org.tensorflow.op.core

Class CropAndResizeGradBoxes

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.CropAndResizeGradBoxes

All Implemented Interfaces:

Op, Operand<Float>

@Operator
public final class CropAndResizeGradBoxes
extends PrimitiveOp
implements Operand<Float>

Computes the gradient of the crop_and_resize op wrt the input boxes tensor.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CropAndResizeGradBoxes.Options Optional attributes for CropAndResizeGradBoxes

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<Float>	asOutput() Returns the symbolic handle of a tensor.
static <T extends Number> CropAndResizeGradBoxes	create(Scope scope, Operand<Float> grads, Operand<T> image, Operand<Float> boxes, Operand<Integer> boxInd, CropAndResizeGradBoxes.Options... options) Factory method to create a class to wrap a new CropAndResizeGradBoxes operation to the graph.
static CropAndResizeGradBoxes.Options	method(String method)
Output<Float>	output() A 2-D tensor of shape `[num_boxes, 4]`.

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> CropAndResizeGradBoxes create(Scope scope,
                                                               Operand<Float> grads,
                                                               Operand<T> image,
                                                               Operand<Float> boxes,
                                                               Operand<Integer> boxInd,
                                                               CropAndResizeGradBoxes.Options... options)

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

Parameters:

scope - current graph scope

grads - A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.

image - A 4-D tensor of shape `[batch, image_height, image_width, depth]`. Both `image_height` and `image_width` need to be positive.

boxes - A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensor specifies the coordinates of a box in the `box_ind[i]` image and is specified in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of `y` is mapped to the image coordinate at `y * (image_height - 1)`, so as the `[0, 1]` interval of normalized image height is mapped to `[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the `[0, 1]` range are allowed, in which case we use `extrapolation_value` to extrapolate the input image values.

boxInd - A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`. The value of `box_ind[i]` specifies the image that the `i`-th box refers to.

options - carries optional attributes values

Returns:

a new instance of CropAndResizeGradBoxes

method

public static CropAndResizeGradBoxes.Options method(String method)

Parameters:

method - A string specifying the interpolation method. Only 'bilinear' is supported for now.

output

public Output<Float> output()

A 2-D tensor of shape `[num_boxes, 4]`.

asOutput

public Output<Float> 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<Float>

See Also:

OperationBuilder.addInput(Output)