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FusedBatchNorm

public final class FusedBatchNorm

Batch normalization.

Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". The size of 1D Tensors matches the dimension C of the 4D Tensors.

Nested Classes

class FusedBatchNorm.Options Optional attributes for FusedBatchNorm

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <U>
batchMean ()
A 1D Tensor for the computed batch mean, to be used by TensorFlow to compute the running mean.
Output <U>
batchVariance ()
A 1D Tensor for the computed batch variance, to be used by TensorFlow to compute the running variance.
static <T extends TNumber , U extends TNumber > FusedBatchNorm <T, U>
create ( Scope scope, Operand <T> x, Operand <U> scale, Operand <U> offset, Operand <U> mean, Operand <U> variance, Options... options)
Factory method to create a class wrapping a new FusedBatchNorm operation.
static FusedBatchNorm.Options
dataFormat (String dataFormat)
static FusedBatchNorm.Options
epsilon (Float epsilon)
static FusedBatchNorm.Options
exponentialAvgFactor (Float exponentialAvgFactor)
static FusedBatchNorm.Options
isTraining (Boolean isTraining)
Output <U>
reserveSpace1 ()
A 1D Tensor for the computed batch mean, to be reused in the gradient computation.
Output <U>
reserveSpace2 ()
A 1D Tensor for the computed batch variance (inverted variance in the cuDNN case), to be reused in the gradient computation.
Output <U>
reserveSpace3 ()
A 1D Tensor for some intermediate results, to be reused in the gradient computation for better efficiency.
Output <T>
y ()
A 4D Tensor for output data.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "FusedBatchNormV3"

Public Methods

public Output <U> batchMean ()

A 1D Tensor for the computed batch mean, to be used by TensorFlow to compute the running mean.

public Output <U> batchVariance ()

A 1D Tensor for the computed batch variance, to be used by TensorFlow to compute the running variance.

public static FusedBatchNorm <T, U> create ( Scope scope, Operand <T> x, Operand <U> scale, Operand <U> offset, Operand <U> mean, Operand <U> variance, Options... options)

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

Parameters
scope current scope
x A 4D Tensor for input data.
scale A 1D Tensor for scaling factor, to scale the normalized x.
offset A 1D Tensor for offset, to shift to the normalized x.
mean A 1D Tensor for population mean. Used for inference only; must be empty for training.
variance A 1D Tensor for population variance. Used for inference only; must be empty for training.
options carries optional attributes values
Returns
  • a new instance of FusedBatchNorm

public static FusedBatchNorm.Options dataFormat (String dataFormat)

Parameters
dataFormat The data format for x and y. Either "NHWC" (default) or "NCHW".

public static FusedBatchNorm.Options epsilon (Float epsilon)

Parameters
epsilon A small float number added to the variance of x.

public static FusedBatchNorm.Options exponentialAvgFactor (Float exponentialAvgFactor)

public static FusedBatchNorm.Options isTraining (Boolean isTraining)

Parameters
isTraining A bool value to indicate the operation is for training (default) or inference.

public Output <U> reserveSpace1 ()

A 1D Tensor for the computed batch mean, to be reused in the gradient computation.

public Output <U> reserveSpace2 ()

A 1D Tensor for the computed batch variance (inverted variance in the cuDNN case), to be reused in the gradient computation.

public Output <U> reserveSpace3 ()

A 1D Tensor for some intermediate results, to be reused in the gradient computation for better efficiency.

public Output <T> y ()

A 4D Tensor for output data.