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Update contribution instructions.

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Also provide shortcuts in a Makefile.
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Aymeric Augustin
2019-12-22 21:31:12 +01:00
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commit 70373a5f7c
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@@ -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.
@@ -84,44 +90,49 @@ 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] .
```
### 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] .
```
When you update the repository, you should upgrade the transformers installation and its dependencies as follows:
```bash
git pull
pip install --upgrade [--editable] .
```
### 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 need to install from source, as described above.
Look at the [README](https://github.com/huggingface/transformers/blob/master/examples/README.md) for how to run examples.
### Tests
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).
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?