def test_extract(self):
for input_shape in [(1, 3, 40, 40), (1, 3, 10, 10)]:
for kernel_shape in [2, 5]:
xval = np.random.random(input_shape)
kernel = [kernel_shape, kernel_shape]
strides = [kernel_shape, kernel_shape]
xth = KTH.variable(xval)
xtf = KTF.variable(xval)
ztf = KTF.eval(KCTF.extract_image_patches(xtf, kernel, strides, data_format='channels_first', padding='valid'))
zth = KTH.eval(KCTH.extract_image_patches(xth, kernel, strides, data_format='channels_first', padding='valid'))
assert zth.shape == ztf.shape
assert_allclose(zth, ztf, atol=1e-02)
for input_shape in [(1, 40, 40, 3), (1, 10, 10, 3)]:
for kernel_shape in [2, 5]:
xval = np.random.random(input_shape)
kernel = [kernel_shape, kernel_shape]
strides = [kernel_shape, kernel_shape]
xth = KTH.variable(xval)
xtf = KTF.variable(xval)
ztf = KTF.eval(KCTF.extract_image_patches(xtf, kernel, strides, data_format='channels_last', padding='same'))
zth = KTH.eval(KCTH.extract_image_patches(xth, kernel, strides, data_format='channels_last', padding='same'))
assert zth.shape == ztf.shape
assert_allclose(zth, ztf, atol=1e-02)
def test_extract(self):
for input_shape in [(1, 3, 40, 40), (1, 3, 10, 10)]:
for kernel_shape in [2, 5]:
xval = np.random.random(input_shape)
kernel = [kernel_shape, kernel_shape]
strides = [kernel_shape, kernel_shape]
xth = KTH.variable(xval)
xtf = KTF.variable(xval)
ztf = KTF.eval(
KCTF.extract_image_patches(xtf,
kernel,
strides,
dim_ordering='th',
border_mode="valid"))
zth = KTH.eval(
KCTH.extract_image_patches(xth,
kernel,
strides,
dim_ordering='th',
border_mode="valid"))
assert zth.shape == ztf.shape
assert_allclose(zth, ztf, atol=1e-02)
for input_shape in [(1, 40, 40, 3), (1, 10, 10, 3)]:
for kernel_shape in [2, 5]:
xval = np.random.random(input_shape)
kernel = [kernel_shape, kernel_shape]
strides = [kernel_shape, kernel_shape]
xth = KTH.variable(xval)
xtf = KTF.variable(xval)
ztf = KTF.eval(
KCTF.extract_image_patches(xtf,
kernel,
strides,
dim_ordering='tf',
border_mode="same"))
zth = KTH.eval(
KCTH.extract_image_patches(xth,
kernel,
strides,
dim_ordering='tf',
border_mode="same"))
assert zth.shape == ztf.shape
assert_allclose(zth, ztf, atol=1e-02)
def test_extract(self, input_shape, kernel_shape):
xval = np.random.random(input_shape)
kernel = [kernel_shape, kernel_shape]
strides = [kernel_shape, kernel_shape]
xth = KTH.variable(xval)
xtf = KTF.variable(xval)
ztf = KTF.eval(KCTF.extract_image_patches(xtf, kernel, strides,
data_format='channels_first',
padding='valid'))
zth = KTH.eval(KCTH.extract_image_patches(xth, kernel, strides,
data_format='channels_first',
padding='valid'))
assert zth.shape == ztf.shape
assert_allclose(zth, ztf, atol=1e-02)