org.bytedeco.javacpp

Class tensorflow.QuantizedBatchNormWithGlobalNormalization

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.QuantizedBatchNormWithGlobalNormalization

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

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

Quantized Batch normalization. This op is deprecated and will be removed in the future. Prefer tf.nn.batch_normalization. Arguments: * scope: A Scope object * t: A 4D input Tensor. * t_min: The value represented by the lowest quantized input. * t_max: 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. * m_min: The value represented by the lowest quantized mean. * m_max: 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. * v_min: The value represented by the lowest quantized variance. * v_max: 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. * beta_min: The value represented by the lowest quantized offset. * beta_max: 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. * gamma_min: The value represented by the lowest quantized gamma. * gamma_max: The value represented by the highest quantized gamma. * variance_epsilon: A small float number to avoid dividing by 0. * scale_after_normalization: A bool indicating whether the resulted tensor needs to be multiplied with gamma. Returns: * Output result * Output result_min * Output result_max

Nested Class Summary

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
QuantizedBatchNormWithGlobalNormalization(Pointer p) Pointer cast constructor.
QuantizedBatchNormWithGlobalNormalization(tensorflow.Scope scope, tensorflow.Input t, tensorflow.Input t_min, tensorflow.Input t_max, tensorflow.Input m, tensorflow.Input m_min, tensorflow.Input m_max, tensorflow.Input v, tensorflow.Input v_min, tensorflow.Input v_max, tensorflow.Input beta, tensorflow.Input beta_min, tensorflow.Input beta_max, tensorflow.Input gamma, tensorflow.Input gamma_min, tensorflow.Input gamma_max, int out_type, float variance_epsilon, boolean scale_after_normalization)

Method Summary

Modifier and Type	Method and Description
tensorflow.Operation	operation()
tensorflow.QuantizedBatchNormWithGlobalNormalization	operation(tensorflow.Operation operation)
tensorflow.Output	result_max()
tensorflow.QuantizedBatchNormWithGlobalNormalization	result_max(tensorflow.Output result_max)
tensorflow.Output	result_min()
tensorflow.QuantizedBatchNormWithGlobalNormalization	result_min(tensorflow.Output result_min)
tensorflow.Output	result()
tensorflow.QuantizedBatchNormWithGlobalNormalization	result(tensorflow.Output result)

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

QuantizedBatchNormWithGlobalNormalization

public QuantizedBatchNormWithGlobalNormalization(Pointer p)

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

QuantizedBatchNormWithGlobalNormalization

public QuantizedBatchNormWithGlobalNormalization(@Const @ByRef
                                                 tensorflow.Scope scope,
                                                 @ByVal
                                                 tensorflow.Input t,
                                                 @ByVal
                                                 tensorflow.Input t_min,
                                                 @ByVal
                                                 tensorflow.Input t_max,
                                                 @ByVal
                                                 tensorflow.Input m,
                                                 @ByVal
                                                 tensorflow.Input m_min,
                                                 @ByVal
                                                 tensorflow.Input m_max,
                                                 @ByVal
                                                 tensorflow.Input v,
                                                 @ByVal
                                                 tensorflow.Input v_min,
                                                 @ByVal
                                                 tensorflow.Input v_max,
                                                 @ByVal
                                                 tensorflow.Input beta,
                                                 @ByVal
                                                 tensorflow.Input beta_min,
                                                 @ByVal
                                                 tensorflow.Input beta_max,
                                                 @ByVal
                                                 tensorflow.Input gamma,
                                                 @ByVal
                                                 tensorflow.Input gamma_min,
                                                 @ByVal
                                                 tensorflow.Input gamma_max,
                                                 @Cast(value="tensorflow::DataType")
                                                 int out_type,
                                                 float variance_epsilon,
                                                 @Cast(value="bool")
                                                 boolean scale_after_normalization)

Method Detail

operation

@ByRef
public tensorflow.Operation operation()

operation

public tensorflow.QuantizedBatchNormWithGlobalNormalization operation(tensorflow.Operation operation)

result

@ByRef
public tensorflow.Output result()

result

public tensorflow.QuantizedBatchNormWithGlobalNormalization result(tensorflow.Output result)

result_min

@ByRef
public tensorflow.Output result_min()

result_min

public tensorflow.QuantizedBatchNormWithGlobalNormalization result_min(tensorflow.Output result_min)

result_max

@ByRef
public tensorflow.Output result_max()

result_max

public tensorflow.QuantizedBatchNormWithGlobalNormalization result_max(tensorflow.Output result_max)