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+/allennlp_pvt_nightly-0.9.1.dev201910011800.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-allennlp-pvt-nightly
+Version:	0.9.1.dev201910011800
+Release:	1
+Summary:	An open-source NLP research library, built on PyTorch.
+License:	Apache
+URL:		https://github.com/allenai/allennlp
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/13/7e/9c323ca0333aef7af94087cac9ea61255691341109dd28ba99053ce3cd46/allennlp_pvt_nightly-0.9.1.dev201910011800.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-torch
+Requires:	python3-overrides
+Requires:	python3-nltk
+Requires:	python3-spacy
+Requires:	python3-numpy
+Requires:	python3-tensorboardX
+Requires:	python3-boto3
+Requires:	python3-flask
+Requires:	python3-flask-cors
+Requires:	python3-gevent
+Requires:	python3-requests
+Requires:	python3-tqdm
+Requires:	python3-editdistance
+Requires:	python3-h5py
+Requires:	python3-scikit-learn
+Requires:	python3-scipy
+Requires:	python3-pytz
+Requires:	python3-unidecode
+Requires:	python3-matplotlib
+Requires:	python3-pytest
+Requires:	python3-flaky
+Requires:	python3-responses
+Requires:	python3-numpydoc
+Requires:	python3-conllu
+Requires:	python3-parsimonious
+Requires:	python3-ftfy
+Requires:	python3-sqlparse
+Requires:	python3-word2number
+Requires:	python3-pytorch-pretrained-bert
+Requires:	python3-pytorch-transformers
+Requires:	python3-jsonpickle
+Requires:	python3-jsonnet
+
+%description
+<p align="center"><img width="40%" src="doc/static/allennlp-logo-dark.png" /></p>
+
+[![Build Status](http://build.allennlp.org/app/rest/builds/buildType:(id:AllenNLP_AllenNLPCommits)/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1)
+[![codecov](https://codecov.io/gh/allenai/allennlp/branch/master/graph/badge.svg)](https://codecov.io/gh/allenai/allennlp)
+
+An [Apache 2.0](https://github.com/allenai/allennlp/blob/master/LICENSE) NLP research library, built on PyTorch,
+for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
+
+## Quick Links
+
+* [Website](https://allennlp.org/)
+* [Tutorial](https://allennlp.org/tutorials)
+* [Forum](https://discourse.allennlp.org)
+* [Documentation](https://allenai.github.io/allennlp-docs/)
+* [Contributing Guidelines](CONTRIBUTING.md)
+* [Model List](MODELS.md)
+* [Continuous Build](http://build.allennlp.org/)
+
+## Package Overview
+
+<table>
+<tr>
+    <td><b> allennlp </b></td>
+    <td> an open-source NLP research library, built on PyTorch </td>
+</tr>
+<tr>
+    <td><b> allennlp.commands </b></td>
+    <td> functionality for a CLI and web service </td>
+</tr>
+<tr>
+    <td><b> allennlp.data </b></td>
+    <td> a data processing module for loading datasets and encoding strings as integers for representation in matrices </td>
+</tr>
+<tr>
+    <td><b> allennlp.models </b></td>
+    <td> a collection of state-of-the-art models </td>
+</tr>
+<tr>
+    <td><b> allennlp.modules </b></td>
+    <td> a collection of PyTorch modules for use with text </td>
+</tr>
+<tr>
+    <td><b> allennlp.nn </b></td>
+    <td> tensor utility functions, such as initializers and activation functions </td>
+</tr>
+<tr>
+    <td><b> allennlp.service </b></td>
+    <td> a web server to that can serve demos for your models </td>
+</tr>
+<tr>
+    <td><b> allennlp.training </b></td>
+    <td> functionality for training models </td>
+</tr>
+</table>
+
+## Installation
+
+AllenNLP requires Python 3.6.1 or later. The preferred way to install AllenNLP is via `pip`.  Just run `pip install allennlp` in your Python environment and you're good to go!
+
+If you need pointers on setting up an appropriate Python environment or would like to install AllenNLP using a different method, see below.
+
+Windows is currently not officially supported, although we try to fix issues when they are easily addressed.
+
+### Installing via pip
+
+#### Setting up a virtual environment
+
+[Conda](https://conda.io/) can be used set up a virtual environment with the
+version of Python required for AllenNLP.  If you already have a Python 3.6 or 3.7
+environment you want to use, you can skip to the 'installing via pip' section.
+
+1.  [Download and install Conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
+
+2.  Create a Conda environment with Python 3.6
+
+    ```bash
+    conda create -n allennlp python=3.6
+    ```
+
+3.  Activate the Conda environment. You will need to activate the Conda environment in each terminal in which you want to use AllenNLP.
+
+    ```bash
+    conda activate allennlp
+    ```
+
+#### Installing the library and dependencies
+
+Installing the library and dependencies is simple using `pip`.
+
+   ```bash
+   pip install allennlp
+   ```
+
+That's it! You're now ready to build and train AllenNLP models.
+AllenNLP installs a script when you install the python package, meaning you can run allennlp commands just by typing `allennlp` into a terminal.
+
+You can now test your installation with `allennlp test-install`.
+
+_`pip` currently installs Pytorch for CUDA 9 only (or no GPU). If you require an older version,
+please visit https://pytorch.org/ and install the relevant pytorch binary._
+
+### Installing using Docker
+
+Docker provides a virtual machine with everything set up to run AllenNLP--
+whether you will leverage a GPU or just run on a CPU.  Docker provides more
+isolation and consistency, and also makes it easy to distribute your
+environment to a compute cluster.
+
+Once you have [installed Docker](https://docs.docker.com/engine/installation/)
+just run the following command to get an environment that will run on either the cpu or gpu.
+
+   ```bash
+   mkdir -p $HOME/.allennlp/
+   docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0
+   ```
+
+You can test the Docker environment with `docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0 test-install`.
+
+### Installing from source
+
+You can also install AllenNLP by cloning our git repository:
+
+  ```bash
+  git clone https://github.com/allenai/allennlp.git
+  ```
+
+Create a Python 3.6 virtual environment, and install AllenNLP in `editable` mode by running:
+
+  ```bash
+  pip install --editable .
+  ```
+
+This will make `allennlp` available on your system but it will use the sources from the local clone
+you made of the source repository.
+
+You can test your installation with `allennlp test-install`.
+The full development environment also requires the JVM and `perl`,
+which must be installed separately.  `./scripts/verify.py` will run
+the full suite of tests used by our continuous build environment.
+
+## Running AllenNLP
+
+Once you've installed AllenNLP, you can run the command-line interface either
+with the `allennlp` command (if you installed via `pip`) or `allennlp` (if you installed via source).
+
+```
+$ allennlp
+Run AllenNLP
+
+optional arguments:
+  -h, --help    show this help message and exit
+  --version     show program's version number and exit
+
+Commands:
+
+    configure   Run the configuration wizard.
+    train       Train a model.
+    evaluate    Evaluate the specified model + dataset.
+    predict     Use a trained model to make predictions.
+    make-vocab  Create a vocabulary.
+    elmo        Create word vectors using a pretrained ELMo model.
+    fine-tune   Continue training a model on a new dataset.
+    dry-run     Create a vocabulary, compute dataset statistics and other
+                training utilities.
+    test-install
+                Run the unit tests.
+    find-lr     Find a learning rate range.
+```
+
+## Docker images
+
+AllenNLP releases Docker images to [Docker Hub](https://hub.docker.com/r/allennlp/) for each release.  For information on how to run these releases, see [Installing using Docker](#installing-using-docker).
+
+### Building a Docker image
+
+For various reasons you may need to create your own AllenNLP Docker image.
+The same image can be used either with a CPU or a GPU.
+
+First, you need to [install Docker](https://www.docker.com/get-started).
+Then run the following command
+(it will take some time, as it completely builds the
+environment needed to run AllenNLP.)
+
+```bash
+docker build -f Dockerfile.pip --tag allennlp/allennlp:latest .
+```
+
+You should now be able to see this image listed by running `docker images allennlp`.
+
+```
+REPOSITORY          TAG                 IMAGE ID            CREATED             SIZE
+allennlp/allennlp            latest              b66aee6cb593        5 minutes ago       2.38GB
+```
+
+### Running the Docker image
+
+You can run the image with `docker run --rm -it allennlp/allennlp:latest`.  The `--rm` flag cleans up the image on exit and the `-it` flags make the session interactive so you can use the bash shell the Docker image starts.
+
+You can test your installation by running  `allennlp test-install`.
+
+## Issues
+
+Everyone is welcome to file issues with either feature requests, bug reports, or general questions.  As a small team with our own internal goals, we may ask for contributions if a prompt fix doesn't fit into our roadmap.  We allow users a two week window to follow up on questions, after which we will close issues.  They can be re-opened if there is further discussion.
+
+## Contributions
+
+The AllenNLP team at AI2 (@allenai) welcomes contributions from the greater AllenNLP community, and, if you would like to get a change into the library, this is likely the fastest approach.  If you would like to contribute a larger feature, we recommend first creating an issue with a proposed design for discussion.  This will prevent you from spending significant time on an implementation which has a technical limitation someone could have pointed out early on.  Small contributions can be made directly in a pull request.
+
+Pull requests (PRs) must have one approving review and no requested changes before they are merged.  As AllenNLP is primarily driven by AI2 (@allenai) we reserve the right to reject or revert contributions that we don't think are good additions.
+
+## Citing
+
+If you use AllenNLP in your research, please cite [AllenNLP: A Deep Semantic Natural Language Processing Platform](https://www.semanticscholar.org/paper/AllenNLP%3A-A-Deep-Semantic-Natural-Language-Platform-Gardner-Grus/a5502187140cdd98d76ae711973dbcdaf1fef46d).
+
+```bibtex
+@inproceedings{Gardner2017AllenNLP,
+  title={AllenNLP: A Deep Semantic Natural Language Processing Platform},
+  author={Matt Gardner and Joel Grus and Mark Neumann and Oyvind Tafjord
+    and Pradeep Dasigi and Nelson F. Liu and Matthew Peters and
+    Michael Schmitz and Luke S. Zettlemoyer},
+  year={2017},
+  Eprint = {arXiv:1803.07640},
+}
+```
+
+## Team
+
+AllenNLP is an open-source project backed by [the Allen Institute for Artificial Intelligence (AI2)](https://allenai.org/).
+AI2 is a non-profit institute with the mission to contribute to humanity through high-impact AI research and engineering.
+To learn more about who specifically contributed to this codebase, see [our contributors](https://github.com/allenai/allennlp/graphs/contributors) page.
+
+
+
+
+%package -n python3-allennlp-pvt-nightly
+Summary:	An open-source NLP research library, built on PyTorch.
+Provides:	python-allennlp-pvt-nightly
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-allennlp-pvt-nightly
+<p align="center"><img width="40%" src="doc/static/allennlp-logo-dark.png" /></p>
+
+[![Build Status](http://build.allennlp.org/app/rest/builds/buildType:(id:AllenNLP_AllenNLPCommits)/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1)
+[![codecov](https://codecov.io/gh/allenai/allennlp/branch/master/graph/badge.svg)](https://codecov.io/gh/allenai/allennlp)
+
+An [Apache 2.0](https://github.com/allenai/allennlp/blob/master/LICENSE) NLP research library, built on PyTorch,
+for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
+
+## Quick Links
+
+* [Website](https://allennlp.org/)
+* [Tutorial](https://allennlp.org/tutorials)
+* [Forum](https://discourse.allennlp.org)
+* [Documentation](https://allenai.github.io/allennlp-docs/)
+* [Contributing Guidelines](CONTRIBUTING.md)
+* [Model List](MODELS.md)
+* [Continuous Build](http://build.allennlp.org/)
+
+## Package Overview
+
+<table>
+<tr>
+    <td><b> allennlp </b></td>
+    <td> an open-source NLP research library, built on PyTorch </td>
+</tr>
+<tr>
+    <td><b> allennlp.commands </b></td>
+    <td> functionality for a CLI and web service </td>
+</tr>
+<tr>
+    <td><b> allennlp.data </b></td>
+    <td> a data processing module for loading datasets and encoding strings as integers for representation in matrices </td>
+</tr>
+<tr>
+    <td><b> allennlp.models </b></td>
+    <td> a collection of state-of-the-art models </td>
+</tr>
+<tr>
+    <td><b> allennlp.modules </b></td>
+    <td> a collection of PyTorch modules for use with text </td>
+</tr>
+<tr>
+    <td><b> allennlp.nn </b></td>
+    <td> tensor utility functions, such as initializers and activation functions </td>
+</tr>
+<tr>
+    <td><b> allennlp.service </b></td>
+    <td> a web server to that can serve demos for your models </td>
+</tr>
+<tr>
+    <td><b> allennlp.training </b></td>
+    <td> functionality for training models </td>
+</tr>
+</table>
+
+## Installation
+
+AllenNLP requires Python 3.6.1 or later. The preferred way to install AllenNLP is via `pip`.  Just run `pip install allennlp` in your Python environment and you're good to go!
+
+If you need pointers on setting up an appropriate Python environment or would like to install AllenNLP using a different method, see below.
+
+Windows is currently not officially supported, although we try to fix issues when they are easily addressed.
+
+### Installing via pip
+
+#### Setting up a virtual environment
+
+[Conda](https://conda.io/) can be used set up a virtual environment with the
+version of Python required for AllenNLP.  If you already have a Python 3.6 or 3.7
+environment you want to use, you can skip to the 'installing via pip' section.
+
+1.  [Download and install Conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
+
+2.  Create a Conda environment with Python 3.6
+
+    ```bash
+    conda create -n allennlp python=3.6
+    ```
+
+3.  Activate the Conda environment. You will need to activate the Conda environment in each terminal in which you want to use AllenNLP.
+
+    ```bash
+    conda activate allennlp
+    ```
+
+#### Installing the library and dependencies
+
+Installing the library and dependencies is simple using `pip`.
+
+   ```bash
+   pip install allennlp
+   ```
+
+That's it! You're now ready to build and train AllenNLP models.
+AllenNLP installs a script when you install the python package, meaning you can run allennlp commands just by typing `allennlp` into a terminal.
+
+You can now test your installation with `allennlp test-install`.
+
+_`pip` currently installs Pytorch for CUDA 9 only (or no GPU). If you require an older version,
+please visit https://pytorch.org/ and install the relevant pytorch binary._
+
+### Installing using Docker
+
+Docker provides a virtual machine with everything set up to run AllenNLP--
+whether you will leverage a GPU or just run on a CPU.  Docker provides more
+isolation and consistency, and also makes it easy to distribute your
+environment to a compute cluster.
+
+Once you have [installed Docker](https://docs.docker.com/engine/installation/)
+just run the following command to get an environment that will run on either the cpu or gpu.
+
+   ```bash
+   mkdir -p $HOME/.allennlp/
+   docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0
+   ```
+
+You can test the Docker environment with `docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0 test-install`.
+
+### Installing from source
+
+You can also install AllenNLP by cloning our git repository:
+
+  ```bash
+  git clone https://github.com/allenai/allennlp.git
+  ```
+
+Create a Python 3.6 virtual environment, and install AllenNLP in `editable` mode by running:
+
+  ```bash
+  pip install --editable .
+  ```
+
+This will make `allennlp` available on your system but it will use the sources from the local clone
+you made of the source repository.
+
+You can test your installation with `allennlp test-install`.
+The full development environment also requires the JVM and `perl`,
+which must be installed separately.  `./scripts/verify.py` will run
+the full suite of tests used by our continuous build environment.
+
+## Running AllenNLP
+
+Once you've installed AllenNLP, you can run the command-line interface either
+with the `allennlp` command (if you installed via `pip`) or `allennlp` (if you installed via source).
+
+```
+$ allennlp
+Run AllenNLP
+
+optional arguments:
+  -h, --help    show this help message and exit
+  --version     show program's version number and exit
+
+Commands:
+
+    configure   Run the configuration wizard.
+    train       Train a model.
+    evaluate    Evaluate the specified model + dataset.
+    predict     Use a trained model to make predictions.
+    make-vocab  Create a vocabulary.
+    elmo        Create word vectors using a pretrained ELMo model.
+    fine-tune   Continue training a model on a new dataset.
+    dry-run     Create a vocabulary, compute dataset statistics and other
+                training utilities.
+    test-install
+                Run the unit tests.
+    find-lr     Find a learning rate range.
+```
+
+## Docker images
+
+AllenNLP releases Docker images to [Docker Hub](https://hub.docker.com/r/allennlp/) for each release.  For information on how to run these releases, see [Installing using Docker](#installing-using-docker).
+
+### Building a Docker image
+
+For various reasons you may need to create your own AllenNLP Docker image.
+The same image can be used either with a CPU or a GPU.
+
+First, you need to [install Docker](https://www.docker.com/get-started).
+Then run the following command
+(it will take some time, as it completely builds the
+environment needed to run AllenNLP.)
+
+```bash
+docker build -f Dockerfile.pip --tag allennlp/allennlp:latest .
+```
+
+You should now be able to see this image listed by running `docker images allennlp`.
+
+```
+REPOSITORY          TAG                 IMAGE ID            CREATED             SIZE
+allennlp/allennlp            latest              b66aee6cb593        5 minutes ago       2.38GB
+```
+
+### Running the Docker image
+
+You can run the image with `docker run --rm -it allennlp/allennlp:latest`.  The `--rm` flag cleans up the image on exit and the `-it` flags make the session interactive so you can use the bash shell the Docker image starts.
+
+You can test your installation by running  `allennlp test-install`.
+
+## Issues
+
+Everyone is welcome to file issues with either feature requests, bug reports, or general questions.  As a small team with our own internal goals, we may ask for contributions if a prompt fix doesn't fit into our roadmap.  We allow users a two week window to follow up on questions, after which we will close issues.  They can be re-opened if there is further discussion.
+
+## Contributions
+
+The AllenNLP team at AI2 (@allenai) welcomes contributions from the greater AllenNLP community, and, if you would like to get a change into the library, this is likely the fastest approach.  If you would like to contribute a larger feature, we recommend first creating an issue with a proposed design for discussion.  This will prevent you from spending significant time on an implementation which has a technical limitation someone could have pointed out early on.  Small contributions can be made directly in a pull request.
+
+Pull requests (PRs) must have one approving review and no requested changes before they are merged.  As AllenNLP is primarily driven by AI2 (@allenai) we reserve the right to reject or revert contributions that we don't think are good additions.
+
+## Citing
+
+If you use AllenNLP in your research, please cite [AllenNLP: A Deep Semantic Natural Language Processing Platform](https://www.semanticscholar.org/paper/AllenNLP%3A-A-Deep-Semantic-Natural-Language-Platform-Gardner-Grus/a5502187140cdd98d76ae711973dbcdaf1fef46d).
+
+```bibtex
+@inproceedings{Gardner2017AllenNLP,
+  title={AllenNLP: A Deep Semantic Natural Language Processing Platform},
+  author={Matt Gardner and Joel Grus and Mark Neumann and Oyvind Tafjord
+    and Pradeep Dasigi and Nelson F. Liu and Matthew Peters and
+    Michael Schmitz and Luke S. Zettlemoyer},
+  year={2017},
+  Eprint = {arXiv:1803.07640},
+}
+```
+
+## Team
+
+AllenNLP is an open-source project backed by [the Allen Institute for Artificial Intelligence (AI2)](https://allenai.org/).
+AI2 is a non-profit institute with the mission to contribute to humanity through high-impact AI research and engineering.
+To learn more about who specifically contributed to this codebase, see [our contributors](https://github.com/allenai/allennlp/graphs/contributors) page.
+
+
+
+
+%package help
+Summary:	Development documents and examples for allennlp-pvt-nightly
+Provides:	python3-allennlp-pvt-nightly-doc
+%description help
+<p align="center"><img width="40%" src="doc/static/allennlp-logo-dark.png" /></p>
+
+[![Build Status](http://build.allennlp.org/app/rest/builds/buildType:(id:AllenNLP_AllenNLPCommits)/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1)
+[![codecov](https://codecov.io/gh/allenai/allennlp/branch/master/graph/badge.svg)](https://codecov.io/gh/allenai/allennlp)
+
+An [Apache 2.0](https://github.com/allenai/allennlp/blob/master/LICENSE) NLP research library, built on PyTorch,
+for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
+
+## Quick Links
+
+* [Website](https://allennlp.org/)
+* [Tutorial](https://allennlp.org/tutorials)
+* [Forum](https://discourse.allennlp.org)
+* [Documentation](https://allenai.github.io/allennlp-docs/)
+* [Contributing Guidelines](CONTRIBUTING.md)
+* [Model List](MODELS.md)
+* [Continuous Build](http://build.allennlp.org/)
+
+## Package Overview
+
+<table>
+<tr>
+    <td><b> allennlp </b></td>
+    <td> an open-source NLP research library, built on PyTorch </td>
+</tr>
+<tr>
+    <td><b> allennlp.commands </b></td>
+    <td> functionality for a CLI and web service </td>
+</tr>
+<tr>
+    <td><b> allennlp.data </b></td>
+    <td> a data processing module for loading datasets and encoding strings as integers for representation in matrices </td>
+</tr>
+<tr>
+    <td><b> allennlp.models </b></td>
+    <td> a collection of state-of-the-art models </td>
+</tr>
+<tr>
+    <td><b> allennlp.modules </b></td>
+    <td> a collection of PyTorch modules for use with text </td>
+</tr>
+<tr>
+    <td><b> allennlp.nn </b></td>
+    <td> tensor utility functions, such as initializers and activation functions </td>
+</tr>
+<tr>
+    <td><b> allennlp.service </b></td>
+    <td> a web server to that can serve demos for your models </td>
+</tr>
+<tr>
+    <td><b> allennlp.training </b></td>
+    <td> functionality for training models </td>
+</tr>
+</table>
+
+## Installation
+
+AllenNLP requires Python 3.6.1 or later. The preferred way to install AllenNLP is via `pip`.  Just run `pip install allennlp` in your Python environment and you're good to go!
+
+If you need pointers on setting up an appropriate Python environment or would like to install AllenNLP using a different method, see below.
+
+Windows is currently not officially supported, although we try to fix issues when they are easily addressed.
+
+### Installing via pip
+
+#### Setting up a virtual environment
+
+[Conda](https://conda.io/) can be used set up a virtual environment with the
+version of Python required for AllenNLP.  If you already have a Python 3.6 or 3.7
+environment you want to use, you can skip to the 'installing via pip' section.
+
+1.  [Download and install Conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
+
+2.  Create a Conda environment with Python 3.6
+
+    ```bash
+    conda create -n allennlp python=3.6
+    ```
+
+3.  Activate the Conda environment. You will need to activate the Conda environment in each terminal in which you want to use AllenNLP.
+
+    ```bash
+    conda activate allennlp
+    ```
+
+#### Installing the library and dependencies
+
+Installing the library and dependencies is simple using `pip`.
+
+   ```bash
+   pip install allennlp
+   ```
+
+That's it! You're now ready to build and train AllenNLP models.
+AllenNLP installs a script when you install the python package, meaning you can run allennlp commands just by typing `allennlp` into a terminal.
+
+You can now test your installation with `allennlp test-install`.
+
+_`pip` currently installs Pytorch for CUDA 9 only (or no GPU). If you require an older version,
+please visit https://pytorch.org/ and install the relevant pytorch binary._
+
+### Installing using Docker
+
+Docker provides a virtual machine with everything set up to run AllenNLP--
+whether you will leverage a GPU or just run on a CPU.  Docker provides more
+isolation and consistency, and also makes it easy to distribute your
+environment to a compute cluster.
+
+Once you have [installed Docker](https://docs.docker.com/engine/installation/)
+just run the following command to get an environment that will run on either the cpu or gpu.
+
+   ```bash
+   mkdir -p $HOME/.allennlp/
+   docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0
+   ```
+
+You can test the Docker environment with `docker run --rm -v $HOME/.allennlp:/root/.allennlp allennlp/allennlp:v0.9.0 test-install`.
+
+### Installing from source
+
+You can also install AllenNLP by cloning our git repository:
+
+  ```bash
+  git clone https://github.com/allenai/allennlp.git
+  ```
+
+Create a Python 3.6 virtual environment, and install AllenNLP in `editable` mode by running:
+
+  ```bash
+  pip install --editable .
+  ```
+
+This will make `allennlp` available on your system but it will use the sources from the local clone
+you made of the source repository.
+
+You can test your installation with `allennlp test-install`.
+The full development environment also requires the JVM and `perl`,
+which must be installed separately.  `./scripts/verify.py` will run
+the full suite of tests used by our continuous build environment.
+
+## Running AllenNLP
+
+Once you've installed AllenNLP, you can run the command-line interface either
+with the `allennlp` command (if you installed via `pip`) or `allennlp` (if you installed via source).
+
+```
+$ allennlp
+Run AllenNLP
+
+optional arguments:
+  -h, --help    show this help message and exit
+  --version     show program's version number and exit
+
+Commands:
+
+    configure   Run the configuration wizard.
+    train       Train a model.
+    evaluate    Evaluate the specified model + dataset.
+    predict     Use a trained model to make predictions.
+    make-vocab  Create a vocabulary.
+    elmo        Create word vectors using a pretrained ELMo model.
+    fine-tune   Continue training a model on a new dataset.
+    dry-run     Create a vocabulary, compute dataset statistics and other
+                training utilities.
+    test-install
+                Run the unit tests.
+    find-lr     Find a learning rate range.
+```
+
+## Docker images
+
+AllenNLP releases Docker images to [Docker Hub](https://hub.docker.com/r/allennlp/) for each release.  For information on how to run these releases, see [Installing using Docker](#installing-using-docker).
+
+### Building a Docker image
+
+For various reasons you may need to create your own AllenNLP Docker image.
+The same image can be used either with a CPU or a GPU.
+
+First, you need to [install Docker](https://www.docker.com/get-started).
+Then run the following command
+(it will take some time, as it completely builds the
+environment needed to run AllenNLP.)
+
+```bash
+docker build -f Dockerfile.pip --tag allennlp/allennlp:latest .
+```
+
+You should now be able to see this image listed by running `docker images allennlp`.
+
+```
+REPOSITORY          TAG                 IMAGE ID            CREATED             SIZE
+allennlp/allennlp            latest              b66aee6cb593        5 minutes ago       2.38GB
+```
+
+### Running the Docker image
+
+You can run the image with `docker run --rm -it allennlp/allennlp:latest`.  The `--rm` flag cleans up the image on exit and the `-it` flags make the session interactive so you can use the bash shell the Docker image starts.
+
+You can test your installation by running  `allennlp test-install`.
+
+## Issues
+
+Everyone is welcome to file issues with either feature requests, bug reports, or general questions.  As a small team with our own internal goals, we may ask for contributions if a prompt fix doesn't fit into our roadmap.  We allow users a two week window to follow up on questions, after which we will close issues.  They can be re-opened if there is further discussion.
+
+## Contributions
+
+The AllenNLP team at AI2 (@allenai) welcomes contributions from the greater AllenNLP community, and, if you would like to get a change into the library, this is likely the fastest approach.  If you would like to contribute a larger feature, we recommend first creating an issue with a proposed design for discussion.  This will prevent you from spending significant time on an implementation which has a technical limitation someone could have pointed out early on.  Small contributions can be made directly in a pull request.
+
+Pull requests (PRs) must have one approving review and no requested changes before they are merged.  As AllenNLP is primarily driven by AI2 (@allenai) we reserve the right to reject or revert contributions that we don't think are good additions.
+
+## Citing
+
+If you use AllenNLP in your research, please cite [AllenNLP: A Deep Semantic Natural Language Processing Platform](https://www.semanticscholar.org/paper/AllenNLP%3A-A-Deep-Semantic-Natural-Language-Platform-Gardner-Grus/a5502187140cdd98d76ae711973dbcdaf1fef46d).
+
+```bibtex
+@inproceedings{Gardner2017AllenNLP,
+  title={AllenNLP: A Deep Semantic Natural Language Processing Platform},
+  author={Matt Gardner and Joel Grus and Mark Neumann and Oyvind Tafjord
+    and Pradeep Dasigi and Nelson F. Liu and Matthew Peters and
+    Michael Schmitz and Luke S. Zettlemoyer},
+  year={2017},
+  Eprint = {arXiv:1803.07640},
+}
+```
+
+## Team
+
+AllenNLP is an open-source project backed by [the Allen Institute for Artificial Intelligence (AI2)](https://allenai.org/).
+AI2 is a non-profit institute with the mission to contribute to humanity through high-impact AI research and engineering.
+To learn more about who specifically contributed to this codebase, see [our contributors](https://github.com/allenai/allennlp/graphs/contributors) page.
+
+
+
+
+%prep
+%autosetup -n allennlp-pvt-nightly-0.9.1.dev201910011800
+
+%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-allennlp-pvt-nightly -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.1.dev201910011800-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..9bb1265
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+431b28bb5824fdacdc3879902c449e9c  allennlp_pvt_nightly-0.9.1.dev201910011800.tar.gz