diff --git a/PyTorch/built-in/audio/ESPnet2_for_PyTorch/CONTRIBUTING.md b/PyTorch/built-in/audio/ESPnet2_for_PyTorch/CONTRIBUTING.md index 3e62434c769ac22b6f5a87d8fb742e6257b00fba..d0af14e6189f6b4c7c17de5aad0f8bbcdb90be4b 100644 --- a/PyTorch/built-in/audio/ESPnet2_for_PyTorch/CONTRIBUTING.md +++ b/PyTorch/built-in/audio/ESPnet2_for_PyTorch/CONTRIBUTING.md @@ -33,7 +33,7 @@ may refer to [port-kaldi-recipe](https://github.com/espnet/espnet/wiki/How-to-po and other existing recipes for new additions. For the Kaldi-style recipe architecture, please refer to [Prepare-Kaldi-Style-Directory](https://kaldi-asr.org/doc/data_prep.html). -For each recipe, we ask you to report the following: experiments results and environnement, model information. +For each recipe, we ask you to report the following: experiments results and environment, model information. For reproducibility, a link to upload the pre-trained model may also be added. All this information should be written in a markdown file called `RESULTS.md` and put at the recipe root. You can refer to [tedlium2-example](https://github.com/espnet/espnet/blob/master/egs/tedlium2/asr1/RESULTS.md) for an example. diff --git a/PyTorch/built-in/audio/ESPnet2_for_PyTorch/public_address_statement.md b/PyTorch/built-in/audio/ESPnet2_for_PyTorch/public_address_statement.md index e22e6716dc4338650d7a174b0872287d3cfea217..fab040b4436f89fd324532b391df9cfebad34a45 100644 --- a/PyTorch/built-in/audio/ESPnet2_for_PyTorch/public_address_statement.md +++ b/PyTorch/built-in/audio/ESPnet2_for_PyTorch/public_address_statement.md @@ -2,43 +2,43 @@ |----------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|---------------| | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 / | cuda地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 / | cuda地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 / | cuda地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/10.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu2004/x86_64 / | 下载相关依赖 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu2004/x86_64 | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/11.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 / | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 | cuda地址 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub | 下载秘钥 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 / | ubuntu镜像地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/8.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 | ubuntu镜像地址 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 / | cuda地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.0/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 / | cuda地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 | cuda地址 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.1/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 / | 下载相关依赖 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64 / | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 | 下载相关依赖 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64 | 下载相关依赖 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/devel/gpu/9.2/Dockerfile | https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64/7fa2af80.pub | 下载秘钥 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/local/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/runtime/Dockerfile | nyalta21@gmail.com | maintainer邮箱 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/docker/prebuilt/runtime/Dockerfile | https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh | miniconda链接 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/aidatatang_200zh/asr1/run.sh | www.openslr.org/resources/62 | 下载配置 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/aishell/asr1/run.sh | www.openslr.org/resources/33 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/aidatatang_200zh/asr1/run.sh | http://www.openslr.org/resources/62 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/aishell/asr1/run.sh | http://www.openslr.org/resources/33 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/ami/asr1/local/ami_download.sh | http://groups.inf.ed.ac.uk/ami | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/ami/asr1/local/ami_download.sh | http://groups.inf.ed.ac.uk/ami/download/temp/amiBuild-04237-Sun-Jun-15-2014.manifest.txt | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/ami/asr1/local/ami_text_prep.sh | http://groups.inf.ed.ac.uk/ami | 下载配置 | @@ -88,10 +88,10 @@ | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/jnas/tts1/run.sh | http://kaldi-asr.org/models/8/0008_sitw_v2_1a.tar.gz | 模型相关说明 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/jsut/tts1/local/download.sh | http://ss-takashi.sakura.ne.jp/corpus/jsut_ver1.1.zip | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/libri_css/asr1/local/download_xvector.sh | http://kaldi-asr.org/models/12/0012_diarization_v1.tar.gz | 下载依赖 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/librispeech/asr1/run.sh | www.openslr.org/resources/12 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/librispeech/asr1/run.sh | http://www.openslr.org/resources/12 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/librispeech/asr1/run.sh | http://www.openslr.org/resources/11/librispeech-lm-norm.txt.gz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/libritts/tts1/run.sh | http://kaldi-asr.org/models/8/0008_sitw_v2_1a.tar.gz | 模型相关说明 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/libritts/tts1/run.sh | www.openslr.org/resources/60 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/libritts/tts1/run.sh | http://www.openslr.org/resources/60 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/ljspeech/tts1/local/data_download.sh | http://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2 | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/m_ailabs/tts1/local/download.sh | http://www.caito.de/data/Training/stt_tts/${lang}.tgz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/mgb2/asr1/local/mgb_extract_data.sh | https://arabicspeech.org/mgb2 | 相关说明 | @@ -143,8 +143,8 @@ | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/yesno/tts1/run.sh | http://www.openslr.org/resources/1/waves_yesno.tar.gz | 数据集地址 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/yoloxochitl_mixtec/asr1/run.sh | http://www.openslr.org/resources/89/Yoloxochitl-Mixtec-Manifest.tgz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs/yoloxochitl_mixtec/asr1/run.sh | http://www.openslr.org/resources/89/Yoloxochitl-Mixtec-Data.tgz | 数据集链接 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aidatatang_200zh/asr1/local/data.sh | www.openslr.org/resources/62 | 下载配置 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aishell/asr1/local/data.sh | www.openslr.org/resources/33 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aidatatang_200zh/asr1/local/data.sh | http://www.openslr.org/resources/62 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aishell/asr1/local/data.sh | http://www.openslr.org/resources/33 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aishell3/tts1/local/data.sh | https://www.openslr.org/resources/93/data_aishell3.tgz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/aishell4/asr1/local/data.sh | https://www.openslr.org/resources/111/$room_name.tar.gz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/an4/asr1/local/data.sh | http://www.speech.cs.cmu.edu/databases/an4/ | 数据集地址 | @@ -159,13 +159,13 @@ | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/jdcinal/asr1/local/data.sh | http://tts.speech.cs.cmu.edu/awb/infomation_navigation_and_attentive_listening_0.2.zip | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/jv_openslr35/asr1/local/data.sh | https://www.openslr.org/resources/35/asr_javanese_${i}.zip | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librilight_limited/asr1/local/data.sh | https://dl.fbaipublicfiles.com/librilight/data/librispeech_finetuning.tgz | 数据集链接 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librilight_limited/asr1/local/data.sh | www.openslr.org/resources/12 | 数据集链接 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librilight_limited/asr1/local/data.sh | http://www.openslr.org/resources/12 | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librimix/enh1/local/data.sh | https://storage.googleapis.com/whisper-public/wham_noise.zip | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librispeech/asr1/conf/tuning/train_asr_transformer3_w2v_large_lv60_960h_finetuning_last_1layer.yaml | https://dl.fbaipublicfiles.com/fairseq/wav2vec/wav2vec2_vox_960h_new.pt | 权重地址 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librispeech/asr1/local/data.sh | www.openslr.org/resources/12 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librispeech/asr1/local/data.sh | http://www.openslr.org/resources/12 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librispeech/asr1/local/data.sh | http://www.openslr.org/resources/11/librispeech-lm-norm.txt.gz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/librispeech/asr1/local/data.sh | http://www.openslr.org/resources/11/librispeech-lm-norm.txt.gz | 数据集链接 | -| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/libritts/tts1/local/data.sh | www.openslr.org/resources/60 | 下载配置 | +| ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/libritts/tts1/local/data.sh | http://www.openslr.org/resources/60 | 下载配置 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/lrs2/lipreading1/local/data.sh | https://zenodo.org/record/5090353/files/lipread_lrw_pretrain.pt.tgz | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/mini_librispeech/diar1/local/data.sh | http://www.openslr.org/resources/26/sim_rir_8k.zip | 数据集链接 | | ModelZoo-PyTorch/PyTorch/built-in/audio/ESPnet2_for_PyTorch/egs2/mini_librispeech/diar1/local/data.sh | https://www.openslr.org/resources/17/ | 数据集链接 | diff --git a/PyTorch/built-in/audio/Wenet_Conformer_for_Pytorch/README.md b/PyTorch/built-in/audio/Wenet_Conformer_for_Pytorch/README.md index ac50f88d606d174e32f061619c3ec617aa413c1c..6cc7580269ec8f14a81f0386be28658389ba2089 100644 --- a/PyTorch/built-in/audio/Wenet_Conformer_for_Pytorch/README.md +++ b/PyTorch/built-in/audio/Wenet_Conformer_for_Pytorch/README.md @@ -89,7 +89,7 @@ Wenet是一款开源的、面向工业落地应用的语音识别工具包，主 | Torch_Version | 三方库依赖版本 | | ------------------- | ----------------- | - | PyTorch 2.1 | torch_audio==2.1.0 | + | PyTorch 2.1 | torchaudio==2.1.0 | - 安装依赖。 diff --git a/PyTorch/built-in/cv/classification/EfficientNetV2_for_PyTorch/README.md b/PyTorch/built-in/cv/classification/EfficientNetV2_for_PyTorch/README.md index 9f550ca2428165639e72d28169c20f8a3748e76c..d964c473fd2d9d85644ad9df0a204fd62f32a43a 100644 --- a/PyTorch/built-in/cv/classification/EfficientNetV2_for_PyTorch/README.md +++ b/PyTorch/built-in/cv/classification/EfficientNetV2_for_PyTorch/README.md @@ -12,7 +12,7 @@ ## 简述 -EfficientNetV2是Efficient的改进版，accuracy达到了发布时的SOTA水平，而且训练速度更快参数来更少。相对EfficientNetV1系列只关注准确率，参数量以及FLOPs，V2版本更加关注模型的实际训练速度。 +EfficientNetV2是Efficient的改进版，accuracy达到了发布时的SOTA水平，而且训练速度更快参数量更少。相对EfficientNetV1系列只关注准确率，参数量以及FLOPs，V2版本更加关注模型的实际训练速度。 - 参考实现： diff --git a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/README.md b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/README.md index 8bd62a3a34144ecdfc9abbfb1f288510d3a76e1e..181fc7748d91012ce8fabec730c769ec93b7f562 100644 --- a/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/README.md +++ b/PyTorch/built-in/cv/classification/ResNet50_ID4149_for_PyTorch/README.md @@ -96,7 +96,7 @@ ResNet是由微软研究院的Kaiming He等四名华人提出，是ImageNet竞 用户自行获取原始数据集，可选用的开源数据集包括ImageNet2012，CIFAR-10等，将数据集上传到服务器任意路径下并解压。 - Resnet18迁移使用到的ImageNet2012数据集目录结构参考如下所示。 + ImageNet2012数据集目录结构参考如下所示。 ``` ├── ImageNet2012 @@ -199,7 +199,7 @@ ResNet是由微软研究院的Kaiming He等四名华人提出，是ImageNet竞 ``` 公共参数： - --data //数据集路径 + --data_path //数据集路径 --arch //使用模型，默认：resnet50 --workers //加载数据进程数，默认：4 --epochs //重复训练次数，默认90 diff --git a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/CONTRIBUTING.md b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/CONTRIBUTING.md index 8a0c63299f02ff464f109c926c0ecc95c012c93c..309a554412a94ee3df4352ed74f793b338c3650d 100644 --- a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/CONTRIBUTING.md +++ b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/CONTRIBUTING.md @@ -35,7 +35,7 @@ We use the following tools for linting and formatting: Style configurations can be found in [setup.cfg](./setup.cfg). We use [pre-commit hook](https://pre-commit.com/) that checks and formats for `flake8`, `yapf`, `isort`, `trailing whitespaces`, `markdown files`, -fixes `end-of-files`, `double-quoted-strings`, `python-encoding-pragma`, `mixed-line-ending`, sorts `requirments.txt` automatically on every commit. +fixes `end-of-files`, `double-quoted-strings`, `python-encoding-pragma`, `mixed-line-ending`, sorts `requirements.txt` automatically on every commit. The config for a pre-commit hook is stored in [.pre-commit-config](https://github.com/open-mmlab/mmclassification/blob/master/.pre-commit-config.yaml). After you clone the repository, you will need to install initialize pre-commit hook. diff --git a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-CN-raw.md b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-CN-raw.md index 9e407d1c22ff709c727f5e76b7365a0e13d2660a..281cce9f752505fe7f0b712bad14661db2eff8b7 100644 --- a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-CN-raw.md +++ b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-CN-raw.md @@ -61,8 +61,8 @@ MMClassification 1.0 已经发布！目前仍在公测中，如果希望试用 2022/9/30 发布了 v0.24.0 版本 -- 支持了 **HorNet**，**EfficientFormerm**，**SwinTransformer V2**，**MViT** 等主干网络。 -- 支持了 Support Standford Cars 数据集。 +- 支持了 **HorNet**，**EfficientFormer**，**SwinTransformer V2**，**MViT** 等主干网络。 +- 支持了 Support Stanford Cars 数据集。 2022/5/1 发布了 v0.23.0 版本 diff --git a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-raw.md b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-raw.md index d129e7d04e5831826032dcbeafbad7c8140bc6f6..014ad1e6bf9f5a51cc4c585d7223beadc2f7b4b6 100644 --- a/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-raw.md +++ b/PyTorch/built-in/cv/classification/Resnet50_Cifar_for_PyTorch/README-raw.md @@ -65,8 +65,8 @@ to [the 1.x branch](https://github.com/open-mmlab/mmclassification/tree/1.x) and v0.24.0 was released in 30/9/2022. Highlights of the new version: -- Support **HorNet**, **EfficientFormerm**, **SwinTransformer V2** and **MViT** backbones. -- Support Standford Cars dataset. +- Support **HorNet**, **EfficientFormer**, **SwinTransformer V2** and **MViT** backbones. +- Support Stanford Cars dataset. v0.23.0 was released in 1/5/2022. Highlights of the new version: @@ -100,10 +100,10 @@ Please see [Getting Started](https://mmclassification.readthedocs.io/en/latest/g - [Learn about Configs](https://mmclassification.readthedocs.io/en/latest/tutorials/config.html) - [Fine-tune Models](https://mmclassification.readthedocs.io/en/latest/tutorials/finetune.html) - [Add New Dataset](https://mmclassification.readthedocs.io/en/latest/tutorials/new_dataset.html) -- [Customizie Data Pipeline](https://mmclassification.readthedocs.io/en/latest/tutorials/data_pipeline.html) +- [Custom Data Pipeline](https://mmclassification.readthedocs.io/en/latest/tutorials/data_pipeline.html) - [Add New Modules](https://mmclassification.readthedocs.io/en/latest/tutorials/new_modules.html) -- [Customizie Schedule](https://mmclassification.readthedocs.io/en/latest/tutorials/schedule.html) -- [Customizie Runtime Settings](https://mmclassification.readthedocs.io/en/latest/tutorials/runtime.html) +- [Customize Schedule](https://mmclassification.readthedocs.io/en/latest/tutorials/schedule.html) +- [Customize Runtime Settings](https://mmclassification.readthedocs.io/en/latest/tutorials/runtime.html) Colab tutorials are also provided: diff --git a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/README.md b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/README.md index c82ab203f91e6969f302fae2441164831a1578a6..2bbb1e23b53888a44d4e42da5bd3341134439e38 100644 --- a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/README.md +++ b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/README.md @@ -145,7 +145,7 @@ DB(Differentiable Binarization)是一种使用可微分二值图来实时文字 启动单卡训练。 ``` - 1.安装环境，确认预训练模型放置路径，若该路径路径与model_path默认值相同，可不传参，否则执行训练脚本时必须传入model_path参数； + 1.安装环境，确认预训练模型放置路径，若该路径与model_path默认值相同，可不传参，否则执行训练脚本时必须传入model_path参数； 2.开始训练 bash ./test/train_full_1p.sh --data_path=${datasets} --model_path=${pretrain_model} # 单卡精度 bash ./test/train_performance_1p.sh --data_path=${datasets} --model_path=${pretrain_model} # 单卡性能 @@ -157,7 +157,7 @@ DB(Differentiable Binarization)是一种使用可微分二值图来实时文字 启动8卡训练。 ``` - 1.安装环境，确认预训练模型放置路径，若该路径路径与model_path默认值相同，可不传参，否则执行训练脚本时必须传入model_path参数； + 1.安装环境，确认预训练模型放置路径，若该路径与model_path默认值相同，可不传参，否则执行训练脚本时必须传入model_path参数； 2.开始训练 bash ./test/train_full_8p.sh --data_path=${datasets} --model_path=${pretrain_model} # 8卡精度 bash ./test/train_performance_8p.sh --data_path=${datasets} --model_path=${pretrain_model} # 8卡性能 @@ -171,7 +171,7 @@ DB(Differentiable Binarization)是一种使用可微分二值图来实时文字 ``` - --data_path参数填写数据集路径，需写到数据集的一级目录，--reusme参数填写模型权重 + --data_path参数填写数据集路径，需写到数据集的一级目录，--resume参数填写模型权重 模型训练脚本参数说明如下。 diff --git a/PyTorch/built-in/mm/CLIP_for_PyTorch/public_address_statement.md b/PyTorch/built-in/mm/CLIP_for_PyTorch/public_address_statement.md index 0f22cea8b0a30995cde5ca19e1399e13f5432ccf..568331c742018deac0d828b2988bd35e84efe77d 100644 --- a/PyTorch/built-in/mm/CLIP_for_PyTorch/public_address_statement.md +++ b/PyTorch/built-in/mm/CLIP_for_PyTorch/public_address_statement.md @@ -38,8 +38,8 @@ | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/file_utils.py | https://pypi.ngc.nvidia.com | 三方库链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/file_utils.py | https://www.tensorflow.org/install | 三方库链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/integrations.py | https://app.sigopt.com/experiment/{experiment.id} | 创建experiment | -| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_flax_pytorch_utils.py | httphttps://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | -| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_flax_pytorch_utils.py | httphttps://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | +| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_flax_pytorch_utils.py | https://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | +| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_flax_pytorch_utils.py | https://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_tf_pytorch_utils.py | https://www.tensorflow.org/install/ | 三方库install | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_tf_pytorch_utils.py | https://www.tensorflow.org/install/ | 三方库install | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_tf_pytorch_utils.py | https://www.tensorflow.org/install/ | 三方库install | @@ -50,7 +50,7 @@ | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_tf_pytorch_utils.py | https://pytorch.org/ | pytorch链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_utils.py | https://www.tensorflow.org/install/ | 三方库install | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_utils.py | https://pytorch.org/ | pytorch链接 | -| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_utils.py | httphttps://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | +| ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/modeling_utils.py | https://flax.readthedocs.io/en/latest/installation.html | 三方库链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/models/albert/modeling_albert.py | https://www.tensorflow.org/install/ | 三方库install | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/models/albert/modeling_albert.py | https://pytorch.org/docs/stable/nn.html#torch.nn.Module | 模型说明链接 | | ModelZoo-PyTorch/PyTorch/built-in/mm/CLIP_for_PyTorch/transformers/src/transformers/models/albert/modeling_tf_albert.py | https://www.tensorflow.org/api_docs/python/tf/keras/Model | 模型说明链接 | diff --git a/PyTorch/contrib/audio/wav2vec2.0/CONTRIBUTING.md b/PyTorch/contrib/audio/wav2vec2.0/CONTRIBUTING.md index 60e90258877423bb458fafbc9d35781484dbe9c6..7f1254042472f522de1595d0ca9510c8a420decd 100644 --- a/PyTorch/contrib/audio/wav2vec2.0/CONTRIBUTING.md +++ b/PyTorch/contrib/audio/wav2vec2.0/CONTRIBUTING.md @@ -30,7 +30,7 @@ the root directory of this source tree. ## Pre-commit hooks In order to ensure your code lints, there are pre-commit hooks configured in the repository which you can install. After installation, they will automatically run each time you commit. -An abbreviated guide is given below; for more information, refer to [the offical pre-commit documentation](https://pre-commit.com/). +An abbreviated guide is given below; for more information, refer to [the official pre-commit documentation](https://pre-commit.com/). ### Installation ``` diff --git a/PyTorch/contrib/audio/wav2vec2.0/README.md b/PyTorch/contrib/audio/wav2vec2.0/README.md index 418ec34db82efa4669b217544f41a89586b8da89..1b62e71326f5b6085c325c177dc92c14f0ca612d 100644 --- a/PyTorch/contrib/audio/wav2vec2.0/README.md +++ b/PyTorch/contrib/audio/wav2vec2.0/README.md @@ -84,7 +84,7 @@ Wav2vec2.0是Meta在2020年发表的无监督语音预训练模型。它的核 主要参考 [wav2vec2.0](https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec) 进行 `LibriSpeech` 数据集准备。 用户需自己新建一个 `$data_path` 路径，用于放预训练模型和数据集，`$data_path` 可以设置为服务器的任意目录（注意存放的磁盘需要为NVME固态硬盘）。 - 下载 `LibirSpeech` 数据集，包括 `train-clean-100`，`dev-clean`，按照 [wav2vec2.0](https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec) 准备 `manifest`，统一放置到 `$data_path` 目录下。 + 下载 `LibriSpeech` 数据集，包括 `train-clean-100`，`dev-clean`，按照 [wav2vec2.0](https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec) 准备 `manifest`，统一放置到 `$data_path` 目录下。 数据集目录结构参考如下所示。 ``` $data_path diff --git a/PyTorch/contrib/cv/classification/HRNet_ID1780_for_PyTorch/README_old.md b/PyTorch/contrib/cv/classification/HRNet_ID1780_for_PyTorch/README_old.md index b39a69bd197093133f86ca3dc1115fc3d1582160..0243b2c9c662e2864ac79d507827a7d019b039ce 100755 --- a/PyTorch/contrib/cv/classification/HRNet_ID1780_for_PyTorch/README_old.md +++ b/PyTorch/contrib/cv/classification/HRNet_ID1780_for_PyTorch/README_old.md @@ -59,11 +59,11 @@ - bash ./test/train_eval_8p.sh --data_path=xxx --device_id=xxx - Training log - - test/output/devie_id/train_${device_id}.log # training detail log + - test/output/device_id/train_${device_id}.log # training detail log - - test/output/devie_id/HRNe_ID1780${device_id}_bs_8p_perf.log # 8p training performance result + - test/output/device_id/HRNet_ID1780${device_id}_bs_8p_perf.log # 8p training performance result - - test/output/devie_id/HRNe_ID1780${device_id}_bs_8p_acc.log # 8p training accuracy result + - test/output/device_id/HRNet_ID1780${device_id}_bs_8p_acc.log # 8p training accuracy result ```bash diff --git a/PyTorch/contrib/cv/classification/InceptionV3_ID1596_for_PyTorch/README.md b/PyTorch/contrib/cv/classification/InceptionV3_ID1596_for_PyTorch/README.md index 431e396ba03d32e5916ec9b755af80254a11afc5..802a058d4947e77ffd461571e2f6a358c8778a6d 100644 --- a/PyTorch/contrib/cv/classification/InceptionV3_ID1596_for_PyTorch/README.md +++ b/PyTorch/contrib/cv/classification/InceptionV3_ID1596_for_PyTorch/README.md @@ -157,7 +157,7 @@ GoogLeNet对网络中的传统卷积层进行了修改，提出了被称为Incep ``` 公共参数： -a // 模型名称 - --data // 数据集路径 + --data_path // 数据集路径 -j // 最大线程数 --output_dir // 输出目录 -b // 训练批次大小 diff --git a/PyTorch/dev/perf/ShuffleNetV2_iflytek_for_Pytorch/README.md b/PyTorch/dev/perf/ShuffleNetV2_iflytek_for_Pytorch/README.md index a2039312721ba035aa181cd4e7dc13d608dd1881..76c8ec83c1dd24ac1cfcc2fc7dfb3efae3812554 100644 --- a/PyTorch/dev/perf/ShuffleNetV2_iflytek_for_Pytorch/README.md +++ b/PyTorch/dev/perf/ShuffleNetV2_iflytek_for_Pytorch/README.md @@ -71,7 +71,7 @@ ShuffleNetV2是一个改进ShuffleNetV1的轻量级的网络，为了解决在 | Torch_Version | 三方库依赖版本 | |:--------------------------------:| :----------------------------------------------------------: | - | PyTorch 2.1 | pillow==9.5.0, torchvison==0.16.0 | + | PyTorch 2.1 | pillow==9.5.0, torchvision==0.16.0 | - 安装依赖。 @@ -128,7 +128,7 @@ ShuffleNetV2是一个改进ShuffleNetV1的轻量级的网络，为了解决在 该模型支持单机单卡训练和单机8卡训练。 - - 单机单卡卡训练 + - 单机单卡训练 启动单卡训练。 @@ -139,14 +139,14 @@ ShuffleNetV2是一个改进ShuffleNetV1的轻量级的网络，为了解决在 ``` bash ./test/train_performance_1p.sh ``` - - 单机8卡卡训练 + - 单机8卡训练 启动8卡训练。 ``` bash ./test/train_full_8p.sh ``` - - 单机8卡卡性能看护 + - 单机8卡性能看护 ``` bash ./test/train_performance_8p.sh ```