From 2013b9f9baf1bc1745a45f3d92f6b82ad1905e6b Mon Sep 17 00:00:00 2001
From: Phil <s8phsaue@stud.uni-saarland.de>
Date: Sun, 22 Dec 2024 15:34:34 +0100
Subject: [PATCH] Small adjustments
---
src/buffer.py | 11 ++---------
1 file changed, 2 insertions(+), 9 deletions(-)
diff --git a/src/buffer.py b/src/buffer.py
index 19df975..2452601 100644
--- a/src/buffer.py
+++ b/src/buffer.py
@@ -2,7 +2,7 @@ import numpy as np
class ReplayBuffer():
def __init__(self, env, cap):
- self._cap = cap
+ self._cap = max(1,cap)
self._size = 0
self._ptr = 0
@@ -12,7 +12,6 @@ class ReplayBuffer():
self._costs = np.zeros((cap, ), dtype=np.float64)
self._next_states = np.zeros_like(self._states)
-
def _add(self, state, action, reward, cost, next_state, start, end):
self._states[start:end] = state
self._actions[start:end] = action
@@ -22,7 +21,6 @@ class ReplayBuffer():
self._ptr = end
self._size = min(self._size + (end - start), self._cap)
-
def add(self, state, action, reward, cost, next_state):
b = state.shape[0]
if self._ptr + b <= self._cap:
@@ -32,7 +30,6 @@ class ReplayBuffer():
self._add(state[:d], action[:d], reward[:d], cost[:d], next_state[:d], start=self._ptr, end=self._cap)
self._add(state[d:], action[d:], reward[d:], cost[d:], next_state[d:], start=0, end=b-d)
-
def sample(self, n):
idxs = np.random.randint(low=0, high=self._size, size=n)
return self._states[idxs], self._actions[idxs], self._rewards[idxs], \
@@ -40,8 +37,4 @@ class ReplayBuffer():
def clear(self):
self._size = 0
- self._ptr = 0
-
- @property
- def size(self):
- return self._size
\ No newline at end of file
+ self._ptr = 0
\ No newline at end of file
--
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