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https://github.com/vale981/ray
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31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
# Counters for sampling and training steps (env- and agent steps).
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NUM_ENV_STEPS_SAMPLED = "num_env_steps_sampled"
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NUM_AGENT_STEPS_SAMPLED = "num_agent_steps_sampled"
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NUM_ENV_STEPS_SAMPLED_THIS_ITER = "num_env_steps_sampled_this_iter"
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NUM_AGENT_STEPS_SAMPLED_THIS_ITER = "num_agent_steps_sampled_this_iter"
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NUM_ENV_STEPS_TRAINED = "num_env_steps_trained"
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NUM_AGENT_STEPS_TRAINED = "num_agent_steps_trained"
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NUM_ENV_STEPS_TRAINED_THIS_ITER = "num_env_steps_trained_this_iter"
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NUM_AGENT_STEPS_TRAINED_THIS_ITER = "num_agent_steps_trained_this_iter"
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# Counters for keeping track of worker weight updates (synchronization
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# between local worker and remote workers).
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NUM_SYNCH_WORKER_WEIGHTS = "num_weight_broadcasts"
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NUM_TRAINING_STEP_CALLS_SINCE_LAST_SYNCH_WORKER_WEIGHTS = (
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"num_training_step_calls_since_last_synch_worker_weights"
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)
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# Counters to track target network updates.
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LAST_TARGET_UPDATE_TS = "last_target_update_ts"
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NUM_TARGET_UPDATES = "num_target_updates"
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# Performance timers (keys for Algorithm._timers).
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TRAINING_ITERATION_TIMER = "training_iteration"
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APPLY_GRADS_TIMER = "apply_grad"
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COMPUTE_GRADS_TIMER = "compute_grads"
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SYNCH_WORKER_WEIGHTS_TIMER = "synch_weights"
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GRAD_WAIT_TIMER = "grad_wait"
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SAMPLE_TIMER = "sample"
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LEARN_ON_BATCH_TIMER = "learn"
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LOAD_BATCH_TIMER = "load"
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TARGET_NET_UPDATE_TIMER = "target_net_update"
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