@Namespace(value="tensorflow::ops") @NoOffset @Properties(inherit=tensorflow.class) public class QuantizedBatchNormWithGlobalNormalization extends Pointer
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_maxPointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
---|
QuantizedBatchNormWithGlobalNormalization(Pointer p)
Pointer cast constructor.
|
QuantizedBatchNormWithGlobalNormalization(Scope scope,
Input t,
Input t_min,
Input t_max,
Input m,
Input m_min,
Input m_max,
Input v,
Input v_min,
Input v_max,
Input beta,
Input beta_min,
Input beta_max,
Input gamma,
Input gamma_min,
Input gamma_max,
int out_type,
float variance_epsilon,
boolean scale_after_normalization) |
Modifier and Type | Method and Description |
---|---|
Operation |
operation() |
QuantizedBatchNormWithGlobalNormalization |
operation(Operation setter) |
Output |
result_max() |
QuantizedBatchNormWithGlobalNormalization |
result_max(Output setter) |
Output |
result_min() |
QuantizedBatchNormWithGlobalNormalization |
result_min(Output setter) |
Output |
result() |
QuantizedBatchNormWithGlobalNormalization |
result(Output setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public QuantizedBatchNormWithGlobalNormalization(Pointer p)
Pointer(Pointer)
.public QuantizedBatchNormWithGlobalNormalization(@Const @ByRef Scope scope, @ByVal Input t, @ByVal Input t_min, @ByVal Input t_max, @ByVal Input m, @ByVal Input m_min, @ByVal Input m_max, @ByVal Input v, @ByVal Input v_min, @ByVal Input v_max, @ByVal Input beta, @ByVal Input beta_min, @ByVal Input beta_max, @ByVal Input gamma, @ByVal Input gamma_min, @ByVal Input gamma_max, @Cast(value="tensorflow::DataType") int out_type, float variance_epsilon, @Cast(value="bool") boolean scale_after_normalization)
public QuantizedBatchNormWithGlobalNormalization operation(Operation setter)
public QuantizedBatchNormWithGlobalNormalization result(Output setter)
public QuantizedBatchNormWithGlobalNormalization result_min(Output setter)
public QuantizedBatchNormWithGlobalNormalization result_max(Output setter)
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