org.bytedeco.javacpp

Class tensorflow.CropAndResizeGradImage

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.CropAndResizeGradImage

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

@Namespace(value="tensorflow::ops")
 @NoOffset
public static class tensorflow.CropAndResizeGradImage
extends Pointer

Computes the gradient of the crop_and_resize op wrt the input image tensor. Arguments: * scope: A Scope object * grads: A 4-D tensor of shape [num_boxes, crop_height, crop_width, depth]. * 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_valueto extrapolate the input image values. * box_ind: 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. * image_size: A 1-D tensor with value [batch, image_height, image_width, depth]containing the original image size. Both image_heightand image_widthneed to be positive. Optional attributes (see Attrs): * method: A string specifying the interpolation method. Only 'bilinear' is supported for now. Returns: * Output: A 4-D tensor of shape [batch, image_height, image_width, depth]{@code .

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	tensorflow.CropAndResizeGradImage.Attrs Optional attribute setters for CropAndResizeGradImage

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
CropAndResizeGradImage(Pointer p) Pointer cast constructor.
CropAndResizeGradImage(tensorflow.Scope scope, tensorflow.Input grads, tensorflow.Input boxes, tensorflow.Input box_ind, tensorflow.Input image_size, int T)
CropAndResizeGradImage(tensorflow.Scope scope, tensorflow.Input grads, tensorflow.Input boxes, tensorflow.Input box_ind, tensorflow.Input image_size, int T, tensorflow.CropAndResizeGradImage.Attrs attrs)

Method Summary

Modifier and Type	Method and Description
tensorflow.Input	asInput()
tensorflow.Output	asOutput()
static tensorflow.CropAndResizeGradImage.Attrs	Method(BytePointer x)
static tensorflow.CropAndResizeGradImage.Attrs	Method(String x)
tensorflow.Node	node()
tensorflow.Operation	operation()
tensorflow.CropAndResizeGradImage	operation(tensorflow.Operation operation)
tensorflow.Output	output()
tensorflow.CropAndResizeGradImage	output(tensorflow.Output output)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

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

Constructor Detail

CropAndResizeGradImage

public CropAndResizeGradImage(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

CropAndResizeGradImage

public CropAndResizeGradImage(@Const @ByRef
                              tensorflow.Scope scope,
                              @ByVal
                              tensorflow.Input grads,
                              @ByVal
                              tensorflow.Input boxes,
                              @ByVal
                              tensorflow.Input box_ind,
                              @ByVal
                              tensorflow.Input image_size,
                              @Cast(value="tensorflow::DataType")
                              int T)

CropAndResizeGradImage

public CropAndResizeGradImage(@Const @ByRef
                              tensorflow.Scope scope,
                              @ByVal
                              tensorflow.Input grads,
                              @ByVal
                              tensorflow.Input boxes,
                              @ByVal
                              tensorflow.Input box_ind,
                              @ByVal
                              tensorflow.Input image_size,
                              @Cast(value="tensorflow::DataType")
                              int T,
                              @Const @ByRef
                              tensorflow.CropAndResizeGradImage.Attrs attrs)

Method Detail

asOutput

@ByVal
 @Name(value="operator tensorflow::Output")
public tensorflow.Output asOutput()

asInput

@ByVal
 @Name(value="operator tensorflow::Input")
public tensorflow.Input asInput()

node

public tensorflow.Node node()

Method

@ByVal
public static tensorflow.CropAndResizeGradImage.Attrs Method(@tensorflow.StringPiece
                                                                     BytePointer x)

Method

@ByVal
public static tensorflow.CropAndResizeGradImage.Attrs Method(@tensorflow.StringPiece
                                                                     String x)

operation

@ByRef
public tensorflow.Operation operation()

operation

public tensorflow.CropAndResizeGradImage operation(tensorflow.Operation operation)

output

@ByRef
public tensorflow.Output output()

output

public tensorflow.CropAndResizeGradImage output(tensorflow.Output output)