Replace '__main__' with "__main__". (#4055)

python/ray/rllib/optimizers/tests/test_segment_tree.py

@@ -99,7 +99,7 @@ def test_max_interval_tree():
     assert np.isclose(tree.min(3, 4), 3.0)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     test_tree_set()
     test_tree_set_overlap()
     test_prefixsum_idx()

python/ray/rllib/test/run_regression_tests.py

@@ -10,7 +10,7 @@ import sys
 import ray
 from ray.tune import run_experiments
 
-if __name__ == '__main__':
+if __name__ == "__main__":
 
     ray.init()
 

python/ray/rllib/test/test_evaluators.py

@@ -40,5 +40,5 @@ class DQNTest(unittest.TestCase):
         self.assertNotEqual(r3["evaluation"], r4["evaluation"])
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main(verbosity=2)

python/ray/rllib/test/test_external_env.py

@@ -195,6 +195,6 @@ class TestExternalEnv(unittest.TestCase):
         self.assertRaises(ValueError, lambda: ev.sample())
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     ray.init()
     unittest.main(verbosity=2)

python/ray/rllib/test/test_multi_agent_env.py

@@ -557,6 +557,6 @@ class TestMultiAgentEnv(unittest.TestCase):
         raise Exception("failed to improve reward")
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     ray.init()
     unittest.main(verbosity=2)

python/ray/rllib/test/test_optimizers.py

@@ -235,5 +235,5 @@ class AsyncSamplesOptimizerTest(unittest.TestCase):
         raise AssertionError("TIMED OUT", optimizer.stats())
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main(verbosity=2)

python/ray/rllib/test/test_policy_evaluator.py

@@ -416,6 +416,6 @@ class TestPolicyEvaluator(unittest.TestCase):
         return obs_f
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     ray.init(num_cpus=5)
     unittest.main(verbosity=2)

python/ray/tune/examples/bayesopt_example.py

@@ -23,7 +23,7 @@ def easy_objective(config, reporter):
         time.sleep(0.02)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
 
     parser = argparse.ArgumentParser()

python/ray/tune/examples/genetic_example.py

@@ -27,7 +27,7 @@ def michalewicz_function(config, reporter):
     reporter(timesteps_total=1, neg_mean_loss=-y)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
 
     parser = argparse.ArgumentParser()

python/ray/tune/examples/hyperopt_example.py

@@ -25,7 +25,7 @@ def easy_objective(config, reporter):
         time.sleep(0.02)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
     from hyperopt import hp
 

python/ray/tune/examples/mnist_pytorch.py

@@ -150,7 +150,7 @@ def train_mnist(args, config, reporter):
         test()
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     datasets.MNIST('~/data', train=True, download=True)
     args = parser.parse_args()
 

python/ray/tune/examples/mnist_pytorch_trainable.py

@@ -165,7 +165,7 @@ class TrainMNIST(Trainable):
         self.model.load_state_dict(checkpoint_path)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     datasets.MNIST('~/data', train=True, download=True)
     args = parser.parse_args()
 

python/ray/tune/examples/nevergrad_example.py

@@ -23,7 +23,7 @@ def easy_objective(config, reporter):
         time.sleep(0.02)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
     from nevergrad.optimization import optimizerlib
 

python/ray/tune/examples/sigopt_example.py

@@ -23,7 +23,7 @@ def easy_objective(config, reporter):
         time.sleep(0.02)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
     import os
 

python/ray/tune/examples/skopt_example.py

@@ -23,7 +23,7 @@ def easy_objective(config, reporter):
         time.sleep(0.02)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import argparse
     from skopt import Optimizer
 

python/ray/tune/examples/tune_mnist_async_hyperband.py

@@ -212,7 +212,7 @@ def train(config={'activation': 'relu'}, reporter=None):
 
 
 # !!! Example of using the ray.tune Python API !!!
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument(
         '--smoke-test', action='store_true', help='Finish quickly for testing')

python/ray/tune/examples/tune_mnist_keras.py

@@ -165,7 +165,7 @@ def create_parser():
     return parser
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = create_parser()
     args = parser.parse_args()
     mnist.load_data()  # we do this because it's not threadsafe

python/ray/tune/examples/tune_mnist_ray.py

@@ -213,7 +213,7 @@ def train(config={'activation': 'relu'}, reporter=None):
 
 
 # !!! Example of using the ray.tune Python API !!!
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument(
         '--smoke-test', action='store_true', help='Finish quickly for testing')

python/ray/tune/examples/tune_mnist_ray_hyperband.py

@@ -209,7 +209,7 @@ class TrainMNIST(Trainable):
 
 
 # !!! Example of using the ray.tune Python API !!!
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument(
         '--smoke-test', action='store_true', help='Finish quickly for testing')

python/ray/tune/schedulers/async_hyperband.py

@@ -151,7 +151,7 @@ class _Bracket():
         return "Bracket: " + iters
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     sched = AsyncHyperBandScheduler(
         grace_period=1, max_t=10, reduction_factor=2)
     print(sched.debug_string())

python/ray/tune/util.py

@@ -87,7 +87,7 @@ def _from_pinnable(obj):
     return obj[0]
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     ray.init()
     X = pin_in_object_store("hello")
     print(X)