buffer.py

import numpy as np


class ReplayBuffer:
    def __init__(self, max_size, input_shape, n_actions):
        self.mem_size = max_size
        self.mem_ctr = 0
        self.state_memory = np.zeros((self.mem_size, *input_shape))
        self.action_memory = np.zeros((self.mem_size, n_actions))
        self.reward_memory = np.zeros(self.mem_size)
        self.next_state_memory = np.zeros((self.mem_size, *input_shape))
        self.terminal_memory = np.zeros(self.mem_size, dtype=bool)
    
    def store_transition(self, state, action, reward, next_state, done):
        index = self.mem_ctr % self.mem_size
        self.state_memory[index] = state
        self.action_memory[index] = action
        self.reward_memory[index] = reward
        self.next_state_memory[index] = next_state
        self.terminal_memory[index] = done
        self.mem_ctr += 1
        
    def sample_buffer(self, batch_size):
        max_mem = min(self.mem_ctr, self.mem_size)
        batch = np.random.choice(max_mem, batch_size)
        
        states = self.state_memory[batch]
        actions = self.action_memory[batch]
        rewards = self.reward_memory[batch]
        next_states = self.next_state_memory[batch]
        dones = self.terminal_memory[batch]
        
        return states, actions, rewards, next_states, dones