chore: import upstream snapshot with attribution
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# @OldAPIStack
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# Runs on a p2.8xlarge single head node machine.
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# Should reach ~400 reward in about 1h and after 15-20M ts.
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atari-impala:
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env: ale_py:ALE/Breakout-v5
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run: IMPALA
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config:
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# Works for both torch and tf.
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framework: torch
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# Make analogous to old v4 + NoFrameskip.
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env_config:
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frameskip: 1
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full_action_space: false
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repeat_action_probability: 0.0
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rollout_fragment_length: 50
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train_batch_size: 4000
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num_gpus: 4
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num_env_runners: 31
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num_gpus_per_env_runner: 0 # works also for partial GPUs (<1.0) per worker
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num_envs_per_env_runner: 5
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clip_rewards: True
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lr_schedule: [
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[0, 0.0005],
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[20000000, 0.000000000001],
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]
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