Merge pull request #2271 from aaugustin/improve-setup-and-requirements

Improve setup and requirements

.circleci/config.yml

@@ -10,55 +10,62 @@ jobs:
         parallelism: 1
         steps:
             - checkout
-            - run: sudo pip install torch
-            - run: sudo pip install tensorflow
-            - run: sudo pip install --progress-bar off .
-            - run: sudo pip install pytest codecov pytest-cov pytest-xdist
-            - run: sudo pip install tensorboardX scikit-learn
+            - run: sudo pip install .[sklearn,tf,torch,testing]
+            - run: sudo pip install codecov pytest-cov
             - run: python -m pytest -n 8 --dist=loadfile -s -v ./tests/ --cov
             - run: codecov
-    run_tests_torch:
+    run_all_tests_torch_and_tf:
         working_directory: ~/transformers
         docker:
             - image: circleci/python:3.5
         environment:
             OMP_NUM_THREADS: 1
+            RUN_SLOW: yes
+            RUN_CUSTOM_TOKENIZERS: yes
         resource_class: xlarge
         parallelism: 1
         steps:
             - checkout
-            - run: sudo pip install torch
-            - run: sudo pip install --progress-bar off .
-            - run: sudo pip install pytest codecov pytest-cov pytest-xdist
-            - run: sudo pip install tensorboardX scikit-learn
+            - run: sudo pip install .[mecab,sklearn,tf,torch,testing]
+            - run: python -m pytest -n 8 --dist=loadfile -s -v ./tests/
+    run_tests_torch:
+        working_directory: ~/transformers
+        docker:
+            - image: circleci/python:3.7
+        environment:
+            OMP_NUM_THREADS: 1
+        resource_class: xlarge
+        parallelism: 1
+        steps:
+            - checkout
+            - run: sudo pip install .[sklearn,torch,testing]
+            - run: sudo pip install codecov pytest-cov
             - run: python -m pytest -n 8 --dist=loadfile -s -v ./tests/ --cov
             - run: codecov
     run_tests_tf:
         working_directory: ~/transformers
         docker:
-            - image: circleci/python:3.5
+            - image: circleci/python:3.7
         environment:
             OMP_NUM_THREADS: 1
         resource_class: xlarge
         parallelism: 1
         steps:
             - checkout
-            - run: sudo pip install tensorflow
-            - run: sudo pip install --progress-bar off .
-            - run: sudo pip install pytest codecov pytest-cov pytest-xdist
-            - run: sudo pip install tensorboardX scikit-learn
+            - run: sudo pip install .[sklearn,tf,testing]
+            - run: sudo pip install codecov pytest-cov
             - run: python -m pytest -n 8 --dist=loadfile -s -v ./tests/ --cov
             - run: codecov
     run_tests_custom_tokenizers:
         working_directory: ~/transformers
         docker:
             - image: circleci/python:3.5
+        environment:
+            RUN_CUSTOM_TOKENIZERS: yes
         steps:
             - checkout
-            - run: sudo pip install --progress-bar off .
-            - run: sudo pip install pytest pytest-xdist
-            - run: sudo pip install mecab-python3
-            - run: RUN_CUSTOM_TOKENIZERS=1 python -m pytest -sv ./tests/test_tokenization_bert_japanese.py
+            - run: sudo pip install .[mecab,testing]
+            - run: python -m pytest -sv ./tests/test_tokenization_bert_japanese.py
     run_examples_torch:
         working_directory: ~/transformers
         docker:
@@ -69,10 +76,8 @@ jobs:
         parallelism: 1
         steps:
             - checkout
-            - run: sudo pip install torch
-            - run: sudo pip install --progress-bar off .
-            - run: sudo pip install pytest pytest-xdist
-            - run: sudo pip install tensorboardX scikit-learn
+            - run: sudo pip install .[sklearn,torch,testing]
+            - run: sudo pip install -r examples/requirements.txt
             - run: python -m pytest -n 8 --dist=loadfile -s -v ./examples/
     deploy_doc:
         working_directory: ~/transformers
@@ -80,11 +85,10 @@ jobs:
             - image: circleci/python:3.5
         steps:
             - add_ssh_keys:
-                  fingerprints:
-                      - "5b:7a:95:18:07:8c:aa:76:4c:60:35:88:ad:60:56:71"
+                fingerprints:
+                    - "5b:7a:95:18:07:8c:aa:76:4c:60:35:88:ad:60:56:71"
             - checkout
-            - run: sudo pip install --progress-bar off -r docs/requirements.txt
-            - run: sudo pip install --progress-bar off .
+            - run: sudo pip install .[tf,torch,docs]
             - run: ./.circleci/deploy.sh
     check_code_quality:
         working_directory: ~/transformers
@@ -94,9 +98,9 @@ jobs:
         parallelism: 1
         steps:
             - checkout
-            - run: sudo pip install --editable .
-            - run: sudo pip install torch tensorflow
-            - run: sudo pip install black git+git://github.com/timothycrosley/isort.git@e63ae06ec7d70b06df9e528357650281a3d3ec22#egg=isort flake8
+            # we need a version of isort with https://github.com/timothycrosley/isort/pull/1000
+            - run: sudo pip install git+git://github.com/timothycrosley/isort.git@e63ae06ec7d70b06df9e528357650281a3d3ec22#egg=isort
+            - run: sudo pip install .[tf,torch,quality]
             - run: black --check --line-length 119 examples templates tests src utils
             - run: isort --check-only --recursive examples templates tests src utils
             - run: flake8 examples templates tests src utils
@@ -127,3 +131,13 @@ workflows:
             - run_tests_torch
             - run_tests_tf
             - deploy_doc: *workflow_filters
+    run_slow_tests:
+        triggers:
+            - schedule:
+                cron: "0 4 * * 1"
+                filters:
+                    branches:
+                        only:
+                            - master
+        jobs:
+            - run_all_tests_torch_and_tf

CONTRIBUTING.md

@@ -100,9 +100,10 @@ Follow these steps to start contributing:
 
 1. Fork the [repository](https://github.com/huggingface/transformers) by
    clicking on the 'Fork' button on the repository's page. This creates a copy of the code
-   under your github user account.
+   under your GitHub user account.
+
 2. Clone your fork to your local disk, and add the base repository as a remote:
-   
+
    ```bash
    $ git clone git@github.com:<your Github handle>/transformers.git
    $ cd transformers
@@ -114,43 +115,78 @@ Follow these steps to start contributing:
    ```bash
    $ git checkout -b a-descriptive-name-for-my-changes
    ```
-   
+
    **do not** work on the `master` branch.
-   
+
 4. Set up a development environment by running the following command in a virtual environment:
 
    ```bash
-   $ pip install -r requirements-dev.txt
+   $ pip install -e .[dev]
    ```
 
-5. Develop the features on your branch. Add changed files using `git add` and
-   then `git commit` to record your changes locally:
-   
+   (If transformers was already installed in the virtual environment, remove
+   it with `pip uninstall transformers` before reinstalling it in editable
+   mode with the `-e` flag.)
+
+   Right now, we need an unreleased version of `isort` to avoid a
+   [bug](https://github.com/timothycrosley/isort/pull/1000):
+
+   ```bash
+   $ pip install -U git+git://github.com/timothycrosley/isort.git@e63ae06ec7d70b06df9e528357650281a3d3ec22#egg=isort
+   ```
+
+5. Develop the features on your branch.
+
+   As you work on the features, you should make sure that the test suite
+   passes:
+
+   ```bash
+   $ make test
+   ```
+
+   `transformers` relies on `black` and `isort` to format its source code
+   consistently. After you make changes, format them with:
+
+   ```bash
+   $ make style
+   ```
+
+   `transformers` also uses `flake8` to check for coding mistakes. Quality
+   control runs in CI, however you can also run the same checks with:
+
+   ```bash
+   $ make quality
+   ```
+
+   Once you're happy with your changes, add changed files using `git add` and
+   make a commit with `git commit` to record your changes locally:
+
    ```bash
    $ git add modified_file.py
    $ git commit
    ```
-   
+
    Please write [good commit
-   messages](https://chris.beams.io/posts/git-commit/). It
-   is a good idea to sync your copy of the code with the original repository
-   regularly. This way you can quickly account for changes:
-   
+   messages](https://chris.beams.io/posts/git-commit/).
+
+   It is a good idea to sync your copy of the code with the original
+   repository regularly. This way you can quickly account for changes:
+
    ```bash
    $ git fetch upstream
    $ git rebase upstream/master
    ```
-   
+
    Push the changes to your account using:
-   
+
    ```bash
    $ git push -u origin a-descriptive-name-for-my-changes
    ```
-   
+
 6. Once you are satisfied (**and the checklist below is happy too**), go to the
-   webpage of your fork on Github. Click on 'Pull request' to send your changes
+   webpage of your fork on GitHub. Click on 'Pull request' to send your changes
    to the project maintainers for review.
-   
+
 7. It's ok if maintainers ask you for changes. It happens to core contributors
    too! So everyone can see the changes in the Pull request, work in your local
    branch and push the changes to your fork. They will automatically appear in
@@ -171,6 +207,53 @@ Follow these steps to start contributing:
 6. All public methods must have informative docstrings;
 
 
+### Tests
+
+You can run 🤗 Transformers tests with `unittest` or `pytest`.
+
+We like `pytest` and `pytest-xdist` because it's faster. From the root of the
+repository, here's how to run tests with `pytest` for the library:
+
+```bash
+$ python -m pytest -n auto --dist=loadfile -s -v ./tests/
+```
+
+and for the examples:
+
+```bash
+$ pip install -r examples/requirements.txt  # only needed the first time
+$ python -m pytest -n auto --dist=loadfile -s -v ./examples/
+```
+
+In fact, that's how `make test` and `make test-examples` are implemented!
+
+You can specify a smaller set of tests in order to test only the feature
+you're working on.
+
+By default, slow tests are skipped. Set the `RUN_SLOW` environment variable to
+`yes` to run them. This will download many gigabytes of models — make sure you
+have enough disk space and a good Internet connection, or a lot of patience!
+
+```bash
+$ RUN_SLOW=yes python -m pytest -n auto --dist=loadfile -s -v ./tests/
+$ RUN_SLOW=yes python -m pytest -n auto --dist=loadfile -s -v ./examples/
+```
+
+Likewise, set the `RUN_CUSTOM_TOKENIZERS` environment variable to `yes` to run
+tests for custom tokenizers, which don't run by default either.
+
+🤗 Transformers uses `pytest` as a test runner only. It doesn't use any
+`pytest`-specific features in the test suite itself.
+
+This means `unittest` is fully supported. Here's how to run tests with
+`unittest`:
+
+```bash
+$ python -m unittest discover -s tests -t . -v
+$ python -m unittest discover -s examples -t examples -v
+```
+
+
 ### Style guide
 
 For documentation strings, `transformers` follows the [google

Makefile

-.PHONY: style
+.PHONY: quality style test test-examples
+
+# Check that source code meets quality standards
+
+quality:
+	black --check --line-length 119 examples templates tests src utils
+	isort --check-only --recursive examples templates tests src utils
+	flake8 examples templates tests src utils
+
+# Format source code automatically
 
 style:
 	black --line-length 119 examples templates tests src utils
 	isort --recursive examples templates tests src utils
+
+# Run tests for the library
+
+test:
+	python -m pytest -n auto --dist=loadfile -s -v ./tests/
+
+# Run tests for examples
+
+test-examples:
+	python -m pytest -n auto --dist=loadfile -s -v ./examples/

README.md

@@ -66,6 +66,12 @@ Choose the right framework for every part of a model's lifetime
 
 This repo is tested on Python 3.5+, PyTorch 1.0.0+ and TensorFlow 2.0.0-rc1
 
+You should install 🤗 Transformers in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
+
+Create a virtual environment with the version of Python you're going to use and activate it.
+
+Now, if you want to use 🤗 Transformers, you can install it with pip. If you'd like to play with the examples, you must install it from source.
+
 ### With pip
 
 First you need to install one of, or both, TensorFlow 2.0 and PyTorch.
@@ -85,43 +91,48 @@ Please refer to [TensorFlow installation page](https://www.tensorflow.org/instal
 When TensorFlow 2.0 and/or PyTorch has been installed, you can install from source by cloning the repository and running:
 
 ```bash
-pip install [--editable] .
+git clone https://github.com/huggingface/transformers
+cd transformers
+pip install .
+```
+
+When you update the repository, you should upgrade the transformers installation and its dependencies as follows:
+
+```bash
+git pull
+pip install --upgrade .
 ```
 
 ### Run the examples
 
 Examples are included in the repository but are not shipped with the library.
-Therefore, in order to run the latest versions of the examples you also need to install from source. To do so, create a new virtual environment and follow these steps:
 
-```bash
-git clone https://github.com/huggingface/transformers
-cd transformers
-pip install [--editable] .
-```
+Therefore, in order to run the latest versions of the examples, you need to install from source, as described above.
 
-### Tests
+Look at the [README](https://github.com/huggingface/transformers/blob/master/examples/README.md) for how to run examples.
 
-A series of tests are included for the library and the example scripts. Library tests can be found in the [tests folder](https://github.com/huggingface/transformers/tree/master/tests) and examples tests in the [examples folder](https://github.com/huggingface/transformers/tree/master/examples).
+### Tests
 
-These tests can be run using `unittest` or `pytest` (install pytest if needed with `pip install pytest`).
+A series of tests are included for the library and for some example scripts. Library tests can be found in the [tests folder](https://github.com/huggingface/transformers/tree/master/tests) and examples tests in the [examples folder](https://github.com/huggingface/transformers/tree/master/examples).
 
 Depending on which framework is installed (TensorFlow 2.0 and/or PyTorch), the irrelevant tests will be skipped. Ensure that both frameworks are installed if you want to execute all tests.
 
-You can run the tests from the root of the cloned repository with the commands:
+Here's the easiest way to run tests for the library:
 
 ```bash
-python -m unittest discover -s tests -t . -v
-python -m unittest discover -s examples -t examples -v
+pip install -e .[testing]
+make test
 ```
 
-or
+and for the examples:
 
 ```bash
-python -m pytest -sv ./tests/
-python -m pytest -sv ./examples/
+pip install -e .[testing]
+pip install -r examples/requirements.txt
+make test-examples
 ```
 
-By default, slow tests are skipped. Set the `RUN_SLOW` environment variable to `yes` to run them.
+For details, refer to the [contributing guide](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#tests).
 
 ### Do you want to run a Transformer model on a mobile device?
 

docs/README.md

 # Generating the documentation
 
 To generate the documentation, you first have to build it. Several packages are necessary to build the doc,
-you can install them using:
+you can install them with the following command, at the root of the code repository:
 
 ```bash
-pip install -r requirements.txt
+pip install -e .[docs]
 ```
- 
+
 ## Packages installed
 
-Here's an overview of all the packages installed. If you ran the previous command installing all packages from 
+Here's an overview of all the packages installed. If you ran the previous command installing all packages from
 `requirements.txt`, you do not need to run the following commands.
 
-Building it requires the package `sphinx` that you can 
+Building it requires the package `sphinx` that you can
 install using:
 
 ```bash
 pip install -U sphinx
 ```
 
-You would also need the custom installed [theme](https://github.com/readthedocs/sphinx_rtd_theme) by 
+You would also need the custom installed [theme](https://github.com/readthedocs/sphinx_rtd_theme) by
 [Read The Docs](https://readthedocs.org/). You can install it using the following command:
 
 ```bash
@@ -34,7 +34,7 @@ pip install recommonmark
 
 ## Building the documentation
 
-Make sure that there is a symlink from the `example` file (in /examples) inside the source folder. Run the following 
+Make sure that there is a symlink from the `example` file (in /examples) inside the source folder. Run the following
 command to generate it:
 
 ```bash

docs/requirements.txt

-alabaster==0.7.12
-Babel==2.7.0
-certifi==2019.6.16
-chardet==3.0.4
-commonmark==0.9.0
-docutils==0.14
-future==0.17.1
-idna==2.8
-imagesize==1.1.0
-Jinja2==2.10.1
-MarkupSafe==1.1.1
-packaging==19.0
-Pygments==2.4.2
-pyparsing==2.4.0
-pytz==2019.1
-recommonmark==0.5.0
-requests==2.22.0
-six==1.12.0
-snowballstemmer==1.9.0
-Sphinx==2.1.2
-sphinx-rtd-theme==0.4.3
-sphinxcontrib-applehelp==1.0.1
-sphinxcontrib-devhelp==1.0.1
-sphinxcontrib-htmlhelp==1.0.2
-sphinxcontrib-jsmath==1.0.1
-sphinxcontrib-qthelp==1.0.2
-sphinxcontrib-serializinghtml==1.1.3
-urllib3==1.25.3
-sphinx-markdown-tables==0.0.9
-numpy==1.17.2
-tensorflow==2.0.0rc2
-torch==1.2.0
\ No newline at end of file

docs/source/installation.md

@@ -17,30 +17,14 @@ To install from source, clone the repository and install with:
 ``` bash
 git clone https://github.com/huggingface/transformers.git
 cd transformers
-pip install [--editable] .
+pip install .
 ```
 
 ## Tests
 
 An extensive test suite is included to test the library behavior and several examples. Library tests can be found in the [tests folder](https://github.com/huggingface/transformers/tree/master/tests) and examples tests in the [examples folder](https://github.com/huggingface/transformers/tree/master/examples).
 
-Tests can be run using `unittest` or `pytest` (install pytest if needed with `pip install pytest`).
-
-Run all the tests from the root of the cloned repository with the commands:
-
-```bash
-python -m unittest discover -s tests -t . -v
-python -m unittest discover -s examples -t examples -v
-```
-
-or
-
-``` bash
-python -m pytest -sv ./tests/
-python -m pytest -sv ./examples/
-```
-
-By default, slow tests are skipped. Set the `RUN_SLOW` environment variable to `yes` to run them.
+Refer to the [contributing guide](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#tests) for details about running tests.
 
 ## OpenAI GPT original tokenization workflow
 

examples/README.md

@@ -10,7 +10,7 @@ Execute the following steps in a new virtual environment:
 ```bash
 git clone https://github.com/huggingface/transformers
 cd transformers
-pip install [--editable] .
+pip install .
 pip install -r ./examples/requirements.txt
 ```
 

examples/distillation/requirements.txt

+transformers
+
 gitpython==3.0.2
 tensorboard>=1.14.0
 tensorboardX==1.8
 psutil==5.6.3
 scipy==1.3.1
-transformers

examples/pplm/README.md

@@ -15,7 +15,7 @@ Please check out the repo under uber-research for more information: https://gith
 
 ```bash
 git clone https://github.com/huggingface/transformers && cd transformers
-pip install [--editable] .
+pip install .
 pip install nltk torchtext # additional requirements.
 cd examples/pplm
 ```

examples/run_ner.py

@@ -25,7 +25,6 @@ import random
 import numpy as np
 import torch
 from seqeval.metrics import f1_score, precision_score, recall_score
-from tensorboardX import SummaryWriter
 from torch.nn import CrossEntropyLoss
 from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
 from torch.utils.data.distributed import DistributedSampler
@@ -54,6 +53,12 @@ from transformers import (
 from utils_ner import convert_examples_to_features, get_labels, read_examples_from_file
 
 
+try:
+    from torch.utils.tensorboard import SummaryWriter
+except ImportError:
+    from tensorboardX import SummaryWriter
+
+
 logger = logging.getLogger(__name__)
 
 ALL_MODELS = sum(

examples/summarization/README.md

@@ -10,7 +10,7 @@ The model is loaded with the pre-trained weights for the abstractive summarizati
 
 ```
 git clone https://github.com/huggingface/transformers && cd transformers
-pip install [--editable] .
+pip install .
 pip install nltk py-rouge
 cd examples/summarization
 ```

examples/summarization/requirements.txt

-# progress bars in model download and training scripts
-tqdm
-# Accessing files from S3 directly.
-boto3
-# Used for downloading models over HTTP
-requests
+transformers
+
 # For ROUGE
 nltk
 py-rouge

requirements-dev.txt

-absl-py==0.8.0
-astor==0.8.0
-atomicwrites==1.3.0
-attrs==19.2.0
-boto3==1.9.243
-botocore==1.12.243
-certifi==2019.9.11
-chardet==3.0.4
-Click==7.0
-docutils==0.15.2
-gast==0.2.2
-google-pasta==0.1.7
-grpcio==1.24.1
-h5py==2.10.0
-idna==2.8
-importlib-metadata==0.23
-jmespath==0.9.4
-joblib==0.14.0
-Keras-Applications==1.0.8
-Keras-Preprocessing==1.1.0
-Markdown==3.1.1
-more-itertools==7.2.0
-numpy==1.17.2
-opt-einsum==3.1.0
-packaging==19.2
-pluggy==0.13.0
-protobuf==3.10.0
-py==1.8.0
-pyparsing==2.4.2
-pytest==5.2.1
-python-dateutil==2.8.0
-regex==2019.8.19
-requests==2.22.0
-s3transfer==0.2.1
-sacremoses==0.0.35
-sentencepiece==0.1.83
-six==1.12.0
-tensorboard==2.0.0
-tensorflow==2.0.0
-tensorflow-estimator==2.0.0
-termcolor==1.1.0
-torch==1.2.0
-tqdm==4.36.1
-urllib3==1.25.6
-wcwidth==0.1.7
-Werkzeug==0.16.0
-wrapt==1.11.2
-zipp==0.6.0

requirements.txt

-# progress bars in model download and training scripts
-tqdm
-# Accessing files from S3 directly.
-boto3
-# Used for downloading models over HTTP
-requests
-# For OpenAI GPT
-regex != 2019.12.17
-# For XLNet
-sentencepiece
-# For XLM
-sacremoses
\ No newline at end of file

setup.cfg

@@ -7,6 +7,7 @@ known_third_party =
     fairseq
     fastprogress
     git
+    MeCab
     nltk
     packaging
     PIL

setup.py

@@ -34,15 +34,42 @@ To create the package for pypi.
 
 """
 
+import shutil
+from pathlib import Path
+
 from setuptools import find_packages, setup
 
 
-extras = {
-    "serving": ["pydantic", "uvicorn", "fastapi"],
-    "serving-tf": ["pydantic", "uvicorn", "fastapi", "tensorflow"],
-    "serving-torch": ["pydantic", "uvicorn", "fastapi", "torch"],
-}
-extras["all"] = [package for package in extras.values()]
+# Remove stale transformers.egg-info directory to avoid https://github.com/pypa/pip/issues/5466
+stale_egg_info = Path(__file__).parent / "transformers.egg-info"
+if stale_egg_info.exists():
+    print(
+        (
+            "Warning: {} exists.\n\n"
+            "If you recently updated transformers to 3.0 or later, this is expected,\n"
+            "but it may prevent transformers from installing in editable mode.\n\n"
+            "This directory is automatically generated by Python's packaging tools.\n"
+            "I will remove it now.\n\n"
+            "See https://github.com/pypa/pip/issues/5466 for details.\n"
+        ).format(stale_egg_info)
+    )
+    shutil.rmtree(stale_egg_info)
+
+
+extras = {}
+
+extras["mecab"] = ["mecab-python3"]
+extras["sklearn"] = ["scikit-learn"]
+extras["tf"] = ["tensorflow"]
+extras["torch"] = ["torch"]
+
+extras["serving"] = ["pydantic", "uvicorn", "fastapi"]
+extras["all"] = extras["serving"] + ["tensorflow", "torch"]
+
+extras["testing"] = ["pytest", "pytest-xdist"]
+extras["quality"] = ["black", "isort", "flake8"]
+extras["docs"] = ["recommonmark", "sphinx", "sphinx-markdown-tables", "sphinx-rtd-theme"]
+extras["dev"] = extras["testing"] + extras["quality"] + ["mecab-python3", "scikit-learn", "tensorflow", "torch"]
 
 setup(
     name="transformers",
@@ -55,25 +82,39 @@ setup(
     keywords="NLP deep learning transformer pytorch tensorflow BERT GPT GPT-2 google openai CMU",
     license="Apache",
     url="https://github.com/huggingface/transformers",
-    package_dir = {'': 'src'},
+    package_dir={"": "src"},
     packages=find_packages("src"),
     install_requires=[
         "numpy",
+        # accessing files from S3 directly
         "boto3",
+        # filesystem locks e.g. to prevent parallel downloads
         "filelock",
+        # for downloading models over HTTPS
         "requests",
+        # progress bars in model download and training scripts
         "tqdm",
+        # for OpenAI GPT
         "regex != 2019.12.17",
+        # for XLNet
         "sentencepiece",
+        # for XLM
         "sacremoses",
     ],
     extras_require=extras,
     scripts=["transformers-cli"],
-    # python_requires='>=3.5.0',
+    python_requires=">=3.5.0",
     classifiers=[
+        "Development Status :: 5 - Production/Stable",
+        "Intended Audience :: Developers",
+        "Intended Audience :: Education",
         "Intended Audience :: Science/Research",
         "License :: OSI Approved :: Apache Software License",
+        "Operating System :: OS Independent",
         "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.5",
+        "Programming Language :: Python :: 3.6",
+        "Programming Language :: Python :: 3.7",
         "Topic :: Scientific/Engineering :: Artificial Intelligence",
     ],
 )