ExtractVolumePatches
Stay organized with collections
Save and categorize content based on your preferences.
Extract `patches` from `input` and put them in the `"depth"` output dimension. 3D extension of `extract_image_patches`.
Public Methods
Output<T>
|
asOutput()
Returns the symbolic handle of a tensor.
|
static
<T extends Number>
ExtractVolumePatches<T>
|
create( Scope scope, Operand<T> input, List<Long> ksizes, List<Long> strides, String padding)
Factory method to create a class wrapping a new ExtractVolumePatches operation.
|
Output<T>
|
patches()
5-D Tensor with shape `[batch, out_planes, out_rows, out_cols,
ksize_planes * ksize_rows * ksize_cols * depth]` containing patches
with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized
in the "depth" dimension.
|
Inherited Methods
From class
java.lang.Object
boolean
|
equals(Object arg0)
|
final
Class<?>
|
getClass()
|
int
|
hashCode()
|
final
void
|
notify()
|
final
void
|
notifyAll()
|
String
|
toString()
|
final
void
|
wait(long arg0, int arg1)
|
final
void
|
wait(long arg0)
|
final
void
|
wait()
|
Public Methods
public
Output<T>
asOutput
()
Returns the symbolic handle of a tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is
used to obtain a symbolic handle that represents the computation of the input.
Factory method to create a class wrapping a new ExtractVolumePatches operation.
Parameters
scope |
current scope |
input |
5-D Tensor with shape `[batch, in_planes, in_rows, in_cols, depth]`. |
ksizes |
The size of the sliding window for each dimension of `input`. |
strides |
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 |
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]
|
Returns
- a new instance of ExtractVolumePatches
public
Output<T>
patches
()
5-D Tensor with shape `[batch, out_planes, out_rows, out_cols,
ksize_planes * ksize_rows * ksize_cols * depth]` containing patches
with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized
in the "depth" dimension. Note `out_planes`, `out_rows` and `out_cols`
are the dimensions of the output patches.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2022-09-07 UTC.
[{
"type": "thumb-down",
"id": "missingTheInformationINeed",
"label":"Missing the information I need"
},{
"type": "thumb-down",
"id": "tooComplicatedTooManySteps",
"label":"Too complicated / too many steps"
},{
"type": "thumb-down",
"id": "outOfDate",
"label":"Out of date"
},{
"type": "thumb-down",
"id": "samplesCodeIssue",
"label":"Samples / code issue"
},{
"type": "thumb-down",
"id": "otherDown",
"label":"Other"
}]
[{
"type": "thumb-up",
"id": "easyToUnderstand",
"label":"Easy to understand"
},{
"type": "thumb-up",
"id": "solvedMyProblem",
"label":"Solved my problem"
},{
"type": "thumb-up",
"id": "otherUp",
"label":"Other"
}]
{"lastModified": "Last updated 2022-09-07 UTC."}
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-09-07 UTC."],[],[]]