fc251ab0b8
* add makefile * bump version * add isort and yapf * update contributing.md * update PR template * spelling check
67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
from typing import Any
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import numpy as np
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from tianshou.data import (
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PrioritizedReplayBuffer,
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PrioritizedReplayBufferManager,
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ReplayBuffer,
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ReplayBufferManager,
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)
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class VectorReplayBuffer(ReplayBufferManager):
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"""VectorReplayBuffer contains n ReplayBuffer with the same size.
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It is used for storing transition from different environments yet keeping the order
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of time.
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:param int total_size: the total size of VectorReplayBuffer.
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:param int buffer_num: the number of ReplayBuffer it uses, which are under the same
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configuration.
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Other input arguments (stack_num/ignore_obs_next/save_only_last_obs/sample_avail)
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are the same as :class:`~tianshou.data.ReplayBuffer`.
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.. seealso::
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Please refer to :class:`~tianshou.data.ReplayBuffer` for other APIs' usage.
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"""
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def __init__(self, total_size: int, buffer_num: int, **kwargs: Any) -> None:
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assert buffer_num > 0
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size = int(np.ceil(total_size / buffer_num))
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buffer_list = [ReplayBuffer(size, **kwargs) for _ in range(buffer_num)]
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super().__init__(buffer_list)
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class PrioritizedVectorReplayBuffer(PrioritizedReplayBufferManager):
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"""PrioritizedVectorReplayBuffer contains n PrioritizedReplayBuffer with same size.
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It is used for storing transition from different environments yet keeping the order
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of time.
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:param int total_size: the total size of PrioritizedVectorReplayBuffer.
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:param int buffer_num: the number of PrioritizedReplayBuffer it uses, which are
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under the same configuration.
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Other input arguments (alpha/beta/stack_num/ignore_obs_next/save_only_last_obs/
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sample_avail) are the same as :class:`~tianshou.data.PrioritizedReplayBuffer`.
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.. seealso::
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Please refer to :class:`~tianshou.data.ReplayBuffer` for other APIs' usage.
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"""
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def __init__(self, total_size: int, buffer_num: int, **kwargs: Any) -> None:
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assert buffer_num > 0
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size = int(np.ceil(total_size / buffer_num))
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buffer_list = [
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PrioritizedReplayBuffer(size, **kwargs) for _ in range(buffer_num)
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]
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super().__init__(buffer_list)
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def set_beta(self, beta: float) -> None:
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for buffer in self.buffers:
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buffer.set_beta(beta)
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