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
.