tf.keras.ops.unfold

Extract sliding local blocks from a 4-D input (batched image).

View aliases

Main aliases

tf.keras.ops.nn.unfold

tf.keras.ops.unfold(
    x, kernel_size, dilation=1, padding=0, stride=1
)

This operation is known as im2col when used with convolution. It rearranges the image into overlapping or non-overlapping patches and returns a tensor whose depth (last axis) contains the flattened patches.

Args
x	A 4-D tensor of shape (N, C, H, W) (channels-first format).
kernel_size	int or tuple of two ints, the size of the sliding window (kH, kW). If a single int is given, it is used for both dimensions.
dilation	int or tuple of two ints, the spacing between kernel points (a.k.a. dilation or atrous convolution). Default: 1.
padding	int or tuple of two ints, the amount of zero-padding to apply to both spatial dimensions. Default: 0.
stride	int or tuple of two ints, the step size of the sliding window. Default: 1.

Returns
A 3-D tensor of shape (N, C * kH * kW, L) where L = num_patches_H * num_patches_W is the total number of patches extracted.

Example:

x = keras.ops.ones((1, 2, 4, 4))
patches = keras.ops.unfold(x, kernel_size=2, stride=2)
patches.shape
(1, 8, 4)