def test_trainer_increment_step(dummy_config):
trainer_params = dummy_config
brain_params = BrainParameters("test_brain", 1, 1, [], [2], [], 0)
trainer = PPOTrainer(brain_params, 0, trainer_params, True, False, 0, "0", False)
policy_mock = mock.Mock()
step_count = 10
policy_mock.increment_step = mock.Mock(return_value=step_count)
trainer.policy = policy_mock
trainer.increment_step(5)
policy_mock.increment_step.assert_called_with(5)
assert trainer.step == 10
def test_trainer_increment_step():
trainer_params = {
"trainer": "ppo",
"batch_size": 2048,
"beta": 0.005,
"buffer_size": 20480,
"epsilon": 0.2,
"gamma": 0.995,
"hidden_units": 512,
"lambd": 0.95,
"learning_rate": 0.0003,
"max_steps": "2e6",
"memory_size": 256,
"normalize": True,
"num_epoch": 3,
"num_layers": 3,
"time_horizon": 1000,
"sequence_length": 64,
"summary_freq": 3000,
"use_recurrent": False,
"use_curiosity": False,
"curiosity_strength": 0.01,
"curiosity_enc_size": 128,
"summary_path": "./summaries/test_trainer_summary",
"model_path": "./models/test_trainer_models/TestModel",
"keep_checkpoints": 5,
"reward_signals": {
"extrinsic": {
"strength": 1.0,
"gamma": 0.99
}
},
}
brain_params = BrainParameters("test_brain", 1, 1, [], [2], [], 0)
trainer = PPOTrainer(brain_params, 0, trainer_params, True, False, 0, "0",
False)
policy_mock = mock.Mock()
step_count = 10
policy_mock.increment_step = mock.Mock(return_value=step_count)
trainer.policy = policy_mock
trainer.increment_step(5)
policy_mock.increment_step.assert_called_with(5)
assert trainer.step == 10
def test_trainer_increment_step(dummy_config):
trainer_params = dummy_config
brain_params = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=1,
camera_resolutions=[],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=0,
)
trainer = PPOTrainer(brain_params, 0, trainer_params, True, False, 0, "0", False)
policy_mock = mock.Mock()
step_count = 10
policy_mock.increment_step = mock.Mock(return_value=step_count)
trainer.policy = policy_mock
trainer.increment_step(5)
policy_mock.increment_step.assert_called_with(5)
assert trainer.step == 10
def test_trainer_increment_step(dummy_config):
trainer_params = dummy_config
brain_params = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=1,
camera_resolutions=[],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=0,
)
trainer = PPOTrainer(brain_params.brain_name, 0, trainer_params, True,
False, 0, "0", False)
policy_mock = mock.Mock()
step_count = (
5
) # 10 hacked becausee this function is no longer called through trainer
policy_mock.increment_step = mock.Mock(return_value=step_count)
trainer.policy = policy_mock
trainer.increment_step(5)
print(trainer.policy.increment_step(5))
policy_mock.increment_step.assert_called_with(5)
assert trainer.step == step_count
