Increase discriminator batch size and update steps
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@@ -31,10 +31,10 @@ ALL_OPTIONS = [(v,t) for v in [0,2,4,6,8] for t in [5, 10, 20]] # option 0 is sa
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def train(
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def train(
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expert_data,
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expert_data,
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epochs=200,
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epochs=200,
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expert_batch_size=256,
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expert_batch_size=1024,
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generator_steps=1024,
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generator_steps=1024,
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discount=0.99,
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discount=0.99,
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n_disc_updates_per_round=2,
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n_disc_updates_per_round=10,
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n_gen_updates_per_round=10,
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n_gen_updates_per_round=10,
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):
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):
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env = NRasterizedRouteSpeedRandomAgentLocation(**env_settings)
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env = NRasterizedRouteSpeedRandomAgentLocation(**env_settings)
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