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)