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68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
from __future__ import annotations
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from typing import Optional, Sequence, Union
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import numpy as np
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from .space import Space
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class MultiBinary(Space[np.ndarray]):
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"""
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An n-shape binary space.
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The argument to MultiBinary defines n, which could be a number or a ``list`` of numbers.
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Example Usage::
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>>> self.observation_space = spaces.MultiBinary(5)
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>>> self.observation_space.sample()
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array([0, 1, 0, 1, 0], dtype=int8)
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>>> self.observation_space = spaces.MultiBinary([3, 2])
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>>> self.observation_space.sample()
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array([[0, 0],
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[0, 1],
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[1, 1]], dtype=int8)
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"""
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def __init__(
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self, n: Union[np.ndarray, Sequence[int], int], seed: Optional[int] = None
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):
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if isinstance(n, (Sequence, np.ndarray)):
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self.n = input_n = tuple(int(i) for i in n)
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assert (np.asarray(input_n) > 0).all() # n (counts) have to be positive
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else:
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self.n = n = int(n)
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input_n = (n,)
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assert (np.asarray(input_n) > 0).all() # n (counts) have to be positive
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super().__init__(input_n, np.int8, seed)
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@property
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def shape(self) -> tuple[int, ...]:
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"""Has stricter type than gym.Space - never None."""
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return self._shape # type: ignore
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def sample(self) -> np.ndarray:
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return self.np_random.integers(low=0, high=2, size=self.n, dtype=self.dtype)
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def contains(self, x) -> bool:
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if isinstance(x, Sequence):
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x = np.array(x) # Promote list to array for contains check
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if self.shape != x.shape:
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return False
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return ((x == 0) | (x == 1)).all()
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def to_jsonable(self, sample_n) -> list:
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return np.array(sample_n).tolist()
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def from_jsonable(self, sample_n) -> list:
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return [np.asarray(sample) for sample in sample_n]
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def __repr__(self) -> str:
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return f"MultiBinary({self.n})"
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def __eq__(self, other) -> bool:
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return isinstance(other, MultiBinary) and self.n == other.n
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