def test_two_preprocessor_layers_in_a_preprocessor_stack(self):
space = Dict(a=FloatBox(shape=(1, 2)),
b=FloatBox(shape=(2, 2, 2)),
c=Tuple(FloatBox(shape=(2, )),
Dict(ca=FloatBox(shape=(3, 3, 2)))))
# Construct the Component to test (PreprocessorStack).
scale = Multiply(factor=2)
gray = GrayScale(weights=(0.5, 0.5), keep_rank=False)
stack = PreprocessorStack(scale, gray)
test = ComponentTest(component=stack, input_spaces=dict(inputs=space))
input_ = dict(
a=np.array([[3.0, 5.0]]),
b=np.array([[[2.0, 4.0], [2.0, 4.0]], [[2.0, 4.0], [2.0, 4.0]]]),
c=(np.array([10.0, 20.0]),
dict(ca=np.array([[[1.0, 2.0], [1.0, 2.0], [1.0, 2.0]],
[[1.0, 2.0], [1.0, 2.0], [1.0, 2.0]],
[[1.0, 2.0], [1.0, 2.0], [1.0, 2.0]]]))))
expected = dict(a=np.array([8.0]),
b=np.array([[6.0, 6.0], [6.0, 6.0]]),
c=(30.0,
dict(ca=np.array([[3.0, 3.0, 3.0], [3.0, 3.0, 3.0],
[3.0, 3.0, 3.0]]))))
test.test("reset")
test.test(("preprocess", input_), expected_outputs=expected)
def test_multiply(self):
multiply = Multiply(factor=2.0)
test = ComponentTest(component=multiply,
input_spaces=dict(preprocessing_inputs=FloatBox(
shape=(2, 1), add_batch_rank=True)))
test.test("reset")
# Batch=2
input_ = np.array([[[1.0], [2.0]], [[3.0], [4.0]]])
expected = np.array([[[2.0], [4.0]], [[6.0], [8.0]]])
test.test(("apply", input_), expected_outputs=expected)