QuantizedBatchNormWithGlobalNormalization

public final class QuantizedBatchNormWithGlobalNormalization

Quantized Batch normalization.

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

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

static <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNormalization<U>	create(Scope scope, Operand<T> t, Operand<TFloat32> tMin, Operand<TFloat32> tMax, Operand<T> m, Operand<TFloat32> mMin, Operand<TFloat32> mMax, Operand<T> v, Operand<TFloat32> vMin, Operand<TFloat32> vMax, Operand<T> beta, Operand<TFloat32> betaMin, Operand<TFloat32> betaMax, Operand<T> gamma, Operand<TFloat32> gammaMin, Operand<TFloat32> gammaMax, Class<U> outType, Float varianceEpsilon, Boolean scaleAfterNormalization) Factory method to create a class wrapping a new QuantizedBatchNormWithGlobalNormalization operation.
Output<U>	result()
Output<TFloat32>	resultMax()
Output<TFloat32>	resultMin()

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

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

Constant Value: "QuantizedBatchNormWithGlobalNormalization"

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

scope	current 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.
varianceEpsilon	A small float number to avoid dividing by 0.
scaleAfterNormalization	A bool indicating whether the resulted tensor needs to be multiplied with gamma.