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Update README.md to add a quick link banner, and to recommend pytest-xdist.

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# JAX: Autograd and XLA [![Test status](https://travis-ci.org/google/jax.svg?branch=master)](https://travis-ci.org/google/jax) # JAX: Autograd and XLA [![Test status](https://travis-ci.org/google/jax.svg?branch=master)](https://travis-ci.org/google/jax)
[**Reference docs**](https://jax.readthedocs.io/en/latest/)
| [**Install guide**](#installation)
| [**Quickstart**](#quickstart-colab-in-the-cloud)
JAX is [Autograd](https://github.com/hips/autograd) and JAX is [Autograd](https://github.com/hips/autograd) and
[XLA](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/xla/g3doc/overview.md), [XLA](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/xla/g3doc/overview.md),
brought together for high-performance machine learning research. brought together for high-performance machine learning research.
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## Running the tests ## Running the tests
To run all the JAX tests, from the repository root directory run To run all the JAX tests, we recommend using `pytest-xdist`, which can run tests in
parallel. First, install `pytest-xdist` by running `pip install pytest-xdist`.
Then, from the repository root directory run
```bash ```bash
nosetests tests pytest-xdist -n auto tests
``` ```
JAX generates test cases combinatorially, and you can control the number of JAX generates test cases combinatorially, and you can control the number of
cases that are generated and checked for each test (default 10): cases that are generated and checked for each test (default 10):
```bash ```bash
JAX_NUM_GENERATED_CASES=100 nosetests tests JAX_NUM_GENERATED_CASES=100 pytest-xdist -n auto tests
``` ```
You can run a more specific set of tests using You can run a more specific set of tests using
[`nose`](https://nose.readthedocs.io/en/latest/usage.html)'s built-in selection [`pytest`](https://docs.pytest.org/en/latest/usage.html#specifying-tests-selecting-tests)'s
mechanisms, or alternatively you can run a specific test file directly to see built-in selection mechanisms, or alternatively you can run a specific test
more detailed information about the cases being run: file directly to see more detailed information about the cases being run:
```bash ```bash
python tests/lax_numpy_test.py --num_generated_cases=5 python tests/lax_numpy_test.py --num_generated_cases=5