Spaces:
Running
Running
File size: 1,270 Bytes
be5548b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
#!/usr/bin/env python3
import time
import argparse
import gym_minigrid
import gym
from gym_minigrid.wrappers import *
parser = argparse.ArgumentParser()
parser.add_argument(
"--env-name",
dest="env_name",
help="gym environment to load",
default='MiniGrid-LavaGapS7-v0'
)
parser.add_argument("--num_resets", default=200)
parser.add_argument("--num_frames", default=5000)
args = parser.parse_args()
env = gym.make(args.env_name)
# Benchmark env.reset
t0 = time.time()
for i in range(args.num_resets):
env.reset()
t1 = time.time()
dt = t1 - t0
reset_time = (1000 * dt) / args.num_resets
# Benchmark rendering
t0 = time.time()
for i in range(args.num_frames):
env.render('rgb_array')
t1 = time.time()
dt = t1 - t0
frames_per_sec = args.num_frames / dt
# Create an environment with an RGB agent observation
env = gym.make(args.env_name)
env = RGBImgPartialObsWrapper(env)
env = ImgObsWrapper(env)
# Benchmark rendering
t0 = time.time()
for i in range(args.num_frames):
obs, reward, done, info = env.step(0)
t1 = time.time()
dt = t1 - t0
agent_view_fps = args.num_frames / dt
print('Env reset time: {:.1f} ms'.format(reset_time))
print('Rendering FPS : {:.0f}'.format(frames_per_sec))
print('Agent view FPS: {:.0f}'.format(agent_view_fps))
|