mirror of
https://github.com/vale981/ray
synced 2025-03-12 06:06:39 -04:00
fd0f967d2e
This reverts commit e4ceae19ef.
Reverts #25346
linux://python/ray/tests:test_client_library_integration never fail before this PR.
In the CI of the reverted PR, it also fails (https://buildkite.com/ray-project/ray-builders-pr/builds/34079#01812442-c541-4145-af22-2a012655c128). So high likely it's because of this PR.
And test output failure seems related as well (https://buildkite.com/ray-project/ray-builders-branch/builds/7923#018125c2-4812-4ead-a42f-7fddb344105b)
58 lines
2 KiB
Python
58 lines
2 KiB
Python
import unittest
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import ray
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import ray.rllib.algorithms.dqn as dqn
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import ray.rllib.agents.ppo as ppo
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from ray.rllib.examples.env.memory_leaking_env import MemoryLeakingEnv
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from ray.rllib.examples.policy.memory_leaking_policy import MemoryLeakingPolicy
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from ray.rllib.policy.policy import PolicySpec
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from ray.rllib.utils.debug.memory import check_memory_leaks
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class TestMemoryLeaks(unittest.TestCase):
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"""Generically tests our memory leak diagnostics tools."""
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@classmethod
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def setUpClass(cls):
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ray.init()
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@classmethod
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def tearDownClass(cls):
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ray.shutdown()
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def test_leaky_env(self):
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"""Tests, whether our diagnostics tools can detect leaks in an env."""
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config = ppo.DEFAULT_CONFIG.copy()
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# Make sure we have an env to test on the local worker.
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# Otherwise, `check_memory_leaks` will complain.
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config["create_env_on_driver"] = True
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config["env"] = MemoryLeakingEnv
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config["env_config"] = {
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"static_samples": True,
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}
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trainer = ppo.PPOTrainer(config=config)
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results = check_memory_leaks(trainer, to_check={"env"}, repeats=150)
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assert results["env"]
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trainer.stop()
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def test_leaky_policy(self):
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"""Tests, whether our diagnostics tools can detect leaks in a policy."""
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config = dqn.DEFAULT_CONFIG.copy()
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# Make sure we have an env to test on the local worker.
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# Otherwise, `check_memory_leaks` will complain.
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config["create_env_on_driver"] = True
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config["env"] = "CartPole-v0"
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config["multiagent"]["policies"] = {
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"default_policy": PolicySpec(policy_class=MemoryLeakingPolicy),
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}
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trainer = dqn.DQNTrainer(config=config)
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results = check_memory_leaks(trainer, to_check={"policy"}, repeats=300)
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assert results["policy"]
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trainer.stop()
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if __name__ == "__main__":
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import pytest
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import sys
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sys.exit(pytest.main(["-v", __file__]))
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