baselines演算法庫common/vec_env/util.py模組分析
阿新 • • 發佈:2022-03-22
util.py模組程式碼:
""" Helpers for dealing with vectorized environments. """ from collections import OrderedDict import gym import numpy as np def copy_obs_dict(obs): """ Deep-copy an observation dict. """ return {k: np.copy(v) for k, v in obs.items()} def dict_to_obs(obs_dict):""" Convert an observation dict into a raw array if the original observation space was not a Dict space. """ if set(obs_dict.keys()) == {None}: return obs_dict[None] return obs_dict def obs_space_info(obs_space): """ Get dict-structured information about a gym.Space. Returns: A tuple (keys, shapes, dtypes): keys: a list of dict keys. shapes: a dict mapping keys to shapes. dtypes: a dict mapping keys to dtypes.""" if isinstance(obs_space, gym.spaces.Dict): assert isinstance(obs_space.spaces, OrderedDict) subspaces = obs_space.spaces elif isinstance(obs_space, gym.spaces.Tuple): assert isinstance(obs_space.spaces, tuple) subspaces = {i: obs_space.spaces[i] for i in range(len(obs_space.spaces))}else: subspaces = {None: obs_space} keys = [] shapes = {} dtypes = {} for key, box in subspaces.items(): keys.append(key) shapes[key] = box.shape dtypes[key] = box.dtype return keys, shapes, dtypes def obs_to_dict(obs): """ Convert an observation into a dict. """ if isinstance(obs, dict): return obs return {None: obs}
函式:
def copy_obs_dict(obs):
def obs_to_dict(obs_dict):
假設傳入的observation都是dict型別的。
在函式
obs_to_dict
中,如果傳入的observation不是dict型別的則將其轉為dict型別,此時的key值設定為None。
函式
def dict_to_obs(obs_dict)
假設輸入的是key為None的dict型別的observation,將其dict型別轉為np.array型別的observation。
如果輸入的不是key為None的dict型別的observation則直接將其返回。
函式
def obs_space_info(obs_space):
輸入引數為observation的spaces變數。
if isinstance(obs_space, gym.spaces.Dict): assert isinstance(obs_space.spaces, OrderedDict) subspaces = obs_space.spaces elif isinstance(obs_space, gym.spaces.Tuple): assert isinstance(obs_space.spaces, tuple) subspaces = {i: obs_space.spaces[i] for i in range(len(obs_space.spaces))} else: subspaces = {None: obs_space}
首先將env.observation_sapce.spaces變數進行判斷,將其轉為dict型別。
對env.observation_space.spaces進行資訊提取,得到:
Returns:
A tuple (keys, shapes, dtypes):
keys: a list of dict keys.
shapes: a dict mapping keys to shapes.
dtypes: a dict mapping keys to dtypes.
最後返回資訊的形式為tuple型別。
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