Dnn.Modules.CrossEntropy Module Reference

Exported Modules
module	Compute.OperationAttributes
module	Compute.DeviceContext
module	Compute.CudaMemoryResource
module	Compute.MemoryResource
module	Compute.DeviceType
module	Dnn.Module
module	Dnn.Tensor
module	Dnn.TensorHelpers
module	Dnn.TensorTraits
module	Compute.OperationRegistry
module	Compute.Precision
module	Compute.CpuMemoryResource
module	Compute.OperationBase
module	Compute.UnaryOperation
module	Serialization.ModelArchive
module	Compute.ComputeDevice

Classes
class	Mila::Dnn::CrossEntropy< TDeviceType, TLogits, TTargets >
	CrossEntropy loss module for neural networks. More...
class	Mila::Dnn::CrossEntropyConfig
	Configuration class for CrossEntropy module. More...

Typedefs
template<typename TLogits = float, typename TTargets = int>
using	Mila::Dnn::CpuCrossEntropy = CrossEntropy< DeviceType::Cpu, TLogits, TTargets >
	Type alias for CPU-based cross entropy module with customizable tensor types.
template<typename TLogits = float, typename TTargets = int>
using	Mila::Dnn::CudaCrossEntropy = CrossEntropy< DeviceType::Cuda, TLogits, TTargets >
	Type alias for CUDA-based cross entropy module with customizable tensor types.
using	ModuleBase = Module< TDeviceType, TLogits, TTargets >
	Alias for base module type.
using	MR = std::conditional_t< TDeviceType==DeviceType::Cuda, CudaMemoryResource, CpuMemoryResource >
	Memory resource type used for tensors, selected based on device type.

Functions
	CrossEntropy (const std::string &device_name, const CrossEntropyConfig &config)
	Constructs a new CrossEntropy module with a device name.
	CrossEntropy (std::shared_ptr< DeviceContext > device_context, const CrossEntropyConfig &config)
	Constructs a new CrossEntropy module with a provided device context.
void	backward (const Tensor< TLogits, MR > &input, const Tensor< TTargets, MR > &targets, const Tensor< TLogits, MR > &output_grad, Tensor< TLogits, MR > &input_grad)
	Calculates gradients for the backward pass.
void	createOperation ()
	Creates the appropriate cross entropy operation for the current device.
void	forward (const Tensor< TLogits, MR > &input, const Tensor< TTargets, MR > &targets, Tensor< TLogits, MR > &output)
	Performs the forward pass of the cross entropy operation.
std::shared_ptr< Tensor< TLogits, MR > >	getClassWeights () const
	Gets the class weights tensor.
float	getLabelSmoothing () const
	Gets the label smoothing factor.
int64_t	getPaddingIndex () const
	Gets the padding index.
int64_t	getVocabSize () const
	Gets the vocabulary size.
bool	ignorePadding () const
	Checks if padding is ignored.
void	initializeClassWeights (const std::vector< float > &weights)
	Initializes the class weights tensor from a vector of weights.
bool	isReduced () const
	Checks if loss is reduced.
void	load (ModelArchive &archive) override
	Deserializes the module state from a ZIP archive.
size_t	parameterCount () const override
	Gets the number of trainable parameters in this module.
void	save (ModelArchive &archive) const override
	Serializes the module state to a ZIP archive.
std::string	toString () const override
	Generates a string representation of this module's configuration.

Variables
OperationAttributes	attributes_
	Operation attributes and configuration.
std::shared_ptr< Tensor< TLogits, MR > >	class_weights_ { nullptr }
	Optional tensor containing weights for each class.
CrossEntropyConfig	config_
	Configuration for the CrossEntropy module.
std::shared_ptr< UnaryOperation< TDeviceType, TLogits, TTargets > >	operation_ { nullptr }
	The operation that implements the cross entropy calculation.
std::vector< std::shared_ptr< Tensor< TLogits, MR > > >	output_state_
	Collection of output state tensors for caching.
std::vector< std::shared_ptr< Tensor< TLogits, MR > > >	parameters_
	Collection of parameters for this module.

Files
file	/home/runner/work/Mila/Mila/Mila/Src/Dnn/Modules/Losses/CrossEntropy.ixx
	Implementation of the CrossEntropy loss function module.
file	/home/runner/work/Mila/Mila/Mila/Src/Dnn/Modules/Losses/CrossEntropyConfig.ixx
	Configuration interface for the CrossEntropy module in the Mila DNN framework.