[rllib] Improve performance for small rollouts #812

pcmoritz · 2017-08-04T23:16:54Z

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AmplabJenkins · 2017-08-04T23:31:56Z

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AmplabJenkins · 2017-08-05T02:21:34Z

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AmplabJenkins · 2017-08-05T23:16:03Z

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AmplabJenkins · 2017-08-05T23:51:39Z

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AmplabJenkins · 2017-08-06T00:01:45Z

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…into pg-multinode-fixes Conflicts: python/ray/rllib/policy_gradient/agent.py

AmplabJenkins · 2017-08-06T02:21:25Z

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AmplabJenkins · 2017-08-06T03:10:37Z

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robertnishihara · 2017-08-06T03:16:25Z

python/ray/rllib/policy_gradient/agent.py

+    def compute_steps(self, gamma, lam, horizon, min_steps_per_task=-1):
+        """Compute multiple rollouts and concatenate the results.
+
+        Parameters:


This should be Args:

robertnishihara · 2017-08-06T03:16:48Z

python/ray/rllib/policy_gradient/agent.py

+
+        Parameters:
+            num_steps: Lower bound on the number of states to be collected.
+        Returns:


add a newline before Returns:

AmplabJenkins · 2017-08-06T03:16:51Z

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robertnishihara · 2017-08-06T03:18:11Z

python/ray/rllib/policy_gradient/policy_gradient.py

+    "lambda": 1.0,
+    # Initial coefficient for KL divergence
    "kl_coeff": 0.2,
+    # Number of SGD iteration in each outer loop


robertnishihara · 2017-08-06T03:21:35Z

python/ray/rllib/policy_gradient/agent.py

+        """Compute multiple rollouts and concatenate the results.
+
+        Parameters:
+            num_steps: Lower bound on the number of states to be collected.


These args are not the actual names of the args

robertnishihara · 2017-08-06T03:24:48Z

python/ray/rllib/policy_gradient/agent.py

        add_advantage_values(trajectory, gamma, lam, self.reward_filter)
        return trajectory

+    def compute_steps(self, gamma, lam, horizon, min_steps_per_task=-1):


would it make sense to define this method in terms of compute_trajectory?

robertnishihara · 2017-08-06T03:30:05Z

python/ray/rllib/policy_gradient/rollout.py

    trajectories = []
    total_rewards = []
-    traj_len_means = []
+    traj_lengths = []


slight preference for trajectory_lengths

robertnishihara · 2017-08-06T03:30:12Z

python/ray/rllib/policy_gradient/agent.py

+        num_steps_so_far = 0
+        trajectories = []
+        total_rewards = []
+        traj_lengths = []


slight preference for trajectory_lengths

robertnishihara · 2017-08-06T03:30:36Z

python/ray/rllib/policy_gradient/agent.py

+            traj_lengths.append(np.logical_not(trajectory["dones"]).sum(axis=0).mean())
+            trajectory = flatten(trajectory)
+            not_done = np.logical_not(trajectory["dones"])
+            trajectory = {key: val[not_done]


add a comment saying that we're filtering out the environments that are finished

AmplabJenkins · 2017-08-06T04:01:56Z

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AmplabJenkins · 2017-08-06T04:01:56Z

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AmplabJenkins · 2017-08-06T04:16:57Z

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AmplabJenkins · 2017-08-06T04:25:08Z

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AmplabJenkins · 2017-08-06T04:36:05Z

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pcmoritz added 2 commits August 4, 2017 16:15

batch small rollouts together

1647612

implement minimum number of samples for each task

11450b0

add total time

71930dc

pcmoritz force-pushed the pg-multinode-fixes branch from 032fc5f to 71930dc Compare August 5, 2017 23:35

fix linting

99cc663

style

3510cd4

pcmoritz added 2 commits August 5, 2017 19:02

fix

a6f460f

Merge branch 'pg-multinode-fixes' of https://github.com/pcmoritz/ray-1 …

7b1dd49

…into pg-multinode-fixes Conflicts: python/ray/rllib/policy_gradient/agent.py

pcmoritz added 2 commits August 5, 2017 19:53

factor out parameters and document stuff

5d4fb7e

add rollout batchsize

093fc66

robertnishihara reviewed Aug 6, 2017

View reviewed changes

address comments

5e73a94

linting

3994256

pcmoritz force-pushed the pg-multinode-fixes branch from 1240642 to 3994256 Compare August 6, 2017 04:09

small fix

4b61c52

robertnishihara merged commit 0225581 into ray-project:master Aug 6, 2017

robertnishihara deleted the pg-multinode-fixes branch August 6, 2017 05:13

[rllib] Improve performance for small rollouts #812

[rllib] Improve performance for small rollouts #812

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