CPU implementation of the cross entropy loss operation for neural networks. More...

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Public Types
using	MR = typename CpuDevice::MR
using	OperationBase = UnaryOperation<DeviceType::Cpu, int, float>
Public Types inherited from Mila::Dnn::Compute::UnaryOperation< DeviceType::Cpu, int, float >
using	MR
using	TensorInputType
using	TensorOutputType
Public Types inherited from Mila::Dnn::Compute::Operation< TDeviceType, TPrecision >
using	DataTypeTraits

Public Member Functions
	CpuCrossEntropyOp (const CrossEntropyConfig &config)
	Constructs a new CPU Cross Entropy operation with the default device context.
void	backward (const Tensor< int, MR > &input, const Tensor< float, MR > &output, const Tensor< float, MR > &output_gradient, const std::vector< std::shared_ptr< ITensor > > &parameters, std::vector< std::shared_ptr< Tensor< float, MR > > > &parameter_gradients, Tensor< int, MR > &input_gradient, const std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const
	Performs the backward pass of the cross entropy operation.
void	backward_impl (float dlogits, const float dlosses, const float *probs, const Tensor< int, CpuMemoryResource > &targets, int B, int T, int V, int Vp) const
	Helper method for the backward pass implementation.
void	forward (const Tensor< int, MR > &input, const std::vector< std::shared_ptr< ITensor > > &parameters, Tensor< float, MR > &output, std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const override
	Performs the forward pass of the cross entropy operation.
std::string	getName () const override
	Gets the name of this operation.
Public Member Functions inherited from Mila::Dnn::Compute::UnaryOperation< DeviceType::Cpu, int, float >
virtual	~UnaryOperation ()=default
virtual void	backward (const ITensor &input, const ITensor &output_grad, ITensor &input_grad) const=0
	Backward pass: compute gradient wrt input given output gradient.
virtual void	forward (const ITensor &input, ITensor &output) const=0
	Forward pass: compute output = f(input).
Public Member Functions inherited from Mila::Dnn::Compute::Operation< TDeviceType, TPrecision >
virtual	~Operation ()=default
virtual void	build (const BuildContext &build_context)
	Prepare the operation for a concrete input shape.
virtual void	clearGradients () noexcept
	Clear any cached gradient pointers held by the operation.
virtual TensorDataType	getDataType () const
	Tensor data type for this operation.
virtual DeviceType	getDeviceType () const
	Device type for this operation.
virtual OperationType	getOperationType () const=0
	Operation type identifier.
virtual std::size_t	getStateMemorySize () const
	Returns the number of bytes of state memory allocated by this operation.
virtual bool	isBuilt () const
	Whether build() completed successfully for a concrete input shape.
virtual bool	isEvalMode () const
	Query whether operation is configured for training.
virtual void	setGradients (ITensor weight_grad, ITensor bias_grad)
	Bind module-owned gradient tensors to the operation.
virtual void	setParameters (ITensor weight, ITensor bias)
	Bind module-owned parameter tensors to the operation.
virtual void	setTrainingMode (TrainingMode training_mode)
	Configure operation training-mode behavior.

Private Attributes
CrossEntropyConfig	config_
	Configuration for the CrossEntropy operation.

Additional Inherited Members
Static Public Attributes inherited from Mila::Dnn::Compute::Operation< TDeviceType, TPrecision >
static constexpr TensorDataType	data_type
static constexpr DeviceType	device_type
Static Protected Member Functions inherited from Mila::Dnn::Compute::UnaryOperation< DeviceType::Cpu, int, float >
static const TensorInputType &	asInputTensor (const ITensor &t)
static TensorOutputType &	asOutputTensor (ITensor &t)
Protected Attributes inherited from Mila::Dnn::Compute::Operation< TDeviceType, TPrecision >
bool	is_built_
TrainingMode	training_mode_

Detailed Description

CPU implementation of the cross entropy loss operation for neural networks.

This class provides a CPU-based implementation of the cross entropy loss function, which is commonly used in classification tasks. It computes the negative log likelihood of the correct class given the predicted probabilities.

Template Parameters

TInput	The data type of the input tensor elements (typically int for class indices).
TDataType	The data type used for computation and output (typically float).

Member Typedef Documentation

◆ MR

using Mila::Dnn::Compute::CpuCrossEntropyOp::MR = typename CpuDevice::MR

◆ OperationBase

using Mila::Dnn::Compute::CpuCrossEntropyOp::OperationBase = UnaryOperation<DeviceType::Cpu, int, float>

Constructor & Destructor Documentation

◆ CpuCrossEntropyOp()

Mila::Dnn::Compute::CpuCrossEntropyOp::CpuCrossEntropyOp ( const CrossEntropyConfig & config )

inline

Constructs a new CPU Cross Entropy operation with the default device context.

Initializes the operation with a CPU device context.

Member Function Documentation

◆ backward()

void Mila::Dnn::Compute::CpuCrossEntropyOp::backward	(	const Tensor< int, MR > &	input,
		const Tensor< float, MR > &	output,
		const Tensor< float, MR > &	output_gradient,
		const std::vector< std::shared_ptr< ITensor > > &	parameters,
		std::vector< std::shared_ptr< Tensor< float, MR > > > &	parameter_gradients,
		Tensor< int, MR > &	input_gradient,
		const std::vector< std::shared_ptr< Tensor< float, MR > > > &	output_state ) const

inline

Performs the backward pass of the cross entropy operation.

Computes gradients with respect to inputs and probabilities.

Parameters

input	Input tensor from the forward pass (target indices).
output	Output tensor from the forward pass (loss values).
output_gradient	Gradient of the loss with respect to the output.
parameters	Parameters tensor from forward pass (probabilities).
parameter_gradients	Gradients for parameters (probabilities).
input_gradient	Gradient of the loss with respect to the input (unused for integer targets).
attributes	Additional attributes for the operation.
output_state	Cache tensors from forward pass.

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◆ backward_impl()

void Mila::Dnn::Compute::CpuCrossEntropyOp::backward_impl	(	float *	dlogits,
		const float *	dlosses,
		const float *	probs,
		const Tensor< int, CpuMemoryResource > &	targets,
		int	B,
		int	T,
		int	V,
		int	Vp ) const

inline

Helper method for the backward pass implementation.

Computes gradients for the combined softmax and cross entropy operation.

Parameters

dlogits	Gradient buffer for logits/probabilities.
dlosses	Gradient buffer from output loss.
probs	Original probability values.
targets	Target class indices.
B	Batch size.
TDataType	Sequence length.
V	Vocabulary size (without padding).
Vp	Padded vocabulary size.

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◆ forward()

void Mila::Dnn::Compute::CpuCrossEntropyOp::forward	(	const Tensor< int, MR > &	input,
		const std::vector< std::shared_ptr< ITensor > > &	parameters,
		Tensor< float, MR > &	output,
		std::vector< std::shared_ptr< Tensor< float, MR > > > &	output_state ) const

inlineoverride

Performs the forward pass of the cross entropy operation.

Computes the negative log likelihood of the correct class for each sample.

Parameters

input	Input tensor containing target class indices of shape [B, TDataType].
parameters	Parameters tensor containing probabilities of shape [B, TDataType, V].
attributes	Additional attributes for the operation.
output	Output tensor to store the cross entropy losses of shape [B, TDataType].
output_state	Cache for storing intermediate results (used in backward pass).

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◆ getName()

std::string Mila::Dnn::Compute::CpuCrossEntropyOp::getName ( ) const

inlineoverridevirtual

Gets the name of this operation.

Returns: std::string The name of the operation ("Cpu::CrossEntropyOp").

Implements Mila::Dnn::Compute::Operation< TDeviceType, TPrecision >.

Member Data Documentation

◆ config_

CrossEntropyConfig Mila::Dnn::Compute::CpuCrossEntropyOp::config_

private

Configuration for the CrossEntropy operation.

The documentation for this class was generated from the following file:

/__w/Mila/Mila/Mila/Src/Dnn/Compute/Devices/Cpu/Operations/CpuCrossEntropyOp.ixx

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ MR

◆ OperationBase

Constructor & Destructor Documentation

◆ CpuCrossEntropyOp()

Member Function Documentation

◆ backward()

◆ backward_impl()

◆ forward()

◆ getName()

Member Data Documentation

◆ config_