From 5a959f125570491719c92868168cd372e4323549 Mon Sep 17 00:00:00 2001
From: Reinis Cimurs <33617541+reiniscimurs@users.noreply.github.com>
Date: Wed, 17 Aug 2022 21:25:18 +0200
Subject: [PATCH] Delete replay_buffer2.py

---
 TD3/replay_buffer2.py | 51 -------------------------------------------
 1 file changed, 51 deletions(-)
 delete mode 100644 TD3/replay_buffer2.py

diff --git a/TD3/replay_buffer2.py b/TD3/replay_buffer2.py
deleted file mode 100644
index 31745741..00000000
--- a/TD3/replay_buffer2.py
+++ /dev/null
@@ -1,51 +0,0 @@
-"""
-Data structure for implementing experience replay
-Author: Patrick Emami
-"""
-from collections import deque
-import random
-import numpy as np
-
-class ReplayBuffer(object):
-
-    def __init__(self, buffer_size, random_seed=123):
-        """
-        The right side of the deque contains the most recent experiences
-        """
-        self.buffer_size = buffer_size
-        self.count = 0
-        self.buffer = deque()
-        random.seed(random_seed)
-
-    def add(self, s, a, r, t, s2):
-        experience = (s, a, r, t, s2)
-        if self.count < self.buffer_size:
-            self.buffer.append(experience)
-            self.count += 1
-        else:
-            self.buffer.popleft()
-            self.buffer.append(experience)
-
-    def size(self):
-        return self.count
-
-    def sample_batch(self, batch_size):
-        batch = []
-
-        if self.count < batch_size:
-            batch = random.sample(self.buffer, self.count)
-        else:
-            batch = random.sample(self.buffer, batch_size)
-
-        s_batch = np.array([_[0] for _ in batch])
-        a_batch = np.array([_[1] for _ in batch])
-        r_batch = np.array([_[2] for _ in batch]).reshape(-1,1)
-        t_batch = np.array([_[3] for _ in batch]).reshape(-1,1)
-        s2_batch = np.array([_[4] for _ in batch])
-
-        return s_batch, a_batch, r_batch, t_batch, s2_batch
-
-
-    def clear(self):
-        self.buffer.clear()
-        self.count = 0
\ No newline at end of file