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@@ -0,0 +1 @@ +/tfkit-0.8.20.tar.gz diff --git a/python-tfkit.spec b/python-tfkit.spec new file mode 100644 index 0000000..4b5eb4c --- /dev/null +++ b/python-tfkit.spec @@ -0,0 +1,470 @@ +%global _empty_manifest_terminate_build 0 +Name: python-tfkit +Version: 0.8.20 +Release: 1 +Summary: Transformers kit - Multi-task QA/Tagging/Multi-label Multi-Class Classification/Generation with BERT/ALBERT/T5/BERT +License: Apache +URL: https://github.com/voidful/TFkit +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/e4/2c/3fcd1b598bf9df1fa113f9a6b962ac9be7cf4f2ba61683c1c9b7b775c238/tfkit-0.8.20.tar.gz +BuildArch: noarch + +Requires: python3-transformers +Requires: python3-tensorboard +Requires: python3-tensorboardX +Requires: python3-torch +Requires: python3-matplotlib +Requires: python3-nlp2 +Requires: python3-tqdm +Requires: python3-inquirer +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-pytorch-crf +Requires: python3-sentencepiece +Requires: python3-pandas +Requires: python3-accelerate +Requires: python3-joblib +Requires: python3-scikit-learn +Requires: python3-editdistance + +%description +<p align="center"> + <br> + <img src="https://raw.githubusercontent.com/voidful/TFkit/master/docs/img/tfkit.png" width="300"/> + <br> +</p> +<br/> +<p align="center"> + <a href="https://pypi.org/project/tfkit/"> + <img alt="PyPI" src="https://img.shields.io/pypi/v/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Download" src="https://img.shields.io/pypi/dm/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Build" src="https://img.shields.io/github/workflow/status/voidful/tfkit/Python package"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Last Commit" src="https://img.shields.io/github/last-commit/voidful/tfkit"> + </a> + <a href="https://www.codefactor.io/repository/github/voidful/tfkit/overview/master"> + <img src="https://www.codefactor.io/repository/github/voidful/tfkit/badge/master" alt="CodeFactor" /> + </a> + <a href="https://github.com/voidful/tfkit"> + <img src="https://visitor-badge.glitch.me/badge?page_id=voidful.tfkit" alt="Visitor" /> + </a> + <a href="https://codecov.io/gh/voidful/TFkit"> + <img src="https://codecov.io/gh/voidful/TFkit/branch/master/graph/badge.svg" /> + </a> +</p> + +## What is it +TFKit is a tool kit mainly for language generation. +It leverages the use of transformers on many tasks with different models in this all-in-one framework. +All you need is a little change of config. + +## Task Supported +With transformer models - BERT/ALBERT/T5/BART...... +| | | +|-|-| +| Text Generation | :memo: seq2seq language model | +| Text Generation | :pen: causal language model | +| Text Generation | :printer: once generation model / once generation model with ctc loss | +| Text Generation | :pencil: onebyone generation model | + +# Getting Started +Learn more from the [document](https://voidful.github.io/TFkit/). + +## How To Use + +### Step 0: Install +Simple installation from PyPI +```bash +pip install git+https://github.com/voidful/TFkit.git@refactor-dataset +``` + +### Step 1: Prepare dataset in csv format +[Task format](https://voidful.tech/TFkit/tasks/) +``` +input, target +``` + +### Step 2: Train model +```bash +tfkit-train \ +--task clas \ +--config xlm-roberta-base \ +--train training_data.csv \ +--test testing_data.csv \ +--lr 4e-5 \ +--maxlen 384 \ +--epoch 10 \ +--savedir roberta_sentiment_classificer +``` + +### Step 3: Evaluate +```bash +tfkit-eval \ +--task roberta_sentiment_classificer/1.pt \ +--metric clas \ +--valid testing_data.csv +``` + +## Advanced features +<details> + <summary>Multi-task training </summary> + + ```bash + tfkit-train \ + --task clas clas \ + --config xlm-roberta-base \ + --train training_data_taskA.csv training_data_taskB.csv \ + --test testing_data_taskA.csv testing_data_taskB.csv \ + --lr 4e-5 \ + --maxlen 384 \ + --epoch 10 \ + --savedir roberta_sentiment_classificer_multi_task + ``` +</details> + +## Not maintained task +Due to time constraints, the following tasks are temporarily not supported +| | | +|-|-| +| Classification | :label: multi-class and multi-label classification | +| Question Answering | :page_with_curl: extractive qa | +| Question Answering | :radio_button: multiple-choice qa | +| Tagging | :eye_speech_bubble: sequence level tagging / sequence level with crf | +| Self-supervise Learning | :diving_mask: mask language model | + +## Supplement +- [transformers models list](https://huggingface.co/models): you can find any pretrained models here +- [nlprep](https://github.com/voidful/NLPrep): download and preprocessing data in one line +- [nlp2go](https://github.com/voidful/nlp2go): create demo api as quickly as possible. + + +## Contributing +Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/voidful/tfkit/blob/master/CONTRIBUTING.md). + +## License  + +* [License](https://github.com/voidful/tfkit/blob/master/LICENSE) + +## Icons reference +Icons modify from <a href="http://www.freepik.com/" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> +Icons modify from <a href="https://www.flaticon.com/authors/nikita-golubev" title="Nikita Golubev">Nikita Golubev</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> + + + + +%package -n python3-tfkit +Summary: Transformers kit - Multi-task QA/Tagging/Multi-label Multi-Class Classification/Generation with BERT/ALBERT/T5/BERT +Provides: python-tfkit +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-tfkit +<p align="center"> + <br> + <img src="https://raw.githubusercontent.com/voidful/TFkit/master/docs/img/tfkit.png" width="300"/> + <br> +</p> +<br/> +<p align="center"> + <a href="https://pypi.org/project/tfkit/"> + <img alt="PyPI" src="https://img.shields.io/pypi/v/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Download" src="https://img.shields.io/pypi/dm/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Build" src="https://img.shields.io/github/workflow/status/voidful/tfkit/Python package"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Last Commit" src="https://img.shields.io/github/last-commit/voidful/tfkit"> + </a> + <a href="https://www.codefactor.io/repository/github/voidful/tfkit/overview/master"> + <img src="https://www.codefactor.io/repository/github/voidful/tfkit/badge/master" alt="CodeFactor" /> + </a> + <a href="https://github.com/voidful/tfkit"> + <img src="https://visitor-badge.glitch.me/badge?page_id=voidful.tfkit" alt="Visitor" /> + </a> + <a href="https://codecov.io/gh/voidful/TFkit"> + <img src="https://codecov.io/gh/voidful/TFkit/branch/master/graph/badge.svg" /> + </a> +</p> + +## What is it +TFKit is a tool kit mainly for language generation. +It leverages the use of transformers on many tasks with different models in this all-in-one framework. +All you need is a little change of config. + +## Task Supported +With transformer models - BERT/ALBERT/T5/BART...... +| | | +|-|-| +| Text Generation | :memo: seq2seq language model | +| Text Generation | :pen: causal language model | +| Text Generation | :printer: once generation model / once generation model with ctc loss | +| Text Generation | :pencil: onebyone generation model | + +# Getting Started +Learn more from the [document](https://voidful.github.io/TFkit/). + +## How To Use + +### Step 0: Install +Simple installation from PyPI +```bash +pip install git+https://github.com/voidful/TFkit.git@refactor-dataset +``` + +### Step 1: Prepare dataset in csv format +[Task format](https://voidful.tech/TFkit/tasks/) +``` +input, target +``` + +### Step 2: Train model +```bash +tfkit-train \ +--task clas \ +--config xlm-roberta-base \ +--train training_data.csv \ +--test testing_data.csv \ +--lr 4e-5 \ +--maxlen 384 \ +--epoch 10 \ +--savedir roberta_sentiment_classificer +``` + +### Step 3: Evaluate +```bash +tfkit-eval \ +--task roberta_sentiment_classificer/1.pt \ +--metric clas \ +--valid testing_data.csv +``` + +## Advanced features +<details> + <summary>Multi-task training </summary> + + ```bash + tfkit-train \ + --task clas clas \ + --config xlm-roberta-base \ + --train training_data_taskA.csv training_data_taskB.csv \ + --test testing_data_taskA.csv testing_data_taskB.csv \ + --lr 4e-5 \ + --maxlen 384 \ + --epoch 10 \ + --savedir roberta_sentiment_classificer_multi_task + ``` +</details> + +## Not maintained task +Due to time constraints, the following tasks are temporarily not supported +| | | +|-|-| +| Classification | :label: multi-class and multi-label classification | +| Question Answering | :page_with_curl: extractive qa | +| Question Answering | :radio_button: multiple-choice qa | +| Tagging | :eye_speech_bubble: sequence level tagging / sequence level with crf | +| Self-supervise Learning | :diving_mask: mask language model | + +## Supplement +- [transformers models list](https://huggingface.co/models): you can find any pretrained models here +- [nlprep](https://github.com/voidful/NLPrep): download and preprocessing data in one line +- [nlp2go](https://github.com/voidful/nlp2go): create demo api as quickly as possible. + + +## Contributing +Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/voidful/tfkit/blob/master/CONTRIBUTING.md). + +## License  + +* [License](https://github.com/voidful/tfkit/blob/master/LICENSE) + +## Icons reference +Icons modify from <a href="http://www.freepik.com/" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> +Icons modify from <a href="https://www.flaticon.com/authors/nikita-golubev" title="Nikita Golubev">Nikita Golubev</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> + + + + +%package help +Summary: Development documents and examples for tfkit +Provides: python3-tfkit-doc +%description help +<p align="center"> + <br> + <img src="https://raw.githubusercontent.com/voidful/TFkit/master/docs/img/tfkit.png" width="300"/> + <br> +</p> +<br/> +<p align="center"> + <a href="https://pypi.org/project/tfkit/"> + <img alt="PyPI" src="https://img.shields.io/pypi/v/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Download" src="https://img.shields.io/pypi/dm/tfkit"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Build" src="https://img.shields.io/github/workflow/status/voidful/tfkit/Python package"> + </a> + <a href="https://github.com/voidful/tfkit"> + <img alt="Last Commit" src="https://img.shields.io/github/last-commit/voidful/tfkit"> + </a> + <a href="https://www.codefactor.io/repository/github/voidful/tfkit/overview/master"> + <img src="https://www.codefactor.io/repository/github/voidful/tfkit/badge/master" alt="CodeFactor" /> + </a> + <a href="https://github.com/voidful/tfkit"> + <img src="https://visitor-badge.glitch.me/badge?page_id=voidful.tfkit" alt="Visitor" /> + </a> + <a href="https://codecov.io/gh/voidful/TFkit"> + <img src="https://codecov.io/gh/voidful/TFkit/branch/master/graph/badge.svg" /> + </a> +</p> + +## What is it +TFKit is a tool kit mainly for language generation. +It leverages the use of transformers on many tasks with different models in this all-in-one framework. +All you need is a little change of config. + +## Task Supported +With transformer models - BERT/ALBERT/T5/BART...... +| | | +|-|-| +| Text Generation | :memo: seq2seq language model | +| Text Generation | :pen: causal language model | +| Text Generation | :printer: once generation model / once generation model with ctc loss | +| Text Generation | :pencil: onebyone generation model | + +# Getting Started +Learn more from the [document](https://voidful.github.io/TFkit/). + +## How To Use + +### Step 0: Install +Simple installation from PyPI +```bash +pip install git+https://github.com/voidful/TFkit.git@refactor-dataset +``` + +### Step 1: Prepare dataset in csv format +[Task format](https://voidful.tech/TFkit/tasks/) +``` +input, target +``` + +### Step 2: Train model +```bash +tfkit-train \ +--task clas \ +--config xlm-roberta-base \ +--train training_data.csv \ +--test testing_data.csv \ +--lr 4e-5 \ +--maxlen 384 \ +--epoch 10 \ +--savedir roberta_sentiment_classificer +``` + +### Step 3: Evaluate +```bash +tfkit-eval \ +--task roberta_sentiment_classificer/1.pt \ +--metric clas \ +--valid testing_data.csv +``` + +## Advanced features +<details> + <summary>Multi-task training </summary> + + ```bash + tfkit-train \ + --task clas clas \ + --config xlm-roberta-base \ + --train training_data_taskA.csv training_data_taskB.csv \ + --test testing_data_taskA.csv testing_data_taskB.csv \ + --lr 4e-5 \ + --maxlen 384 \ + --epoch 10 \ + --savedir roberta_sentiment_classificer_multi_task + ``` +</details> + +## Not maintained task +Due to time constraints, the following tasks are temporarily not supported +| | | +|-|-| +| Classification | :label: multi-class and multi-label classification | +| Question Answering | :page_with_curl: extractive qa | +| Question Answering | :radio_button: multiple-choice qa | +| Tagging | :eye_speech_bubble: sequence level tagging / sequence level with crf | +| Self-supervise Learning | :diving_mask: mask language model | + +## Supplement +- [transformers models list](https://huggingface.co/models): you can find any pretrained models here +- [nlprep](https://github.com/voidful/NLPrep): download and preprocessing data in one line +- [nlp2go](https://github.com/voidful/nlp2go): create demo api as quickly as possible. + + +## Contributing +Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/voidful/tfkit/blob/master/CONTRIBUTING.md). + +## License  + +* [License](https://github.com/voidful/tfkit/blob/master/LICENSE) + +## Icons reference +Icons modify from <a href="http://www.freepik.com/" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> +Icons modify from <a href="https://www.flaticon.com/authors/nikita-golubev" title="Nikita Golubev">Nikita Golubev</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a> + + + + +%prep +%autosetup -n tfkit-0.8.20 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-tfkit -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.20-1 +- Package Spec generated @@ -0,0 +1 @@ +faa556bcb30a1c7e7407d94a07c1562e tfkit-0.8.20.tar.gz |