org.tensorflow.op.core

Class ExtractImagePatches<T extends Number>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.ExtractImagePatches<T>

Type Parameters:

T - data type for patches() output

All Implemented Interfaces:

Op, Operand<T>

@Operator
public final class ExtractImagePatches<T extends Number>
extends PrimitiveOp
implements Operand<T>

Extract `patches` from `images` and put them in the "depth" output dimension.

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<T>	asOutput() Returns the symbolic handle of a tensor.
static <T extends Number> ExtractImagePatches<T>	create(Scope scope, Operand<T> images, List<Long> ksizes, List<Long> strides, List<Long> rates, String padding) Factory method to create a class to wrap a new ExtractImagePatches operation to the graph.
Output<T>	patches() 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows * ksize_cols * depth]` containing image patches with size `ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension.

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

create

public static <T extends Number> ExtractImagePatches<T> create(Scope scope,
                                                               Operand<T> images,
                                                               List<Long> ksizes,
                                                               List<Long> strides,
                                                               List<Long> rates,
                                                               String padding)

Factory method to create a class to wrap a new ExtractImagePatches operation to the graph.

Parameters:

scope - current graph scope

images - 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.

ksizes - The size of the sliding window for each dimension of `images`.

strides - 1-D of length 4. How far the centers of two consecutive patches are in the images. Must be: `[1, stride_rows, stride_cols, 1]`.

rates - 1-D of length 4. Must be: `[1, rate_rows, rate_cols, 1]`. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with `patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)`, followed by subsampling them spatially by a factor of `rates`. This is equivalent to `rate` in dilated (a.k.a. Atrous) convolutions.

padding - The type of padding algorithm to use.

We specify the size-related attributes as:

       ksizes = [1, ksize_rows, ksize_cols, 1]
       strides = [1, strides_rows, strides_cols, 1]
       rates = [1, rates_rows, rates_cols, 1]
 

Returns:

a new instance of ExtractImagePatches

patches

public Output<T> patches()

4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows * ksize_cols * depth]` containing image patches with size `ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension. Note `out_rows` and `out_cols` are the dimensions of the output patches.

asOutput

public Output<T> asOutput()

Description copied from interface: Operand

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.

Specified by:

asOutput in interface Operand<T extends Number>

See Also:

OperationBuilder.addInput(Output)