def test_walker_is_correctly_reinitialized(
self, position_offset, rotate_180_degrees, use_variations):
walker_spawn_position = position_offset
if not rotate_180_degrees:
walker_spawn_rotation = None
else:
walker_spawn_rotation = np.pi
if use_variations:
walker_spawn_position = deterministic.Constant(position_offset)
walker_spawn_rotation = deterministic.Constant(walker_spawn_rotation)
walker = cmu_humanoid.CMUHumanoid()
arena = corridor_arenas.EmptyCorridor()
task = corridor_tasks.RunThroughCorridor(
walker=walker,
arena=arena,
walker_spawn_position=walker_spawn_position,
walker_spawn_rotation=walker_spawn_rotation)
# Randomize the initial pose and joint positions in order to check that they
# are set correctly by `initialize_episode`.
random_state = np.random.RandomState(12345)
task.initialize_episode_mjcf(random_state)
physics = mjcf.Physics.from_mjcf_model(task.root_entity.mjcf_model)
walker_joints = walker.mjcf_model.find_all('joint')
physics.bind(walker_joints).qpos = random_state.uniform(
size=len(walker_joints))
walker.set_pose(physics,
position=random_state.uniform(size=3),
quaternion=rotations.UniformQuaternion()(random_state))
task.initialize_episode(physics, random_state)
physics.forward()
with self.subTest('Correct joint positions'):
walker_qpos = physics.bind(walker_joints).qpos
if walker.upright_pose.qpos is not None:
np.testing.assert_array_equal(walker_qpos, walker.upright_pose.qpos)
else:
walker_qpos0 = physics.bind(walker_joints).qpos0
np.testing.assert_array_equal(walker_qpos, walker_qpos0)
walker_xpos, walker_xquat = walker.get_pose(physics)
with self.subTest('Correct position'):
expected_xpos = walker.upright_pose.xpos + np.array(position_offset)
np.testing.assert_array_equal(walker_xpos, expected_xpos)
with self.subTest('Correct orientation'):
upright_xquat = walker.upright_pose.xquat.copy()
upright_xquat /= np.linalg.norm(walker.upright_pose.xquat)
if rotate_180_degrees:
expected_xquat = (-upright_xquat[3], -upright_xquat[2],
upright_xquat[1], upright_xquat[0])
else:
expected_xquat = upright_xquat
np.testing.assert_allclose(walker_xquat, expected_xquat)
def testMultiplicative(self, use_constant_variation_object):
amount = 23
if use_constant_variation_object:
variation = noises.Multiplicative(deterministic.Constant(amount))
else:
variation = noises.Multiplicative(amount)
initial_value = 3
current_value = initial_value
for _ in range(NUM_ITERATIONS):
current_value = variation(initial_value=initial_value,
current_value=current_value)
self.assertEqual(current_value, initial_value * amount)
def testAdditiveCumulative(self, use_constant_variation_object):
amount = 3
if use_constant_variation_object:
variation = noises.Additive(deterministic.Constant(amount),
cumulative=True)
else:
variation = noises.Additive(amount, cumulative=True)
initial_value = 1
current_value = initial_value
for i in range(NUM_ITERATIONS):
current_value = variation(initial_value=initial_value,
current_value=current_value)
self.assertEqual(current_value, initial_value + amount * (i + 1))
def test_getitem(self):
value = deterministic.Constant(np.array([4, 5, 6, 7, 8]))
np.testing.assert_array_equal(variation.evaluate(value[[3, 1]]),
[7, 5])
def setUp(self):
super(VariationTest, self).setUp()
self.value_1 = 3
self.variation_1 = deterministic.Constant(self.value_1)
self.value_2 = 5
self.variation_2 = deterministic.Constant(self.value_2)
def setUp(self):
self.value_1 = 3
self.variation_1 = deterministic.Constant(self.value_1)
self.value_2 = 5
self.variation_2 = deterministic.Constant(self.value_2)
