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[tune] Add Fractional GPU example/docs (#3169)

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* Add example for fractional GPU support

* Update tune_mnist_keras.py

* Update doc/source/tune-usage.rst
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Richard Liaw
2018-10-31 18:53:16 -07:00
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parent 1f29a960f4
commit 2086a57e61
2 changed files with 11 additions and 2 deletions
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doc/source/tune-usage.rst
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@@ -193,9 +193,12 @@ Using GPUs (Resource Allocation)
Tune will allocate the specified GPU and CPU ``trial_resources`` to each individual trial (defaulting to 1 CPU per trial). Under the hood, Tune runs each trial as a Ray actor, using Ray's resource handling to allocate resources and place actors. A trial will not be scheduled unless at least that amount of resources is available in the cluster, preventing the cluster from being overloaded.
Fractional values are also supported, (i.e., ``"gpu": 0.2``). You can find an example of this in the `Keras MNIST example <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/tune_mnist_keras.py>`__.
If GPU resources are not requested, the ``CUDA_VISIBLE_DEVICES`` environment variable will be set as empty, disallowing GPU access.
Otherwise, it will be set to the GPUs in the list (this is managed by Ray).
If your trainable function / class creates further Ray actors or tasks that also consume CPU / GPU resources, you will also want to set ``extra_cpu`` or ``extra_gpu`` to reserve extra resource slots for the actors you will create. For example, if a trainable class requires 1 GPU itself, but will launch 4 actors each using another GPU, then it should set ``"gpu": 1, "extra_gpu": 4``.
.. code-block:: python