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@@ -0,0 +1 @@ +/allennlp_pvt_nightly-0.9.1.dev201910011800.tar.gz diff --git a/python-allennlp-pvt-nightly.spec b/python-allennlp-pvt-nightly.spec new file mode 100644 index 0000000..5b324d9 --- /dev/null +++ b/python-allennlp-pvt-nightly.spec @@ -0,0 +1,800 @@ +%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> + +[/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1) +[](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> + +[/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1) +[](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> + +[/statusIcon)](http://build.allennlp.org/viewType.html?buildTypeId=AllenNLP_AllenNLPCommits&guest=1) +[](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 @@ -0,0 +1 @@ +431b28bb5824fdacdc3879902c449e9c allennlp_pvt_nightly-0.9.1.dev201910011800.tar.gz |