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
)
Args |
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).
|
Returns |
A Tensor . Has the same type as input .
|