Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.
tf.extract_volume_patches(
input, ksizes, strides, padding, name=None
)
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.
We specify the size-related attributes as:
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.