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from collections.abc import Sequence |
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from dataclasses import dataclass |
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from typing import TYPE_CHECKING, Optional |
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import numpy as np |
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from tianshou.utils.print import DataclassPPrintMixin |
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if TYPE_CHECKING: |
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from tianshou.data import CollectStats, CollectStatsBase |
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from tianshou.policy.base import TrainingStats |
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@dataclass(kw_only=True) |
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class SequenceSummaryStats(DataclassPPrintMixin): |
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"""A data structure for storing the statistics of a sequence.""" |
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mean: float |
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std: float |
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max: float |
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min: float |
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@classmethod |
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def from_sequence(cls, sequence: Sequence[float | int] | np.ndarray) -> "SequenceSummaryStats": |
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return cls( |
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mean=float(np.mean(sequence)), |
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std=float(np.std(sequence)), |
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max=float(np.max(sequence)), |
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min=float(np.min(sequence)), |
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) |
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@dataclass(kw_only=True) |
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class TimingStats(DataclassPPrintMixin): |
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"""A data structure for storing timing statistics.""" |
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total_time: float = 0.0 |
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"""The total time elapsed.""" |
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train_time: float = 0.0 |
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"""The total time elapsed for training (collecting samples plus model update).""" |
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train_time_collect: float = 0.0 |
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"""The total time elapsed for collecting training transitions.""" |
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train_time_update: float = 0.0 |
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"""The total time elapsed for updating models.""" |
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test_time: float = 0.0 |
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"""The total time elapsed for testing models.""" |
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update_speed: float = 0.0 |
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"""The speed of updating (env_step per second).""" |
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@dataclass(kw_only=True) |
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class InfoStats(DataclassPPrintMixin): |
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"""A data structure for storing information about the learning process.""" |
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gradient_step: int |
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"""The total gradient step.""" |
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best_reward: float |
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"""The best reward over the test results.""" |
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best_reward_std: float |
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"""Standard deviation of the best reward over the test results.""" |
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train_step: int |
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"""The total collected step of training collector.""" |
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train_episode: int |
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"""The total collected episode of training collector.""" |
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test_step: int |
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"""The total collected step of test collector.""" |
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test_episode: int |
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"""The total collected episode of test collector.""" |
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timing: TimingStats |
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"""The timing statistics.""" |
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@dataclass(kw_only=True) |
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class EpochStats(DataclassPPrintMixin): |
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"""A data structure for storing epoch statistics.""" |
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epoch: int |
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"""The current epoch.""" |
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train_collect_stat: "CollectStatsBase" |
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"""The statistics of the last call to the training collector.""" |
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test_collect_stat: Optional["CollectStats"] |
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"""The statistics of the last call to the test collector.""" |
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training_stat: Optional["TrainingStats"] |
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"""The statistics of the last model update step. |
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Can be None if no model update is performed, typically in the last training iteration.""" |
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info_stat: InfoStats |
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"""The information of the collector.""" |
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