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from __future__ import annotations
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from enum import Enum
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from typing import Any, TypeAlias, TypedDict
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import numpy as np
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import torch
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class TransitionKey(str, Enum):
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"""Keys for accessing EnvTransition dictionary components."""
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OBSERVATION = "observation"
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ACTION = "action"
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REWARD = "reward"
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DONE = "done"
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TRUNCATED = "truncated"
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INFO = "info"
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COMPLEMENTARY_DATA = "complementary_data"
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PolicyAction: TypeAlias = torch.Tensor
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RobotAction: TypeAlias = dict[str, Any]
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EnvAction: TypeAlias = np.ndarray
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RobotObservation: TypeAlias = dict[str, Any]
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EnvTransition = TypedDict(
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"EnvTransition",
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{
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TransitionKey.OBSERVATION.value: dict[str, Any] | None,
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TransitionKey.ACTION.value: PolicyAction | RobotAction | EnvAction | None,
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TransitionKey.REWARD.value: float | torch.Tensor | None,
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TransitionKey.DONE.value: bool | torch.Tensor | None,
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TransitionKey.TRUNCATED.value: bool | torch.Tensor | None,
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TransitionKey.INFO.value: dict[str, Any] | None,
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TransitionKey.COMPLEMENTARY_DATA.value: dict[str, Any] | None,
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},
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)
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