add test atari

tests/test_examples/test_train_atari.py

@@ -0,0 +1,74 @@
+""""""
+
+import os
+import sys
+
+import numpy as np
+import pytest
+
+from openrl.configs.config import create_config_parser
+from openrl.envs.common import make
+from openrl.envs.wrappers.atari_wrappers import (
+    ClipRewardEnv,
+    FireResetEnv,
+    NoopResetEnv,
+    WarpFrame,
+)
+from openrl.envs.wrappers.image_wrappers import TransposeImage
+from openrl.envs.wrappers.monitor import Monitor
+from openrl.modules.common import PPONet as Net
+from openrl.runners.common import PPOAgent as Agent
+
+env_wrappers = [
+    Monitor,
+    NoopResetEnv,
+    FireResetEnv,
+    WarpFrame,
+    ClipRewardEnv,
+    TransposeImage,
+]
+
+
+@pytest.fixture(
+    scope="module",
+    params=[
+        "--episode_length 5 --use_recurrent_policy false --vec_info_class.id"
+        " EPS_RewardInfo --use_valuenorm true --use_adv_normalize true"
+        " --use_share_model True --entropy_coef 0.01"
+    ],
+)
+def config(request):
+    cfg_parser = create_config_parser()
+    cfg = cfg_parser.parse_args(request.param.split())
+    return cfg
+
+
+@pytest.mark.unittest
+def test_train_atari(config):
+    env_num = 2
+    env = make(
+        "ALE/Pong-v5",
+        env_num=env_num,
+        cfg=config,
+        asynchronous=True,
+        env_wrappers=env_wrappers,
+    )
+    net = Net(env, cfg=config)
+    agent = Agent(net)
+    agent.train(total_time_steps=30)
+    agent.save("./ppo_agent/")
+    agent.load("./ppo_agent/")
+    agent.set_env(env)
+    obs, info = env.reset(seed=0)
+    step = 0
+    while step < 5:
+        action, _ = agent.act(obs, deterministic=True)
+        obs, r, done, info = env.step(action)
+        if np.any(done):
+            break
+        step += 1
+    env.close()
+
+
+if __name__ == "__main__":
+    sys.exit(pytest.main(["-sv", os.path.basename(__file__)]))