Larger batches
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@@ -46,11 +46,11 @@ class LLBuffer(deque):
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def train(
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expert_data,
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expert_batch_size=3072,
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expert_batch_size=4096,
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discriminator_updates_per_round=20,
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generator_steps=1024,
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generator_batch_size=1024,
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generator_total_steps=4096,
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generator_total_steps=8192,
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generator_updates_per_round=10,
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discount=1.0,
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epochs=200,
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@@ -138,7 +138,7 @@ def evaluate():
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# %%
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if __name__ == '__main__':
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with open("data/NormalizedIntersimpleExpertMu.001N100000_TLNRasterizedRouteRandomAgentLocationw70h70mppx1mu.001rskips50.pkl", "rb") as f:
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with open("data/NormalizedIntersimpleExpertMu.001N50000_TLNRasterizedRouteRandomAgentLocationw70h70mppx1mu.001rskips50.pkl", "rb") as f:
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trajectories = pickle.load(f)
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transitions = rollout.flatten_trajectories(trajectories)
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train(transitions)
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