You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
# ignore this
from simple_spread_test import make_env
from maa2c import MAA2C
import imageio
import numpy as np
import os
import torch
if __name__ == '__main__':
env = make_env(scenario_name="simple_spread")
ma_controller = MAA2C(env ,gif = True)
# Number of images to capture
n_images = 10000
images = []
# init a new episode
obs = env.reset()
# init the img var with the starting state of the env
img = env.render(mode='rgb_array')[0]
for i in range(n_images):
# At each step, append an image to list
images.append(img)
# Advance a step and render a new image
with torch.no_grad():
action = ma_controller.get_actions(obs)
obs, _, _ ,_ = env.step(action)
img = env.render(mode='rgb_array')[0]
imageio.mimwrite('./simple_spread.gif',
[np.array(img) for i, img in enumerate(images) if i%2 == 0],
fps=50)
Save a GIF file based on this argument in trainer.
To-do:
The text was updated successfully, but these errors were encountered: