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@@ -133,6 +133,8 @@ If TensorBoard is installed, automatically visualize all trial results:
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RLlib Quick Start
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-----------------
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.. image:: https://github.com/ray-project/ray/raw/master/doc/source/rllib-stack.svg
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`RLlib`_ is an open-source library for reinforcement learning built on top of Ray that offers both high scalability and a unified API for a variety of applications.
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.. code-block:: bash
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@@ -52,10 +52,10 @@ Policies can be implemented using `any framework <https://github.com/ray-project
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return -tf.reduce_mean(
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action_dist.logp(train_batch["actions"]) * train_batch["rewards"])
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# <class 'ray.rllib.policy.tf_policy_template.MyTFPolicy'>
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MyTFPolicy = build_tf_policy(
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name="MyTFPolicy",
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loss_fn=policy_gradient_loss)
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# <class 'ray.rllib.policy.tf_policy_template.MyTFPolicy'>
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MyTFPolicy = build_tf_policy(
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name="MyTFPolicy",
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loss_fn=policy_gradient_loss)
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Sample Batches
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~~~~~~~~~~~~~~
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