def testStepHybrid(self):
obs_spec = array_spec.BoundedArraySpec((2, 3), np.int32, -10, 10)
action_spec = {
'discrete':
array_spec.BoundedArraySpec((1,), np.int32, 1, 3),
'continuous':
array_spec.ArraySpec((2,), np.float32)
}
mock_env = mock.Mock(
wraps=random_py_environment.RandomPyEnvironment(obs_spec, action_spec))
one_hot_action_wrapper = wrappers.OneHotActionWrapper(mock_env)
one_hot_action_wrapper.reset()
action = {
'discrete':
np.array([[0, 1, 0]]).astype(np.int32),
'continuous':
np.array([0.5, 0.3]).astype(np.float32)
}
one_hot_action_wrapper.step(action)
self.assertTrue(mock_env.step.called)
expected_action = {
'discrete':
np.array([2]),
'continuous':
np.array([0.5, 0.3])
}
np.testing.assert_array_almost_equal(
expected_action['discrete'], mock_env.step.call_args[0][0]['discrete'])
np.testing.assert_array_almost_equal(
expected_action['continuous'],
mock_env.step.call_args[0][0]['continuous'])
def testActionSpec(self):
cartpole_env = gym.spec('CartPole-v1').make()
env = gym_wrapper.GymWrapper(cartpole_env)
one_hot_action_wrapper = wrappers.OneHotActionWrapper(env)
expected_spec = array_spec.BoundedArraySpec(shape=(2, ),
dtype=np.int64,
minimum=0,
maximum=1,
name='one_hot_action_spec')
self.assertEqual(one_hot_action_wrapper.action_spec(), expected_spec)
def testStep(self):
obs_spec = array_spec.BoundedArraySpec((2, 3), np.int32, -10, 10)
action_spec = array_spec.BoundedArraySpec((1, ), np.int32, 0, 2)
mock_env = mock.Mock(wraps=random_py_environment.RandomPyEnvironment(
obs_spec, action_spec))
one_hot_action_wrapper = wrappers.OneHotActionWrapper(mock_env)
one_hot_action_wrapper.reset()
one_hot_action_wrapper.step(np.array([0.5, 0.4, 0.1]))
self.assertTrue(mock_env.step.called)
np.testing.assert_array_equal(0, mock_env.step.call_args[0][0])
