stable-baselines3/tests/test_cnn.py
2020-04-21 20:41:58 +02:00

20 lines
859 B
Python

import pytest
from torchy_baselines import A2C, PPO, SAC, TD3
from torchy_baselines.common.identity_env import FakeImageEnv
@pytest.mark.parametrize('model_class', [A2C, PPO, SAC])
def test_cnn(model_class):
# Fake grayscale with frameskip
# Atari after preprocessing: 84x84x1, here we are using lower resolution
# to check that the network handle it automatically
env = FakeImageEnv(screen_height=40, screen_width=40, n_channels=1,
discrete = model_class not in {SAC, TD3})
if model_class in {A2C, PPO}:
kwargs = dict(n_steps=100)
else:
# Avoid memory error when using replay buffer
# Reduce the size of the features
kwargs = dict(buffer_size=500, policy_kwargs=dict(features_extractor_kwargs=dict(features_dim=40)))
_ = model_class('CnnPolicy', env, **kwargs).learn(500)