mirror of
https://github.com/saymrwulf/stable-baselines3.git
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daaebd0a52
* Drop python 3.8 support, add python 3.12 support * Upgrade to python 3.9 syntax * Fixes for Numpy v2 * Fix doc warning
65 lines
2.6 KiB
Python
65 lines
2.6 KiB
Python
"""
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Helpers for dealing with vectorized environments.
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"""
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from typing import Any
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import numpy as np
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from gymnasium import spaces
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from stable_baselines3.common.preprocessing import check_for_nested_spaces
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from stable_baselines3.common.vec_env.base_vec_env import VecEnvObs
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def dict_to_obs(obs_space: spaces.Space, obs_dict: dict[Any, np.ndarray]) -> VecEnvObs:
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"""
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Convert an internal representation raw_obs into the appropriate type
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specified by space.
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:param obs_space: an observation space.
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:param obs_dict: a dict of numpy arrays.
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:return: returns an observation of the same type as space.
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If space is Dict, function is identity; if space is Tuple, converts dict to Tuple;
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otherwise, space is unstructured and returns the value raw_obs[None].
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"""
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if isinstance(obs_space, spaces.Dict):
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return obs_dict
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elif isinstance(obs_space, spaces.Tuple):
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assert len(obs_dict) == len(obs_space.spaces), "size of observation does not match size of observation space"
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return tuple(obs_dict[i] for i in range(len(obs_space.spaces)))
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else:
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assert set(obs_dict.keys()) == {None}, "multiple observation keys for unstructured observation space"
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return obs_dict[None]
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def obs_space_info(obs_space: spaces.Space) -> tuple[list[str], dict[Any, tuple[int, ...]], dict[Any, np.dtype]]:
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"""
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Get dict-structured information about a gym.Space.
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Dict spaces are represented directly by their dict of subspaces.
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Tuple spaces are converted into a dict with keys indexing into the tuple.
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Unstructured spaces are represented by {None: obs_space}.
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:param obs_space: an observation space
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:return: A tuple (keys, shapes, dtypes):
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keys: a list of dict keys.
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shapes: a dict mapping keys to shapes.
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dtypes: a dict mapping keys to dtypes.
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"""
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check_for_nested_spaces(obs_space)
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if isinstance(obs_space, spaces.Dict):
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assert isinstance(obs_space.spaces, dict), "Dict space must have ordered subspaces"
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subspaces = obs_space.spaces
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elif isinstance(obs_space, spaces.Tuple):
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subspaces = {i: space for i, space in enumerate(obs_space.spaces)} # type: ignore[assignment,misc]
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else:
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assert not hasattr(obs_space, "spaces"), f"Unsupported structured space '{type(obs_space)}'"
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subspaces = {None: obs_space} # type: ignore[assignment,dict-item]
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keys = []
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shapes = {}
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dtypes = {}
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for key, box in subspaces.items():
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keys.append(key)
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shapes[key] = box.shape
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dtypes[key] = box.dtype
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return keys, shapes, dtypes # type: ignore[return-value]
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