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LoadCartpole.py
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LoadCartpole.py
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from DuelingNetwork.model import Net
import numpy as np
import matplotlib.pyplot as plt
import gym
import random
import torch
from torch import nn
from torch import optim
from frameSave import save_frames_as_gif
from collections import namedtuple
import warnings
import time
import torch.nn.functional as F
model = torch.load("pth/cartpole.pth")
model.eval()
ENV = 'CartPole-v0'
env=gym.make(ENV)
observation = env.reset()
state=observation
state=torch.from_numpy(state).type(torch.FloatTensor)
state=torch.unsqueeze(state,0)
frames = []
for i in range(200):
with torch.no_grad():
model.eval()
action=model(state).max(1)[1].view(1,1)
observation_next, _, done, _ = env.step(
action.item())
if done:
break
else:
state_next = observation_next # 관측 결과를 그대로 상태로 사용
state_next = torch.from_numpy(state_next).type(
torch.FloatTensor) # numpy 변수를 파이토치 텐서로 변환
state_next = torch.unsqueeze(state_next, 0)
state = state_next
# env.render()
frames.append(env.render(mode="rgb_array"))
time.sleep(0.01)
# print(i)
env.close()
save_frames_as_gif(frames,filename='CartPole.gif')