39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
from glob import glob
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import tensorboard_reducer as tbr
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from policy import policies
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strict_steps=False
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overwrite = True
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reduce_ops = ("mean", "min", "max")
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for policy_name in policies:
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print(f"Calculating {policy_name}")
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# Define glob pattern to find the directories
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input_event_dirs = sorted(glob(f"tnsrbrd/sb3/{policy_name}_[0-9]"))
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print(f"Found {input_event_dirs}")
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# Define output dir
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events_output_dir = f"tnsrbrd/results/{policy_name}"
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# Load TB events
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events_dict = tbr.load_tb_events(input_event_dirs, strict_steps=False, verbose=True)
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# Get number of steps and other params
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n_scalars = len(events_dict)
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n_steps, n_events = list(events_dict.values())[0].shape
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print(f"Loaded {n_events} TensorBoard runs with {n_scalars} scalars and {n_steps} steps each")
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print(", ".join(events_dict))
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# Reduce events
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reduced_events = tbr.reduce_events(events_dict, reduce_ops, verbose=True)
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for op in reduce_ops:
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print(f"Writing '{op}' reduction to '{events_output_dir}-{op}'")
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tbr.write_tb_events(reduced_events, events_output_dir, overwrite)
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print(f"Reduction of {policy_name} done.")
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