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MirrorPadGrad

public final class MirrorPadGrad

Gradient op for `MirrorPad` op. This op folds a mirror-padded tensor.

This operation folds the padded areas of `input` by `MirrorPad` according to the `paddings` you specify. `paddings` must be the same as `paddings` argument given to the corresponding `MirrorPad` op.

The folded size of each dimension D of the output is:

`input.dim_size(D) - paddings(D, 0) - paddings(D, 1)`

For example:

# 't' is [[1, 2, 3], [4, 5, 6], [7, 8, 9]].
 # 'paddings' is [[0, 1]], [0, 1]].
 # 'mode' is SYMMETRIC.
 # rank of 't' is 2.
 pad(t, paddings) ==> [[ 1,  5]
                       [11, 28]]
 

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of a tensor.
static <T, U extends Number> MirrorPadGrad<T>
create(Scope scope, Operand<T> input, Operand<U> paddings, String mode)
Factory method to create a class wrapping a new MirrorPadGrad operation.
Output<T>
output()
The folded tensor.

Inherited Methods

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.

public static MirrorPadGrad<T> create (Scope scope, Operand<T> input, Operand<U> paddings, String mode)

Factory method to create a class wrapping a new MirrorPadGrad operation.

Parameters
scope current scope
input The input tensor to be folded.
paddings A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of `input`.
mode The mode used in the `MirrorPad` op.
Returns
  • a new instance of MirrorPadGrad

public Output<T> output ()

The folded tensor.