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[rllib/tune] Add test for fractional gpu support in xray mode; add rllib support for fractional gpu (#2768)

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* frac gpu

* doc

* Update rllib-training.rst

* yapf

* remove xray
This commit is contained in:
Eric Liang
2018-09-03 11:12:23 -07:00
committed by GitHub
parent 9d655721e5
commit df4788e501
10 changed files with 41 additions and 9 deletions
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doc/source/rllib-training.rst
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@@ -50,6 +50,11 @@ In an example below, we train A2C by specifying 8 workers through the config fla
python ray/python/ray/rllib/train.py --env=PongDeterministic-v4 \
--run=A2C --config '{"num_workers": 8, "monitor": true}'
Specifying Resources
~~~~~~~~~~~~~~~~~~~~
You can control the degree of parallelism used by setting the ``num_workers`` hyperparameter for most agents. Many agents also provide a ``num_gpus`` or ``gpu`` option. In addition, you can allocate a fraction of a GPU by setting ``gpu_fraction: f``. For example, with DQN you can pack five agents onto one GPU by setting ``gpu_fraction: 0.2``. Note that fractional GPU support requires enabling the experimental Xray backend by setting the environment variable ``RAY_USE_XRAY=1``.
Evaluating Trained Agents
~~~~~~~~~~~~~~~~~~~~~~~~~