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JohnJim0816
2021-03-23 16:10:11 +08:00
parent d4690c2058
commit bf0f2990cf
198 changed files with 1668 additions and 1545 deletions
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41
codes/ddpg/agent.py
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@@ -5,7 +5,7 @@
@Email: johnjim0816@gmail.com
@Date: 2020-06-09 20:25:52
@LastEditor: John
LastEditTime: 2020-09-02 01:19:13
LastEditTime: 2021-03-17 20:43:25
@Discription:
@Environment: python 3.7.7
'''
@@ -14,18 +14,17 @@ import torch
import torch.nn as nn
import torch.optim as optim
from model import Actor, Critic
from memory import ReplayBuffer
from common.model import Actor, Critic
from common.memory import ReplayBuffer
class DDPG:
def __init__(self, n_states, n_actions, hidden_dim=30, device="cpu", critic_lr=1e-3,
actor_lr=1e-4, gamma=0.99, soft_tau=1e-2, memory_capacity=100000, batch_size=128):
self.device = device
self.critic = Critic(n_states, n_actions, hidden_dim).to(device)
self.actor = Actor(n_states, n_actions, hidden_dim).to(device)
self.target_critic = Critic(n_states, n_actions, hidden_dim).to(device)
self.target_actor = Actor(n_states, n_actions, hidden_dim).to(device)
def __init__(self, n_states, n_actions, cfg):
self.device = cfg.device
self.critic = Critic(n_states, n_actions, cfg.hidden_dim).to(cfg.device)
self.actor = Actor(n_states, n_actions, cfg.hidden_dim).to(cfg.device)
self.target_critic = Critic(n_states, n_actions, cfg.hidden_dim).to(cfg.device)
self.target_actor = Actor(n_states, n_actions, cfg.hidden_dim).to(cfg.device)
for target_param, param in zip(self.target_critic.parameters(), self.critic.parameters()):
target_param.data.copy_(param.data)
@@ -33,14 +32,14 @@ class DDPG:
target_param.data.copy_(param.data)
self.critic_optimizer = optim.Adam(
self.critic.parameters(), lr=critic_lr)
self.actor_optimizer = optim.Adam(self.actor.parameters(), lr=actor_lr)
self.memory = ReplayBuffer(memory_capacity)
self.batch_size = batch_size
self.soft_tau = soft_tau
self.gamma = gamma
self.critic.parameters(), lr=cfg.critic_lr)
self.actor_optimizer = optim.Adam(self.actor.parameters(), lr=cfg.actor_lr)
self.memory = ReplayBuffer(cfg.memory_capacity)
self.batch_size = cfg.batch_size
self.soft_tau = cfg.soft_tau
self.gamma = cfg.gamma
def select_action(self, state):
def choose_action(self, state):
state = torch.FloatTensor(state).unsqueeze(0).to(self.device)
action = self.actor(state)
# torch.detach()用于切断反向传播
@@ -87,8 +86,8 @@ class DDPG:
target_param.data * (1.0 - self.soft_tau) +
param.data * self.soft_tau
)
def save_model(self,path):
torch.save(self.target_actor.state_dict(), path)
def save(self,path):
torch.save(self.target_net.state_dict(), path+'DDPG_checkpoint.pth')
def load_model(self,path):
self.actor.load_state_dict(torch.load(path))
def load(self,path):
self.actor.load_state_dict(torch.load(path+'DDPG_checkpoint.pth'))