org.bytedeco.pytorch

Class LayerNormImpl

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.pytorch.Module

org.bytedeco.pytorch.LayerNormImplCloneable

org.bytedeco.pytorch.LayerNormImpl

All Implemented Interfaces:

AutoCloseable

@Namespace(value="torch::nn")
 @NoOffset
 @Properties(inherit=torch.class)
public class LayerNormImpl
extends LayerNormImplCloneable

Applies Layer Normalization over a mini-batch of inputs as described in the paper Layer Normalization_ . See https://pytorch.org/docs/master/nn.html#torch.nn.LayerNorm to learn about the exact behavior of this module. See the documentation for torch::nn::LayerNormOptions class to learn what constructor arguments are supported for this module. Example:

  LayerNorm model(LayerNormOptions({2,
  2}).elementwise_affine(false).eps(2e-5));
  

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
LayerNormImpl(LayerNormOptions options_)
LayerNormImpl(LongVector normalized_shape)
LayerNormImpl(Module pointer) Downcast constructor.
LayerNormImpl(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
Tensor	bias() The learned bias.
LayerNormImpl	bias(Tensor setter)
Tensor	forward(Tensor input) Applies layer normalization over a mini-batch of inputs as described in the paper Layer Normalization_ .
LayerNormOptions	options() The options with which this module was constructed.
LayerNormImpl	options(LayerNormOptions setter)
void	pretty_print(Pointer stream) Pretty prints the LayerNorm module into the given stream.
void	reset_parameters()
void	reset() reset() must perform initialization of all members with reference semantics, most importantly parameters, buffers and submodules.
Tensor	weight() The learned weight.
LayerNormImpl	weight(Tensor setter)

Methods inherited from class org.bytedeco.pytorch.LayerNormImplCloneable

asModule, asModule, clone, clone

Methods inherited from class org.bytedeco.pytorch.Module

apply, apply, apply, apply, apply, apply, apply, apply, buffers, buffers, children, eval, is_serializable, is_training, load, modules, modules, name, named_buffers, named_buffers, named_children, named_modules, named_modules, named_modules, named_parameters, named_parameters, parameters, parameters, register_buffer, register_buffer, register_module, register_module, register_parameter, register_parameter, register_parameter, register_parameter, save, shiftLeft, to, to, to, train, unregister_module, unregister_module, zero_grad

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, 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

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

LayerNormImpl

public LayerNormImpl(Pointer p)

Pointer cast constructor. Invokes Pointer(Pointer).

LayerNormImpl

public LayerNormImpl(Module pointer)

Downcast constructor.

LayerNormImpl

public LayerNormImpl(@ByVal @Cast(value="std::vector<int64_t>*")
                     LongVector normalized_shape)

LayerNormImpl

public LayerNormImpl(@ByVal
                     LayerNormOptions options_)

Method Detail

reset

public void reset()

Description copied from class: LayerNormImplCloneable

reset() must perform initialization of all members with reference semantics, most importantly parameters, buffers and submodules.

Overrides:

reset in class LayerNormImplCloneable

reset_parameters

public void reset_parameters()

pretty_print

public void pretty_print(@Cast(value="std::ostream*") @ByRef
                         Pointer stream)

Pretty prints the LayerNorm module into the given stream.

Overrides:

pretty_print in class Module

forward

@ByVal
public Tensor forward(@Const @ByRef
                             Tensor input)

Applies layer normalization over a mini-batch of inputs as described in the paper Layer Normalization_ . The mean and standard-deviation are calculated separately over the last certain number dimensions which have to be of the shape specified by input normalized_shape. Layer Normalization: https://arxiv.org/abs/1607.06450

options

@ByRef
public LayerNormOptions options()

The options with which this module was constructed.

options

public LayerNormImpl options(LayerNormOptions setter)

weight

@ByRef
public Tensor weight()

The learned weight. Initialized to ones if the elementwise_affine option is set to true upon construction.

weight

public LayerNormImpl weight(Tensor setter)

bias

@ByRef
public Tensor bias()

The learned bias. Initialized to zeros elementwise_affine option is set to true upon construction.

bias

public LayerNormImpl bias(Tensor setter)