From 9836fbcd4218a814526672caa21399014a093c29 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Mon, 10 Apr 2023 17:13:22 +0000 Subject: automatic import of python-spacy-transformers --- python-spacy-transformers.spec | 320 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 320 insertions(+) create mode 100644 python-spacy-transformers.spec (limited to 'python-spacy-transformers.spec') diff --git a/python-spacy-transformers.spec b/python-spacy-transformers.spec new file mode 100644 index 0000000..cfb5ab2 --- /dev/null +++ b/python-spacy-transformers.spec @@ -0,0 +1,320 @@ +%global _empty_manifest_terminate_build 0 +Name: python-spacy-transformers +Version: 1.2.2 +Release: 1 +Summary: spaCy pipelines for pre-trained BERT and other transformers +License: MIT +URL: https://spacy.io +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a1/fa/711780a25596a4254c81734a5ea3aa09874732a24b02cf36503e5399a407/spacy-transformers-1.2.2.tar.gz + +Requires: python3-spacy +Requires: python3-numpy +Requires: python3-transformers +Requires: python3-torch +Requires: python3-srsly +Requires: python3-spacy-alignments +Requires: python3-dataclasses +Requires: python3-cupy +Requires: python3-cupy-cuda100 +Requires: python3-cupy-cuda101 +Requires: python3-cupy-cuda102 +Requires: python3-cupy-cuda110 +Requires: python3-cupy-cuda111 +Requires: python3-cupy-cuda112 +Requires: python3-cupy-cuda80 +Requires: python3-cupy-cuda90 +Requires: python3-cupy-cuda91 +Requires: python3-cupy-cuda92 + +%description + + +# spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy + +This package provides [spaCy](https://github.com/explosion/spaCy) components and +architectures to use transformer models via +[Hugging Face's `transformers`](https://github.com/huggingface/transformers) in +spaCy. The result is convenient access to state-of-the-art transformer +architectures, such as BERT, GPT-2, XLNet, etc. + +> **This release requires [spaCy v3](https://spacy.io/usage/v3).** For +> the previous version of this library, see the +> [`v0.6.x` branch](https://github.com/explosion/spacy-transformers/tree/v0.6.x). + +[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/18/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=18) +[![PyPi](https://img.shields.io/pypi/v/spacy-transformers.svg?style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/spacy-transformers) +[![GitHub](https://img.shields.io/github/release/explosion/spacy-transformers/all.svg?style=flat-square&logo=github)](https://github.com/explosion/spacy-transformers/releases) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black) + +## Features + +- Use pretrained transformer models like **BERT**, **RoBERTa** and **XLNet** to + power your spaCy pipeline. +- Easy **multi-task learning**: backprop to one transformer model from several + pipeline components. +- Train using spaCy v3's powerful and extensible config system. +- Automatic alignment of transformer output to spaCy's tokenization. +- Easily customize what transformer data is saved in the `Doc` object. +- Easily customize how long documents are processed. +- Out-of-the-box serialization and model packaging. + +## 🚀 Installation + +Installing the package from pip will automatically install all dependencies, +including PyTorch and spaCy. Make sure you install this package **before** you +install the models. Also note that this package requires **Python 3.6+**, +**PyTorch v1.5+** and **spaCy v3.0+**. + +```bash +pip install 'spacy[transformers]' +``` + +For GPU installation, find your CUDA version using `nvcc --version` and add the +[version in brackets](https://spacy.io/usage/#gpu), e.g. +`spacy[transformers,cuda92]` for CUDA9.2 or `spacy[transformers,cuda100]` for +CUDA10.0. + +If you are having trouble installing PyTorch, follow the +[instructions](https://pytorch.org/get-started/locally/) on the official website +for your specific operating system and requirements, or try the following: + +```bash +pip install spacy-transformers -f https://download.pytorch.org/whl/torch_stable.html +``` + +## 📖 Documentation + +> ⚠️ **Important note:** This package has been extensively refactored to take +> advantage of [spaCy v3.0](https://spacy.io). Previous versions that +> were built for [spaCy v2.x](https://v2.spacy.io) worked considerably +> differently. Please see previous tagged versions of this README for +> documentation on prior versions. + +- 📘 + [Embeddings, Transformers and Transfer Learning](https://spacy.io/usage/embeddings-transformers): + How to use transformers in spaCy +- 📘 [Training Pipelines and Models](https://spacy.io/usage/training): + Train and update components on your own data and integrate custom models +- 📘 + [Layers and Model Architectures](https://spacy.io/usage/layers-architectures): + Power spaCy components with custom neural networks +- 📗 [`Transformer`](https://spacy.io/api/transformer): Pipeline + component API reference +- 📗 + [Transformer architectures](https://spacy.io/api/architectures#transformers): + Architectures and registered functions + + +%package -n python3-spacy-transformers +Summary: spaCy pipelines for pre-trained BERT and other transformers +Provides: python-spacy-transformers +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +BuildRequires: python3-cffi +BuildRequires: gcc +BuildRequires: gdb +%description -n python3-spacy-transformers + + +# spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy + +This package provides [spaCy](https://github.com/explosion/spaCy) components and +architectures to use transformer models via +[Hugging Face's `transformers`](https://github.com/huggingface/transformers) in +spaCy. The result is convenient access to state-of-the-art transformer +architectures, such as BERT, GPT-2, XLNet, etc. + +> **This release requires [spaCy v3](https://spacy.io/usage/v3).** For +> the previous version of this library, see the +> [`v0.6.x` branch](https://github.com/explosion/spacy-transformers/tree/v0.6.x). + +[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/18/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=18) +[![PyPi](https://img.shields.io/pypi/v/spacy-transformers.svg?style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/spacy-transformers) +[![GitHub](https://img.shields.io/github/release/explosion/spacy-transformers/all.svg?style=flat-square&logo=github)](https://github.com/explosion/spacy-transformers/releases) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black) + +## Features + +- Use pretrained transformer models like **BERT**, **RoBERTa** and **XLNet** to + power your spaCy pipeline. +- Easy **multi-task learning**: backprop to one transformer model from several + pipeline components. +- Train using spaCy v3's powerful and extensible config system. +- Automatic alignment of transformer output to spaCy's tokenization. +- Easily customize what transformer data is saved in the `Doc` object. +- Easily customize how long documents are processed. +- Out-of-the-box serialization and model packaging. + +## 🚀 Installation + +Installing the package from pip will automatically install all dependencies, +including PyTorch and spaCy. Make sure you install this package **before** you +install the models. Also note that this package requires **Python 3.6+**, +**PyTorch v1.5+** and **spaCy v3.0+**. + +```bash +pip install 'spacy[transformers]' +``` + +For GPU installation, find your CUDA version using `nvcc --version` and add the +[version in brackets](https://spacy.io/usage/#gpu), e.g. +`spacy[transformers,cuda92]` for CUDA9.2 or `spacy[transformers,cuda100]` for +CUDA10.0. + +If you are having trouble installing PyTorch, follow the +[instructions](https://pytorch.org/get-started/locally/) on the official website +for your specific operating system and requirements, or try the following: + +```bash +pip install spacy-transformers -f https://download.pytorch.org/whl/torch_stable.html +``` + +## 📖 Documentation + +> ⚠️ **Important note:** This package has been extensively refactored to take +> advantage of [spaCy v3.0](https://spacy.io). Previous versions that +> were built for [spaCy v2.x](https://v2.spacy.io) worked considerably +> differently. Please see previous tagged versions of this README for +> documentation on prior versions. + +- 📘 + [Embeddings, Transformers and Transfer Learning](https://spacy.io/usage/embeddings-transformers): + How to use transformers in spaCy +- 📘 [Training Pipelines and Models](https://spacy.io/usage/training): + Train and update components on your own data and integrate custom models +- 📘 + [Layers and Model Architectures](https://spacy.io/usage/layers-architectures): + Power spaCy components with custom neural networks +- 📗 [`Transformer`](https://spacy.io/api/transformer): Pipeline + component API reference +- 📗 + [Transformer architectures](https://spacy.io/api/architectures#transformers): + Architectures and registered functions + + +%package help +Summary: Development documents and examples for spacy-transformers +Provides: python3-spacy-transformers-doc +%description help + + +# spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy + +This package provides [spaCy](https://github.com/explosion/spaCy) components and +architectures to use transformer models via +[Hugging Face's `transformers`](https://github.com/huggingface/transformers) in +spaCy. The result is convenient access to state-of-the-art transformer +architectures, such as BERT, GPT-2, XLNet, etc. + +> **This release requires [spaCy v3](https://spacy.io/usage/v3).** For +> the previous version of this library, see the +> [`v0.6.x` branch](https://github.com/explosion/spacy-transformers/tree/v0.6.x). + +[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/18/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=18) +[![PyPi](https://img.shields.io/pypi/v/spacy-transformers.svg?style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/spacy-transformers) +[![GitHub](https://img.shields.io/github/release/explosion/spacy-transformers/all.svg?style=flat-square&logo=github)](https://github.com/explosion/spacy-transformers/releases) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black) + +## Features + +- Use pretrained transformer models like **BERT**, **RoBERTa** and **XLNet** to + power your spaCy pipeline. +- Easy **multi-task learning**: backprop to one transformer model from several + pipeline components. +- Train using spaCy v3's powerful and extensible config system. +- Automatic alignment of transformer output to spaCy's tokenization. +- Easily customize what transformer data is saved in the `Doc` object. +- Easily customize how long documents are processed. +- Out-of-the-box serialization and model packaging. + +## 🚀 Installation + +Installing the package from pip will automatically install all dependencies, +including PyTorch and spaCy. Make sure you install this package **before** you +install the models. Also note that this package requires **Python 3.6+**, +**PyTorch v1.5+** and **spaCy v3.0+**. + +```bash +pip install 'spacy[transformers]' +``` + +For GPU installation, find your CUDA version using `nvcc --version` and add the +[version in brackets](https://spacy.io/usage/#gpu), e.g. +`spacy[transformers,cuda92]` for CUDA9.2 or `spacy[transformers,cuda100]` for +CUDA10.0. + +If you are having trouble installing PyTorch, follow the +[instructions](https://pytorch.org/get-started/locally/) on the official website +for your specific operating system and requirements, or try the following: + +```bash +pip install spacy-transformers -f https://download.pytorch.org/whl/torch_stable.html +``` + +## 📖 Documentation + +> ⚠️ **Important note:** This package has been extensively refactored to take +> advantage of [spaCy v3.0](https://spacy.io). Previous versions that +> were built for [spaCy v2.x](https://v2.spacy.io) worked considerably +> differently. Please see previous tagged versions of this README for +> documentation on prior versions. + +- 📘 + [Embeddings, Transformers and Transfer Learning](https://spacy.io/usage/embeddings-transformers): + How to use transformers in spaCy +- 📘 [Training Pipelines and Models](https://spacy.io/usage/training): + Train and update components on your own data and integrate custom models +- 📘 + [Layers and Model Architectures](https://spacy.io/usage/layers-architectures): + Power spaCy components with custom neural networks +- 📗 [`Transformer`](https://spacy.io/api/transformer): Pipeline + component API reference +- 📗 + [Transformer architectures](https://spacy.io/api/architectures#transformers): + Architectures and registered functions + + +%prep +%autosetup -n spacy-transformers-1.2.2 + +%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-spacy-transformers -f filelist.lst +%dir %{python3_sitearch}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot - 1.2.2-1 +- Package Spec generated -- cgit v1.2.3