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remove unused steps parameter from GraphManager.train
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@@ -325,7 +325,7 @@ class GraphManager(object):
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[environment.handle_episode_ended() for environment in self.environments]
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[environment.handle_episode_ended() for environment in self.environments]
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def train(self, steps: TrainingSteps) -> None:
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def train(self) -> None:
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"""
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"""
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Perform several training iterations for all the levels in the hierarchy
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Perform several training iterations for all the levels in the hierarchy
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:param steps: number of training iterations to perform
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:param steps: number of training iterations to perform
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@@ -426,7 +426,7 @@ class GraphManager(object):
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# The actual steps being done on the environment are decided by the agents themselves.
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# The actual steps being done on the environment are decided by the agents themselves.
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# This is just an high-level controller.
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# This is just an high-level controller.
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self.act(EnvironmentSteps(1))
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self.act(EnvironmentSteps(1))
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self.train(TrainingSteps(1))
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self.train()
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self.occasionally_save_checkpoint()
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self.occasionally_save_checkpoint()
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self.phase = RunPhase.UNDEFINED
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self.phase = RunPhase.UNDEFINED
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@@ -42,7 +42,7 @@ def training_worker(graph_manager, checkpoint_dir, policy_type):
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steps += 1
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steps += 1
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graph_manager.phase = core_types.RunPhase.TRAIN
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graph_manager.phase = core_types.RunPhase.TRAIN
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graph_manager.train(core_types.TrainingSteps(1))
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graph_manager.train()
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graph_manager.phase = core_types.RunPhase.UNDEFINED
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graph_manager.phase = core_types.RunPhase.UNDEFINED
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if steps * graph_manager.agent_params.algorithm.num_consecutive_playing_steps.num_steps > graph_manager.steps_between_evaluation_periods.num_steps * eval_offset:
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if steps * graph_manager.agent_params.algorithm.num_consecutive_playing_steps.num_steps > graph_manager.steps_between_evaluation_periods.num_steps * eval_offset:
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