help="directory to dataset.") parser.add_argument( "--fastspeech2-config", type=str, help="fastspeech2 config file.") parser.add_argument( @@ -126,6 +175,12 @@ def main(): type=str, default="phone_id_map.txt", help="phone vocabulary file.") + + parser.add_argument( + "--speaker-dict", + type=str, + default=None, + help="speaker id map file.") parser.add_argument( "--dur-file", default=None, type=str, help="path to durations.txt.") diff --git a/paddlespeech/t2s/frontend/zh_normalization/char_convert.py b/paddlespeech/t2s/frontend/zh_normalization/char_convert.py index 22462a0c..dcf95d72 100644 --- a/paddlespeech/t2s/frontend/zh_normalization/char_convert.py +++ b/paddlespeech/t2s/frontend/zh_normalization/char_convert.py @@ -14,7 +14,7 @@ # limitations under the License. """Traditional and simplified Chinese conversion, a simplified character may correspond to multiple traditional characters. """ -simplified_charcters = 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+simplified_charcters = 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traditional_characters = 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diff --git a/examples/csmsc/voc3/local/link_wav.py b/utils/link_wav.py similarity index 94% rename from examples/csmsc/voc3/local/link_wav.py rename to utils/link_wav.py index c81e0d4b..5b24c87d 100644 --- a/examples/csmsc/voc3/local/link_wav.py +++ b/utils/link_wav.py @@ -18,7 +18,7 @@ from pathlib import Path import jsonlines import numpy as np - +from tqdm import tqdm def main(): # parse config and args @@ -52,9 +52,9 @@ def main(): output_dir = dump_dir / sub output_dir.mkdir(parents=True, exist_ok=True) results = [] - for name in os.listdir(output_dir / "raw"): - # 003918_feats.npy - utt_id = name.split("_")[0] + files = os.listdir(output_dir / "raw") + for name in tqdm(files): + utt_id = name.split("_feats.npy")[0] mel_path = output_dir / ("raw/" + name) gen_mel = np.load(mel_path) wave_name = utt_id + "_wave.npy"