def test_sequence_preprocessor(self):
space = FloatBox(shape=(1,), add_batch_rank=True)
sequencer = Sequence(sequence_length=3, add_rank=True)
test = ComponentTest(component=sequencer, input_spaces=dict(preprocessing_inputs=space))
vars = sequencer.get_variables("index", "buffer", global_scope=False)
index, buffer = vars["index"], vars["buffer"]
for _ in range_(3):
test.test("reset")
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, -1)
test.test(("apply", np.array([[0.1]])),
expected_outputs=np.array([[[0.1, 0.1, 0.1]]]))
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, 0)
test.test(("apply", np.array([[0.2]])),
expected_outputs=np.array([[[0.1, 0.1, 0.2]]]))
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, 1)
test.test(("apply", np.array([[0.3]])),
expected_outputs=np.array([[[0.1, 0.2, 0.3]]]))
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, 2)
test.test(("apply", np.array([[0.4]])),
expected_outputs=np.array([[[0.2, 0.3, 0.4]]]))
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, 0)
test.test(("apply", np.array([[0.5]])),
expected_outputs=np.array([[[0.3, 0.4, 0.5]]]))
index_value, buffer_value = test.read_variable_values(index, buffer)
self.assertEqual(index_value, 1)
def test_python_sequence_preprocessor(self):
seq_len = 3
space = FloatBox(shape=(1,), add_batch_rank=True)
sequencer = Sequence(sequence_length=seq_len, batch_size=4, add_rank=True, backend="python")
sequencer.create_variables(input_spaces=dict(preprocessing_inputs=space))
#test = ComponentTest(component=sequencer, input_spaces=dict(apply=space))
for _ in range_(3):
sequencer._graph_fn_reset()
self.assertEqual(sequencer.index, -1)
input_ = np.asarray([[1.0], [2.0], [3.0], [4.0]])
out = sequencer._graph_fn_apply(input_)
self.assertEqual(sequencer.index, 0)
recursive_assert_almost_equal(
out, np.asarray([[[1.0, 1.0, 1.0]], [[2.0, 2.0, 2.0]], [[3.0, 3.0, 3.0]], [[4.0, 4.0, 4.0]]])
)
input_ = np.asarray([[1.1], [2.2], [3.3], [4.4]])
out = sequencer._graph_fn_apply(input_)
self.assertEqual(sequencer.index, 1)
recursive_assert_almost_equal(
out, np.asarray([[[1.0, 1.0, 1.1]], [[2.0, 2.0, 2.2]], [[3.0, 3.0, 3.3]], [[4.0, 4.0, 4.4]]])
)
input_ = np.asarray([[1.11], [2.22], [3.33], [4.44]])
out = sequencer._graph_fn_apply(input_)
self.assertEqual(sequencer.index, 2)
recursive_assert_almost_equal(
out, np.asarray([[[1.0, 1.1, 1.11]], [[2.0, 2.2, 2.22]], [[3.0, 3.3, 3.33]], [[4.0, 4.4, 4.44]]])
)
input_ = np.asarray([[10], [20], [30], [40]])
out = sequencer._graph_fn_apply(input_)
self.assertEqual(sequencer.index, 0)
recursive_assert_almost_equal(
out, np.asarray([[[1.1, 1.11, 10]], [[2.2, 2.22, 20]], [[3.3, 3.33, 30]], [[4.4, 4.44, 40]]])
)
def test_sequence_preprocessor_with_container_space(self):
# Test with no batch rank.
space = Tuple(
FloatBox(shape=(1,)),
FloatBox(shape=(2, 2)),
add_batch_rank=False
)
component_to_test = Sequence(sequence_length=4, add_rank=False)
test = ComponentTest(component=component_to_test, input_spaces=dict(preprocessing_inputs=space))
for i in range_(3):
test.test("reset")
test.test(("apply", np.array([np.array([0.5]), np.array([[0.6, 0.7], [0.8, 0.9]])])),
expected_outputs=(np.array([0.5, 0.5, 0.5, 0.5]), np.array([[0.6, 0.7] * 4,
[0.8, 0.9] * 4])))
test.test(("apply", np.array([np.array([0.6]), np.array([[1.1, 1.1], [1.1, 1.1]])])),
expected_outputs=(np.array([0.5, 0.5, 0.5, 0.6]), np.array([[0.6, 0.7, 0.6, 0.7,
0.6, 0.7, 1.1, 1.1],
[0.8, 0.9, 0.8, 0.9,
0.8, 0.9, 1.1, 1.1]])))
test.test(("apply", np.array([np.array([0.7]), np.array([[2.0, 2.1], [2.2, 2.3]])])),
expected_outputs=(np.array([0.5, 0.5, 0.6, 0.7]), np.array([[0.6, 0.7, 0.6, 0.7,
1.1, 1.1, 2.0, 2.1],
[0.8, 0.9, 0.8, 0.9,
1.1, 1.1, 2.2, 2.3]])))
def test_sequence_preprocessor_with_batch(self):
space = FloatBox(shape=(2, ), add_batch_rank=True)
sequencer = Sequence(sequence_length=2, batch_size=3, add_rank=True)
test = ComponentTest(component=sequencer,
input_spaces=dict(preprocessing_inputs=space))
vars = sequencer.get_variables("index", "buffer", global_scope=False)
index, buffer = vars["index"], vars["buffer"]
for _ in range_(3):
test.test("reset")
index_value, buffer_value = test.read_variable_values(
index, buffer)
self.assertEqual(index_value, -1)
test.test(
("apply", np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])),
expected_outputs=np.array([[[1.0, 1.0], [2.0, 2.0]],
[[3.0, 3.0], [4.0, 4.0]],
[[5.0, 5.0], [6.0, 6.0]]]))
index_value, buffer_value = test.read_variable_values(
index, buffer)
self.assertEqual(index_value, 0)
test.test(
("apply", np.array([[0.1, 0.2], [0.3, 0.4], [0.5, 0.6]])),
expected_outputs=np.array([[[1.0, 0.1], [2.0, 0.2]],
[[3.0, 0.3], [4.0, 0.4]],
[[5.0, 0.5], [6.0, 0.6]]]))
index_value, buffer_value = test.read_variable_values(
index, buffer)
self.assertEqual(index_value, 1)
test.test(
("apply", np.array([[10.0, 20.0], [30.0, 40.0], [50.0, 60.0]
])),
expected_outputs=np.array([[[0.1, 10.0], [0.2, 20.0]],
[[0.3, 30.0], [0.4, 40.0]],
[[0.5, 50.0], [0.6, 60.0]]]))
index_value, buffer_value = test.read_variable_values(
index, buffer)
self.assertEqual(index_value, 0)
test.test(
("apply",
np.array([[100.0, 200.0], [300.0, 400.0], [500.0, 600.0]])),
expected_outputs=np.array([[[10.0, 100.0], [20.0, 200.0]],
[[30.0, 300.0], [40.0, 400.0]],
[[50.0, 500.0], [60.0, 600.0]]]))
index_value, buffer_value = test.read_variable_values(
index, buffer)
self.assertEqual(index_value, 1)
test.terminate()