automatic import of python-model-indexopeneuler20.03

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+++ b/.gitignore
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+/model-index-0.1.11.tar.gz
diff --git a/python-model-index.spec b/python-model-index.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-model-index
+Version:	0.1.11
+Release:	1
+Summary:	Create a source of truth for ML model results and browse it on Papers with Code
+License:	MIT
+URL:		https://github.com/paperswithcode/model-index
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/25/91/3db595e51266e5a32f4a26e3b4c4212ba83b4ce649196e81565cf0dcdec2/model-index-0.1.11.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pyyaml
+Requires:	python3-markdown
+Requires:	python3-ordered-set
+Requires:	python3-click
+
+%description
+# model-index: maintain a source of truth for ML models
+
+<p align="center">
+
+<a href="https://app.circleci.com/pipelines/github/paperswithcode/model-index">
+  <img alt="Tests" src="https://img.shields.io/circleci/build/github/paperswithcode/model-index/main">
+</a>
+
+<a href="https://pypi.org/project/model-index/">
+  <img alt="PyPI" src="https://img.shields.io/pypi/v/model-index">
+</a>
+
+<a href="https://model-index.readthedocs.io/en/latest/">
+  <img alt="Docs" src="https://img.shields.io/readthedocs/model-index">
+</a>
+
+</p>
+
+`model-index` has two goals:
+- Make it easy to maintain a source-of-truth index of Machine Learning model metadata 
+- Enable the community browse this model metadata on [Papers with Code](https://paperswithcode.com/)
+
+The main design principle of `model-index` is **flexibility**. You can store your model metadata however is the
+most convenient for you - as JSONs, YAMLs or as annotations inside markdown. `model-index` provides a convenient
+way to collect all this metadata into a single file that's browsable, searchable and comparable.
+
+You can use this library locally or choose to upload the metadata to [Papers with Code](https://paperswithcode.com)
+to have your library featured on the website. 
+
+## How it works
+
+There is a root file for the model index: `model-index.yml` that links to (or contains) metadata. 
+
+```yaml
+Models:
+  - Name: Inception v3
+    Metadata:
+      FLOPs: 5731284192
+      Parameters: 23834568
+      Training Data: ImageNet  
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Image Classification
+        Dataset: ImageNet
+        Metrics:
+          Top 1 Accuracy: 74.67%
+          Top 5 Accuracy: 92.1%
+    Paper: https://arxiv.org/abs/1512.00567v3
+    Code: https://github.com/rwightman/pytorch-image-models/blob/timm/models/inception_v3.py#L442
+    Weights: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth 
+    README: docs/inception-v3-readme.md
+```
+
+All fields except for `Name` are **optional**. You can add any fields you like, but the ones above have a 
+standard meaning across different models and libraries. 
+
+We recommend putting the `model-index.yml` file in the root of your repository (so that relative links such as 
+`docs/inception-v3-readme.md` are easier to write), but you can also put it anywhere else in the repository (e.g.
+in your `docs/` or `models/` folder). 
+
+### Storing metadata in markdown files
+
+Metadata can also be directly stored in a model's README file. For example in this `docs/rexnet.md` file:
+
+```markdown
+<!--
+Type: model-index
+Name: RexNet
+Metadata: 
+  Epochs: 400
+  Batch Size: 512
+Paper: https://arxiv.org/abs/2007.00992v1
+-->
+
+# Summary
+
+Rank Expansion Networks (ReXNets) follow a set of new design 
+principles for designing bottlenecks in image classification models.
+
+## Usage
+
+import timm
+m = timm.create_model('rexnet_100', pretrained=True)
+m.eval()
+```
+
+In this case, you just need to include this markdown file into the global `model-index.yml` file:
+
+```yaml
+Models:
+  - docs/rexnet.md
+```
+
+## Get started
+
+Check out our [official documentation](https://model-index.readthedocs.io/en/latest/) on how to get started. 
+
+## Uploading to Papers with Code
+
+To feature your library on Papers with Code, get in touch with `hello@paperswithcode.com` and the model index
+of your library will be automatically included into Papers with Code. 
+
+
+
+
+
+
+
+
+
+
+
+
+
+%package -n python3-model-index
+Summary:	Create a source of truth for ML model results and browse it on Papers with Code
+Provides:	python-model-index
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-model-index
+# model-index: maintain a source of truth for ML models
+
+<p align="center">
+
+<a href="https://app.circleci.com/pipelines/github/paperswithcode/model-index">
+  <img alt="Tests" src="https://img.shields.io/circleci/build/github/paperswithcode/model-index/main">
+</a>
+
+<a href="https://pypi.org/project/model-index/">
+  <img alt="PyPI" src="https://img.shields.io/pypi/v/model-index">
+</a>
+
+<a href="https://model-index.readthedocs.io/en/latest/">
+  <img alt="Docs" src="https://img.shields.io/readthedocs/model-index">
+</a>
+
+</p>
+
+`model-index` has two goals:
+- Make it easy to maintain a source-of-truth index of Machine Learning model metadata 
+- Enable the community browse this model metadata on [Papers with Code](https://paperswithcode.com/)
+
+The main design principle of `model-index` is **flexibility**. You can store your model metadata however is the
+most convenient for you - as JSONs, YAMLs or as annotations inside markdown. `model-index` provides a convenient
+way to collect all this metadata into a single file that's browsable, searchable and comparable.
+
+You can use this library locally or choose to upload the metadata to [Papers with Code](https://paperswithcode.com)
+to have your library featured on the website. 
+
+## How it works
+
+There is a root file for the model index: `model-index.yml` that links to (or contains) metadata. 
+
+```yaml
+Models:
+  - Name: Inception v3
+    Metadata:
+      FLOPs: 5731284192
+      Parameters: 23834568
+      Training Data: ImageNet  
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Image Classification
+        Dataset: ImageNet
+        Metrics:
+          Top 1 Accuracy: 74.67%
+          Top 5 Accuracy: 92.1%
+    Paper: https://arxiv.org/abs/1512.00567v3
+    Code: https://github.com/rwightman/pytorch-image-models/blob/timm/models/inception_v3.py#L442
+    Weights: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth 
+    README: docs/inception-v3-readme.md
+```
+
+All fields except for `Name` are **optional**. You can add any fields you like, but the ones above have a 
+standard meaning across different models and libraries. 
+
+We recommend putting the `model-index.yml` file in the root of your repository (so that relative links such as 
+`docs/inception-v3-readme.md` are easier to write), but you can also put it anywhere else in the repository (e.g.
+in your `docs/` or `models/` folder). 
+
+### Storing metadata in markdown files
+
+Metadata can also be directly stored in a model's README file. For example in this `docs/rexnet.md` file:
+
+```markdown
+<!--
+Type: model-index
+Name: RexNet
+Metadata: 
+  Epochs: 400
+  Batch Size: 512
+Paper: https://arxiv.org/abs/2007.00992v1
+-->
+
+# Summary
+
+Rank Expansion Networks (ReXNets) follow a set of new design 
+principles for designing bottlenecks in image classification models.
+
+## Usage
+
+import timm
+m = timm.create_model('rexnet_100', pretrained=True)
+m.eval()
+```
+
+In this case, you just need to include this markdown file into the global `model-index.yml` file:
+
+```yaml
+Models:
+  - docs/rexnet.md
+```
+
+## Get started
+
+Check out our [official documentation](https://model-index.readthedocs.io/en/latest/) on how to get started. 
+
+## Uploading to Papers with Code
+
+To feature your library on Papers with Code, get in touch with `hello@paperswithcode.com` and the model index
+of your library will be automatically included into Papers with Code. 
+
+
+
+
+
+
+
+
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for model-index
+Provides:	python3-model-index-doc
+%description help
+# model-index: maintain a source of truth for ML models
+
+<p align="center">
+
+<a href="https://app.circleci.com/pipelines/github/paperswithcode/model-index">
+  <img alt="Tests" src="https://img.shields.io/circleci/build/github/paperswithcode/model-index/main">
+</a>
+
+<a href="https://pypi.org/project/model-index/">
+  <img alt="PyPI" src="https://img.shields.io/pypi/v/model-index">
+</a>
+
+<a href="https://model-index.readthedocs.io/en/latest/">
+  <img alt="Docs" src="https://img.shields.io/readthedocs/model-index">
+</a>
+
+</p>
+
+`model-index` has two goals:
+- Make it easy to maintain a source-of-truth index of Machine Learning model metadata 
+- Enable the community browse this model metadata on [Papers with Code](https://paperswithcode.com/)
+
+The main design principle of `model-index` is **flexibility**. You can store your model metadata however is the
+most convenient for you - as JSONs, YAMLs or as annotations inside markdown. `model-index` provides a convenient
+way to collect all this metadata into a single file that's browsable, searchable and comparable.
+
+You can use this library locally or choose to upload the metadata to [Papers with Code](https://paperswithcode.com)
+to have your library featured on the website. 
+
+## How it works
+
+There is a root file for the model index: `model-index.yml` that links to (or contains) metadata. 
+
+```yaml
+Models:
+  - Name: Inception v3
+    Metadata:
+      FLOPs: 5731284192
+      Parameters: 23834568
+      Training Data: ImageNet  
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Image Classification
+        Dataset: ImageNet
+        Metrics:
+          Top 1 Accuracy: 74.67%
+          Top 5 Accuracy: 92.1%
+    Paper: https://arxiv.org/abs/1512.00567v3
+    Code: https://github.com/rwightman/pytorch-image-models/blob/timm/models/inception_v3.py#L442
+    Weights: https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth 
+    README: docs/inception-v3-readme.md
+```
+
+All fields except for `Name` are **optional**. You can add any fields you like, but the ones above have a 
+standard meaning across different models and libraries. 
+
+We recommend putting the `model-index.yml` file in the root of your repository (so that relative links such as 
+`docs/inception-v3-readme.md` are easier to write), but you can also put it anywhere else in the repository (e.g.
+in your `docs/` or `models/` folder). 
+
+### Storing metadata in markdown files
+
+Metadata can also be directly stored in a model's README file. For example in this `docs/rexnet.md` file:
+
+```markdown
+<!--
+Type: model-index
+Name: RexNet
+Metadata: 
+  Epochs: 400
+  Batch Size: 512
+Paper: https://arxiv.org/abs/2007.00992v1
+-->
+
+# Summary
+
+Rank Expansion Networks (ReXNets) follow a set of new design 
+principles for designing bottlenecks in image classification models.
+
+## Usage
+
+import timm
+m = timm.create_model('rexnet_100', pretrained=True)
+m.eval()
+```
+
+In this case, you just need to include this markdown file into the global `model-index.yml` file:
+
+```yaml
+Models:
+  - docs/rexnet.md
+```
+
+## Get started
+
+Check out our [official documentation](https://model-index.readthedocs.io/en/latest/) on how to get started. 
+
+## Uploading to Papers with Code
+
+To feature your library on Papers with Code, get in touch with `hello@paperswithcode.com` and the model index
+of your library will be automatically included into Papers with Code. 
+
+
+
+
+
+
+
+
+
+
+
+
+
+%prep
+%autosetup -n model-index-0.1.11
+
+%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-model-index -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.11-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..e1df609
--- /dev/null
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@@ -0,0 +1 @@
+bef5cf5bf398945ef110cfd3a72a8965  model-index-0.1.11.tar.gz