mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
import gym
|
|
import numpy as np
|
|
|
|
from ray.rllib.utils.annotations import PublicAPI
|
|
|
|
|
|
@PublicAPI
|
|
class Repeated(gym.Space):
|
|
"""Represents a variable-length list of child spaces.
|
|
|
|
Example:
|
|
self.observation_space = spaces.Repeated(spaces.Box(4,), max_len=10)
|
|
--> from 0 to 10 boxes of shape (4,)
|
|
|
|
See also: documentation for rllib.models.RepeatedValues, which shows how
|
|
the lists are represented as batched input for ModelV2 classes.
|
|
"""
|
|
|
|
def __init__(self, child_space: gym.Space, max_len: int):
|
|
super().__init__()
|
|
self.child_space = child_space
|
|
self.max_len = max_len
|
|
|
|
def sample(self):
|
|
return [
|
|
self.child_space.sample()
|
|
for _ in range(self.np_random.randint(1, self.max_len + 1))
|
|
]
|
|
|
|
def contains(self, x):
|
|
return (
|
|
isinstance(x, (list, np.ndarray))
|
|
and len(x) <= self.max_len
|
|
and all(self.child_space.contains(c) for c in x)
|
|
)
|
|
|
|
def __repr__(self):
|
|
return "Repeated({}, {})".format(self.child_space, self.max_len)
|