def test_outout_with_interleave_and_stride_and_no_interleave():
in_shape = 200, 200
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.random.randn(200, 200).astype('f')
full_features = slm.process(img, pad_apron=True, interleave_stride=True)
features = slm.process(img, pad_apron=True, interleave_stride=False)
assert_allclose(features, full_features[::8, ::8], rtol=RTOL, atol=ATOL)
def test_outout_with_interleave_and_stride_and_no_interleave():
in_shape = 200, 200
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.random.randn(200, 200).astype('f')
full_features = slm.process(img, pad_apron=True, interleave_stride=True)
features = slm.process(img, pad_apron=True, interleave_stride=False)
assert_allclose(features, full_features[::8, ::8], rtol=RTOL, atol=ATOL)
def test_zero_input_image_with_pad_with_interleave():
in_shape = 200, 200
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.zeros(in_shape).astype('f')
features = slm.process(img, pad_apron=True, interleave_stride=True)
assert features.shape == (200, 200, 256)
assert features.sum() == 0.
def test_null_image_same_size_as_receptive_field():
in_shape = 121, 121
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.zeros(in_shape).astype('f')
features = slm.process(img)
assert features.shape == (1, 1, 256)
assert features.sum() == 0.
def test_null_image_same_size_as_receptive_field():
in_shape = 121, 121
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.zeros(in_shape).astype('f')
features = slm.process(img)
assert features.shape == (1, 1, 256)
assert features.sum() == 0.
def test_zero_input_image_with_pad_with_interleave():
in_shape = 200, 200
desc = L3_first_desc
slm = SequentialLayeredModel(in_shape, desc)
img = np.zeros(in_shape).astype('f')
features = slm.process(img, pad_apron=True, interleave_stride=True)
assert features.shape == (200, 200, 256)
assert features.sum() == 0.
