Release 0.7 Fix gym_unity Tests (#1744)

* Change gym-unity tests to use Mock instead of MockCommunicator

* move creation of mock objects into helper functions

* Fix comment

* Fix Codacy errors

* Fix ending whitespace

* Minor fixes

gym-unity/tests/test_gym.py

 
 from gym import spaces
 from gym_unity.envs import UnityEnv, UnityGymException
-from mock_communicator import MockCommunicator
-@mock.patch('mlagents.envs.UnityEnvironment.executable_launcher')
-@mock.patch('mlagents.envs.UnityEnvironment.get_communicator')
-def test_gym_wrapper(mock_communicator, mock_launcher):
-    mock_communicator.return_value = MockCommunicator(
-        discrete_action=False, visual_inputs=0, stack=False, num_agents=1)
+# Tests
-    # Test for incorrect number of agents.
-    with pytest.raises(UnityGymException):
-        UnityEnv(' ', use_visual=False, multiagent=True)
-    env = UnityEnv(' ', use_visual=False)
+@mock.patch('gym_unity.envs.unity_env.UnityEnvironment')
+def test_gym_wrapper(mock_env):
+    mock_brain = create_mock_brainparams()
+    mock_braininfo = create_mock_vector_braininfo()
+    setup_mock_unityenvironment(mock_env, mock_brain, mock_braininfo)
+
+    env = UnityEnv(' ', use_visual=False, multiagent=False)
     assert isinstance(env, UnityEnv)
     assert isinstance(env.reset(), np.ndarray)
     actions = env.action_space.sample()
     assert isinstance(done, bool)
     assert isinstance(info, dict)
 
-@mock.patch('mlagents.envs.UnityEnvironment.executable_launcher')
-@mock.patch('mlagents.envs.UnityEnvironment.get_communicator')
-def test_multi_agent(mock_communicator, mock_launcher):
-    mock_communicator.return_value = MockCommunicator(
-        discrete_action=False, visual_inputs=0, stack=False, num_agents=2)
-    # Test for incorrect number of agents.
+@mock.patch('gym_unity.envs.unity_env.UnityEnvironment')
+def test_multi_agent(mock_env):
+    mock_brain = create_mock_brainparams()
+    mock_braininfo = create_mock_vector_braininfo(num_agents=2)
+    setup_mock_unityenvironment(mock_env, mock_brain, mock_braininfo)
+
     with pytest.raises(UnityGymException):
         UnityEnv(' ', multiagent=False)
 
     assert isinstance(done, list)
     assert isinstance(info, dict)
 
+
-    mock_env.return_value.academy_name = 'MockAcademy'
-    mock_brain = mock.Mock();
-    mock_brain.return_value.number_visual_observations = 0
-    mock_brain.return_value.num_stacked_vector_observations = 1
-    mock_brain.return_value.vector_action_space_type = 'discrete'
-    mock_brain.return_value.vector_observation_space_size = 1
-    # Unflattened action space
-    mock_brain.return_value.vector_action_space_size = [2,2,3]
+    mock_brain = create_mock_brainparams(vector_action_space_type='discrete', vector_action_space_size=[2,2,3])
+    mock_braininfo = create_mock_vector_braininfo(num_agents=1)
+    setup_mock_unityenvironment(mock_env, mock_brain, mock_braininfo)
-    mock_env.return_value.brains = {'MockBrain':mock_brain()}
-    mock_env.return_value.external_brain_names = ['MockBrain']
     env = UnityEnv(' ', use_visual=False, multiagent=False, flatten_branched=True)
     assert isinstance(env.action_space, spaces.Discrete)
     assert env.action_space.n==12
     # Check that False produces a MultiDiscrete
     env = UnityEnv(' ', use_visual=False, multiagent=False, flatten_branched=False)
     assert isinstance(env.action_space, spaces.MultiDiscrete)
+
+# Helper methods
+
+
+def create_mock_brainparams(number_visual_observations=0, num_stacked_vector_observations=1,
+                            vector_action_space_type='continuous', vector_observation_space_size=3,
+                            vector_action_space_size=None):
+    """
+    Creates a mock BrainParameters object with parameters.
+    """
+    # Avoid using mutable object as default param
+    if vector_action_space_size is None:
+        vector_action_space_size = [2]
+    mock_brain = mock.Mock();
+    mock_brain.return_value.number_visual_observations = number_visual_observations
+    mock_brain.return_value.num_stacked_vector_observations = num_stacked_vector_observations
+    mock_brain.return_value.vector_action_space_type = vector_action_space_type
+    mock_brain.return_value.vector_observation_space_size = vector_observation_space_size
+    mock_brain.return_value.vector_action_space_size = vector_action_space_size
+    return mock_brain()
+
+
+def create_mock_vector_braininfo(num_agents = 1):
+    """
+    Creates a mock BrainInfo with vector observations. Imitates constant
+    vector observations, rewards, dones, and agents.
+
+    :int num_agents: Number of "agents" to imitate in your BrainInfo values.
+    """
+    mock_braininfo = mock.Mock()
+    mock_braininfo.return_value.vector_observations = np.array([num_agents*[1, 2, 3,]])
+    mock_braininfo.return_value.rewards = num_agents*[1.0]
+    mock_braininfo.return_value.local_done = num_agents*[False]
+    mock_braininfo.return_value.text_observations = num_agents*['']
+    mock_braininfo.return_value.agents = range(0,num_agents)
+    return mock_braininfo()
+
+
+def setup_mock_unityenvironment(mock_env, mock_brain, mock_braininfo):
+    """
+    Takes a mock UnityEnvironment and adds the appropriate properties, defined by the mock
+    BrainParameters and BrainInfo.
+
+    :Mock mock_env: A mock UnityEnvironment, usually empty.
+    :Mock mock_brain: A mock Brain object that specifies the params of this environment.
+    :Mock mock_braininfo: A mock BrainInfo object that will be returned at each step and reset.
+    """
+    mock_env.return_value.academy_name = 'MockAcademy'
+    mock_env.return_value.brains = {'MockBrain':mock_brain}
+    mock_env.return_value.external_brain_names = ['MockBrain']
+    mock_env.return_value.reset.return_value = {'MockBrain':mock_braininfo}
+    mock_env.return_value.step.return_value = {'MockBrain':mock_braininfo}