tf.compat.v1.extract_image_patches

Extract patches from images and put them in the "depth" output dimension.

Compat aliases for migration

tf.compat.v1.image.extract_image_patches

tf.compat.v1.extract_image_patches(
    images, ksizes=None, strides=None, rates=None, padding=None, name=None,
    sizes=None
)

Args
`images`	A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `int8`, `int16`, `int32`, `int64`, `uint8`, `uint16`, `uint32`, `uint64`, `complex64`, `complex128`, `bool`. 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.
`ksizes`	A list of `ints` that has length `>= 4`. The size of the sliding window for each dimension of `images`.
`strides`	A list of `ints` that has length `>= 4`. How far the centers of two consecutive patches are in the images. Must be: `[1, stride_rows, stride_cols, 1]`.
`rates`	A list of `ints` that has length `>= 4`. Must be: `[1, rate_rows, rate_cols, 1]`. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with `patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)`, followed by subsampling them spatially by a factor of `rates`. This is equivalent to `rate` in dilated (a.k.a. Atrous) convolutions.
`padding`	A `string` from: `"SAME", "VALID"`. The type of padding algorithm to use.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `images`.

Args