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import numpy as np
from collections import deque
class TemporaryBuffer:
def __init__(self, delayed_steps):
self.d = delayed_steps
self.states = deque(maxlen=delayed_steps + 2)
self.actions = deque(maxlen=2 * delayed_steps + 1)
def clear(self):
self.states.clear()
self.actions.clear()
def get_augmented_state(self, last_observed_state, first_action_idx):
aug_state = np.concatenate([last_observed_state, self.actions[first_action_idx]])
for i in range(first_action_idx + 1, first_action_idx + self.d):
aug_state = np.concatenate([aug_state, self.actions[i]])
return aug_state
def get_tuple(self):
assert len(self.states) == self.d + 2 and len(self.actions) == 2 * self.d + 1
aug_s = self.get_augmented_state(self.states[0], 0)
s = self.states[-2]
a = self.actions[self.d]
next_aug_s = self.get_augmented_state(self.states[1], 1)
next_s = self.states[-1]
self.states.popleft()
self.actions.popleft()
return aug_s, s, a, next_aug_s, next_s
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