Merge pull request #3097 from Unity-Technologies/develop-pytest5

Update tests to support pytest 5.x

ml-agents/mlagents/trainers/tests/test_learn.py

 from mlagents.trainers.learn import parse_command_line
 
 
-@pytest.fixture
 def basic_options(extra_args=None):
     extra_args = extra_args or {}
     args = ["basic_path"]

ml-agents/mlagents/trainers/tests/test_rl_trainer.py

 from mlagents.trainers.buffer import AgentBuffer
 
 
-@pytest.fixture
 def dummy_config():
     return yaml.safe_load(
         """

ml-agents/mlagents/trainers/tests/test_sac.py

             sess.run(run_list, feed_dict=feed_dict)
 
 
-def test_sac_save_load_buffer(tmpdir):
+def test_sac_save_load_buffer(tmpdir, dummy_config):
     env, mock_brain, _ = mb.setup_mock_env_and_brains(
         mock.Mock(),
         False,
         vector_obs_space=VECTOR_OBS_SPACE,
         discrete_action_space=DISCRETE_ACTION_SPACE,
     )
-    trainer_params = dummy_config()
+    trainer_params = dummy_config
     trainer_params["summary_path"] = str(tmpdir)
     trainer_params["model_path"] = str(tmpdir)
     trainer_params["save_replay_buffer"] = True

ml-agents/mlagents/trainers/tests/test_trainer_controller.py

 from unittest.mock import MagicMock, Mock, patch
+import pytest
-
-import yaml
-import pytest
-
 from mlagents.trainers.trainer_controller import TrainerController
 from mlagents.trainers.subprocess_env_manager import EnvironmentStep
 from mlagents.trainers.sampler_class import SamplerManager
-def dummy_config():
-    return yaml.safe_load(
-        """
-        default:
-            trainer: ppo
-            batch_size: 32
-            beta: 5.0e-3
-            buffer_size: 512
-            epsilon: 0.2
-            gamma: 0.99
-            hidden_units: 128
-            lambd: 0.95
-            learning_rate: 3.0e-4
-            max_steps: 5.0e4
-            normalize: true
-            num_epoch: 5
-            num_layers: 2
-            time_horizon: 64
-            sequence_length: 64
-            summary_freq: 1000
-            use_recurrent: false
-            memory_size: 8
-            use_curiosity: false
-            curiosity_strength: 0.0
-            curiosity_enc_size: 1
-        """
-    )
-
-
-@pytest.fixture
 def basic_trainer_controller():
     return TrainerController(
         trainer_factory=None,
     tensorflow_set_seed.assert_called_with(seed)
 
 
-def trainer_controller_with_start_learning_mocks():
+@pytest.fixture
+def trainer_controller_with_start_learning_mocks(basic_trainer_controller):
     trainer_mock = MagicMock()
     trainer_mock.get_step = 0
     trainer_mock.get_max_steps = 5
-    tc = basic_trainer_controller()
+    tc = basic_trainer_controller
     tc.initialize_trainers = MagicMock()
     tc.trainers = {"testbrain": trainer_mock}
     tc.advance = MagicMock()
 
 
 @patch.object(tf, "reset_default_graph")
-def test_start_learning_trains_forever_if_no_train_model(tf_reset_graph):
-    tc, trainer_mock = trainer_controller_with_start_learning_mocks()
+def test_start_learning_trains_forever_if_no_train_model(
+    tf_reset_graph, trainer_controller_with_start_learning_mocks
+):
+    tc, trainer_mock = trainer_controller_with_start_learning_mocks
     tc.train_model = False
 
     tf_reset_graph.return_value = None
 
 
 @patch.object(tf, "reset_default_graph")
-def test_start_learning_trains_until_max_steps_then_saves(tf_reset_graph):
-    tc, trainer_mock = trainer_controller_with_start_learning_mocks()
+def test_start_learning_trains_until_max_steps_then_saves(
+    tf_reset_graph, trainer_controller_with_start_learning_mocks
+):
+    tc, trainer_mock = trainer_controller_with_start_learning_mocks
     tf_reset_graph.return_value = None
 
     brain_info_mock = MagicMock()
     tc._save_model.assert_called_once()
 
 
-def trainer_controller_with_take_step_mocks():
+@pytest.fixture
+def trainer_controller_with_take_step_mocks(basic_trainer_controller):
     trainer_mock = MagicMock()
     trainer_mock.get_step = 0
     trainer_mock.get_max_steps = 5
-    tc = basic_trainer_controller()
+    tc = basic_trainer_controller
-def test_take_step_adds_experiences_to_trainer_and_trains():
-    tc, trainer_mock = trainer_controller_with_take_step_mocks()
+def test_take_step_adds_experiences_to_trainer_and_trains(
+    trainer_controller_with_take_step_mocks
+):
+    tc, trainer_mock = trainer_controller_with_take_step_mocks
 
     brain_name = "testbrain"
     action_info_dict = {brain_name: MagicMock()}
     trainer_mock.increment_step.assert_called_once()
 
 
-def test_take_step_if_not_training():
-    tc, trainer_mock = trainer_controller_with_take_step_mocks()
+def test_take_step_if_not_training(trainer_controller_with_take_step_mocks):
+    tc, trainer_mock = trainer_controller_with_take_step_mocks
     tc.train_model = False
 
     brain_name = "testbrain"

ml-agents/mlagents/trainers/tests/test_trainer_util.py

 
 
 @pytest.fixture
-def dummy_config_with_override():
-    base = dummy_config()
+def dummy_config_with_override(dummy_config):
+    base = dummy_config
     base["testbrain"] = {}
     base["testbrain"]["normalize"] = False
     return base
 
 
 @patch("mlagents.trainers.brain.BrainParameters")
-def test_initialize_trainer_parameters_override_defaults(BrainParametersMock):
+def test_initialize_trainer_parameters_override_defaults(
+    BrainParametersMock, dummy_config_with_override
+):
     summaries_dir = "test_dir"
     run_id = "testrun"
     model_path = "model_dir"
     seed = 11
     expected_reward_buff_cap = 1
 
-    base_config = dummy_config_with_override()
+    base_config = dummy_config_with_override
     expected_config = base_config["default"]
     expected_config["summary_path"] = summaries_dir + f"/{run_id}_testbrain"
     expected_config["model_path"] = model_path + "/testbrain"
 
 
 @patch("mlagents.trainers.brain.BrainParameters")
-def test_initialize_ppo_trainer(BrainParametersMock):
+def test_initialize_ppo_trainer(BrainParametersMock, dummy_config):
     brain_params_mock = BrainParametersMock()
     BrainParametersMock.return_value.brain_name = "testbrain"
     external_brains = {"testbrain": BrainParametersMock()}
     seed = 11
     expected_reward_buff_cap = 1
 
-    base_config = dummy_config()
+    base_config = dummy_config
     expected_config = base_config["default"]
     expected_config["summary_path"] = summaries_dir + f"/{run_id}_testbrain"
     expected_config["model_path"] = model_path + "/testbrain"
 
 
 @patch("mlagents.trainers.brain.BrainParameters")
-def test_initialize_invalid_trainer_raises_exception(BrainParametersMock):
+def test_initialize_invalid_trainer_raises_exception(
+    BrainParametersMock, dummy_bad_config
+):
     summaries_dir = "test_dir"
     run_id = "testrun"
     model_path = "model_dir"
     seed = 11
-    bad_config = dummy_bad_config()
+    bad_config = dummy_bad_config
     BrainParametersMock.return_value.brain_name = "testbrain"
     external_brains = {"testbrain": BrainParametersMock()}
 
             trainers[brain_name] = trainer_factory.generate(brain_parameters)
 
 
-def test_handles_no_default_section():
+def test_handles_no_default_section(dummy_config):
-    config = dummy_config()
-    no_default_config = {brain_name: config["default"]}
+    no_default_config = {brain_name: dummy_config["default"]}
     brain_parameters = BrainParameters(
         brain_name=brain_name,
         vector_observation_space_size=1,
     trainer_factory.generate(brain_parameters)
 
 
-def test_raise_if_no_config_for_brain():
+def test_raise_if_no_config_for_brain(dummy_config):
-    config = dummy_config()
-    bad_config = {"some_other_brain": config["default"]}
+    bad_config = {"some_other_brain": dummy_config["default"]}
     brain_parameters = BrainParameters(
         brain_name=brain_name,
         vector_observation_space_size=1,

test_requirements.txt

 # Test-only dependencies should go here, not in setup.py
-pytest>=3.2.2,<4.0.0
+pytest>4.0.0,<6.0.0
 pytest-cov==2.6.1