tf.extract_volume_patches

Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.

tf.extract_volume_patches(
    input: Annotated[Any, TV_ExtractVolumePatches_T],
    ksizes,
    strides,
    padding: str,
    name=None
) -> Annotated[Any, TV_ExtractVolumePatches_T]

input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. 5-D Tensor with shape [batch, in_planes, in_rows, in_cols, depth].
ksizes A list of ints that has length >= 5. The size of the sliding window for each dimension of input.
strides A list of ints that has length >= 5. 1-D of length 5. How far the centers of two consecutive patches are in input. Must be: [1, stride_planes, stride_rows, stride_cols, 1].
padding A string from: "SAME", "VALID". The type of padding algorithm to use.

The size-related attributes are specified as follows:

ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
strides = [1, stride_planes, strides_rows, strides_cols, 1]

name A name for the operation (optional).

A Tensor. Has the same type as input.