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[rllib] Remove experimental eager support

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Eric Liang
2019-07-21 12:27:17 -07:00
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parent b0c0de49a2
commit f9043cc49a
8 changed files with 16 additions and 114 deletions
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doc/source/rllib-concepts.rst
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@@ -437,8 +437,6 @@ While RLlib runs all TF operations in graph mode, you can still leverage TensorF
You can find a runnable file for the above eager execution example `here <https://github.com/ray-project/ray/blob/master/python/ray/rllib/examples/eager_execution.py>`__.
There is also experimental support for running the entire loss function in eager mode. This can be enabled with ``use_eager: True``, e.g., ``rllib train --env=CartPole-v0 --run=PPO --config='{"use_eager": true}'``. However this currently only works for PG, A2C, and PPO.
Building Policies in PyTorch
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