org.tensorflow.op.core

Class QuantizedBatchNormWithGlobalNormalization<U>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.QuantizedBatchNormWithGlobalNormalization<U>

Type Parameters:

U - data type for result() output

All Implemented Interfaces:

Op

@Operator
public final class QuantizedBatchNormWithGlobalNormalization<U>
extends PrimitiveOp

Quantized Batch normalization.

This op is deprecated and will be removed in the future. Prefer `tf.nn.batch_normalization`.

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
static <U,T> QuantizedBatchNormWithGlobalNormalization<U>	create(Scope scope, Operand<T> t, Operand<Float> tMin, Operand<Float> tMax, Operand<T> m, Operand<Float> mMin, Operand<Float> mMax, Operand<T> v, Operand<Float> vMin, Operand<Float> vMax, Operand<T> beta, Operand<Float> betaMin, Operand<Float> betaMax, Operand<T> gamma, Operand<Float> gammaMin, Operand<Float> gammaMax, Class<U> outType, Float varianceEpsilon, Boolean scaleAfterNormalization) Factory method to create a class to wrap a new QuantizedBatchNormWithGlobalNormalization operation to the graph.
Output<U>	result()
Output<Float>	resultMax()
Output<Float>	resultMin()

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 <U,T> QuantizedBatchNormWithGlobalNormalization<U> create(Scope scope,
                                                                        Operand<T> t,
                                                                        Operand<Float> tMin,
                                                                        Operand<Float> tMax,
                                                                        Operand<T> m,
                                                                        Operand<Float> mMin,
                                                                        Operand<Float> mMax,
                                                                        Operand<T> v,
                                                                        Operand<Float> vMin,
                                                                        Operand<Float> vMax,
                                                                        Operand<T> beta,
                                                                        Operand<Float> betaMin,
                                                                        Operand<Float> betaMax,
                                                                        Operand<T> gamma,
                                                                        Operand<Float> gammaMin,
                                                                        Operand<Float> gammaMax,
                                                                        Class<U> outType,
                                                                        Float varianceEpsilon,
                                                                        Boolean scaleAfterNormalization)

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

Parameters:

scope - current graph scope

t - A 4D input Tensor.

tMin - The value represented by the lowest quantized input.

tMax - The value represented by the highest quantized input.

m - A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof.

mMin - The value represented by the lowest quantized mean.

mMax - The value represented by the highest quantized mean.

v - A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof.

vMin - The value represented by the lowest quantized variance.

vMax - The value represented by the highest quantized variance.

beta - A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor.

betaMin - The value represented by the lowest quantized offset.

betaMax - The value represented by the highest quantized offset.

gamma - A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor.

gammaMin - The value represented by the lowest quantized gamma.

gammaMax - The value represented by the highest quantized gamma.

outType -

varianceEpsilon - A small float number to avoid dividing by 0.

scaleAfterNormalization - A bool indicating whether the resulted tensor needs to be multiplied with gamma.

Returns:

a new instance of QuantizedBatchNormWithGlobalNormalization

result

public Output<U> result()

resultMin

public Output<Float> resultMin()

resultMax

public Output<Float> resultMax()