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update pre-commit (#344)
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@@ -419,7 +419,6 @@ entropies = []
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# use tqdm to get a progress bar for training
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for sample_phase in tqdm(range(n_updates)):
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# we don't have to reset the envs, they just continue playing
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# until the episode is over and then reset automatically
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@@ -435,7 +434,6 @@ for sample_phase in tqdm(range(n_updates)):
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# play n steps in our parallel environments to collect data
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for step in range(n_steps_per_update):
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# select an action A_{t} using S_{t} as input for the agent
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actions, action_log_probs, state_value_preds, entropy = agent.select_action(
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states
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@@ -674,7 +672,6 @@ for episode in range(n_showcase_episodes):
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# play one episode
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done = False
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while not done:
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# select an action A_{t} using S_{t} as input for the agent
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with torch.no_grad():
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action, _, _, _ = agent.select_action(state[None, :])
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