2019-03-26 00:27:59 -07:00
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import numpy as np
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import pprint
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2019-05-20 16:46:05 -07:00
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from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch
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2019-03-26 00:27:59 -07:00
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_printer = pprint.PrettyPrinter(indent=2, width=60)
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def summarize(obj):
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"""Return a pretty-formatted string for an object.
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This has special handling for pretty-formatting of commonly used data types
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in RLlib, such as SampleBatch, numpy arrays, etc.
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"""
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return _printer.pformat(_summarize(obj))
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def _summarize(obj):
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if isinstance(obj, dict):
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return {k: _summarize(v) for k, v in obj.items()}
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elif hasattr(obj, "_asdict"):
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return {
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"type": obj.__class__.__name__,
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"data": _summarize(obj._asdict()),
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}
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elif isinstance(obj, list):
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return [_summarize(x) for x in obj]
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elif isinstance(obj, tuple):
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return tuple(_summarize(x) for x in obj)
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elif isinstance(obj, np.ndarray):
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2019-07-16 22:37:57 -07:00
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if obj.size == 0:
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return _StringValue("np.ndarray({}, dtype={})".format(
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obj.shape, obj.dtype))
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elif obj.dtype == np.object:
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2019-03-26 00:27:59 -07:00
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return _StringValue("np.ndarray({}, dtype={}, head={})".format(
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obj.shape, obj.dtype, _summarize(obj[0])))
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else:
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return _StringValue(
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"np.ndarray({}, dtype={}, min={}, max={}, mean={})".format(
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obj.shape, obj.dtype, round(float(np.min(obj)), 3),
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round(float(np.max(obj)), 3), round(
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float(np.mean(obj)), 3)))
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elif isinstance(obj, MultiAgentBatch):
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return {
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"type": "MultiAgentBatch",
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"policy_batches": _summarize(obj.policy_batches),
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"count": obj.count,
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}
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elif isinstance(obj, SampleBatch):
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return {
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"type": "SampleBatch",
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"data": {k: _summarize(v)
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for k, v in obj.items()},
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}
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else:
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return obj
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2020-01-02 17:42:13 -08:00
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class _StringValue:
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2019-03-26 00:27:59 -07:00
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def __init__(self, value):
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self.value = value
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def __repr__(self):
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return self.value
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