def test_skip():
"""
Test a FrameSkipEnv wrapper.
"""
# Timestep limit is 5.
env = SimpleEnv(4, (3, 2, 5), 'float32')
act1 = np.random.uniform(high=255.0, size=(3, 2, 5))
act2 = np.random.uniform(high=255.0, size=(3, 2, 5))
obs1 = env.reset()
rew1 = 0.0
rew2 = 0.0
for _ in range(3):
obs2, rew, _, _ = env.step(act1)
rew1 += rew
for _ in range(2):
obs3, rew, done, _ = env.step(act2)
rew2 += rew
assert done
env = FrameSkipEnv(env, num_frames=3)
actual_obs1 = env.reset()
assert np.allclose(actual_obs1, obs1)
actual_obs2, actual_rew1, done, _ = env.step(act1)
assert not done
assert actual_rew1 == rew1
assert np.allclose(actual_obs2, obs2)
actual_obs3, actual_rew2, done, _ = env.step(act2)
assert done
assert actual_rew2 == rew2
assert np.allclose(actual_obs3, obs3)
def test_resize_even(self):
"""
Test resizing for an even number of pixels.
"""
env = SimpleEnv(5, (13, 5, 3), 'float32')
frame = env.reset()
actual = ResizeImageEnv(env, size=(5, 4)).reset()
expected = tf.Session().run(
tf.image.resize_images(frame, [5, 4], method=tf.image.ResizeMethod.AREA))
self.assertEqual(actual.shape, (5, 4, 3))
self.assertTrue(np.allclose(actual, expected))
def test_max_2(self):
"""
Test maxing 2 frames.
"""
env = SimpleEnv(5, (3, 2, 5), 'float32')
actions = [env.action_space.sample() for _ in range(4)]
frame1 = env.reset()
frame2 = env.step(actions[0])[0]
frame3 = env.step(actions[1])[0]
frame4 = env.step(actions[2])[0]
frame5 = env.step(actions[3])[0]
wrapped = MaxEnv(env, num_images=2)
max1 = wrapped.reset()
max2 = wrapped.step(actions[0])[0]
max3 = wrapped.step(actions[1])[0]
max4 = wrapped.step(actions[2])[0]
max5 = wrapped.step(actions[3])[0]
self.assertTrue((max1 == frame1).all())
self.assertTrue((max2 == np.max([frame1, frame2], axis=0)).all())
self.assertTrue((max3 == np.max([frame2, frame3], axis=0)).all())
self.assertTrue((max4 == np.max([frame3, frame4], axis=0)).all())
self.assertTrue((max5 == np.max([frame4, frame5], axis=0)).all())