Mila
Deep Neural Network Library
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Mila::Dnn::Compute::CpuSoftmaxOp Class Referenceexport

CPU implementation of the softmax operation for neural networks. More...

Inheritance diagram for Mila::Dnn::Compute::CpuSoftmaxOp:
Collaboration diagram for Mila::Dnn::Compute::CpuSoftmaxOp:

Public Types

using MR = typename CpuDevice::MR
 
using OperationBase = UnaryOperation< DeviceType::Cpu, float >
 
- Public Types inherited from Mila::Dnn::Compute::UnaryOperation< DeviceType::Cpu, float >
using MR = std::conditional_t< TDeviceType==DeviceType::Cuda, CudaMemoryResource, HostMemoryResource >
 Memory resource type based on device type.
 

Public Member Functions

 CpuSoftmaxOp (const SoftmaxConfig &config)
 Constructs a new CPU Softmax operation with the default device context.
 
 CpuSoftmaxOp (std::shared_ptr< DeviceContext > context, const SoftmaxConfig &config)
 Constructs a new CPU Softmax operation with a specific device context.
 
void backward (const Tensor< float, MR > &input, const Tensor< float, MR > &output, const Tensor< float, MR > &output_gradient, const std::vector< std::shared_ptr< Tensor< float, MR > > > &parameters, std::vector< std::shared_ptr< Tensor< float, MR > > > &parameter_gradients, Tensor< float, MR > &input_gradient, const OperationAttributes &properties, const std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const
 Performs the backward pass of the softmax operation.
 
void forward (const Tensor< float, MR > &input, const std::vector< std::shared_ptr< Tensor< float, MR > > > &parameters, const OperationAttributes &properties, Tensor< float, MR > &output, std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const override
 Performs the forward pass of the softmax operation.
 
std::string getName () const override
 Gets the name of this operation.
 
- Public Member Functions inherited from Mila::Dnn::Compute::UnaryOperation< DeviceType::Cpu, float >
 UnaryOperation (OperationType operation_type)
 Constructs a UnaryOperation with the specified operation type.
 
 UnaryOperation (OperationType operation_type, std::shared_ptr< DeviceContext > context)
 Constructs a UnaryOperation with the specified operation type and device context.
 
virtual ~UnaryOperation ()=default
 Virtual destructor for proper cleanup of derived classes.
 
virtual void backward (const Tensor< float, MR > &grad, const std::vector< std::shared_ptr< Tensor< float, MR > > > &parameters, std::vector< std::shared_ptr< Tensor< float, MR > > > &output_grads) const
 Executes the backward pass of a unary operation.
 
virtual void backward (const Tensor< float, MR > &input, const Tensor< float, MR > &output_grad, const std::vector< std::shared_ptr< Tensor< float, MR > > > &parameters, std::vector< std::shared_ptr< Tensor< float, MR > > > &parameter_grads, Tensor< float, MR > &input_grad, const OperationAttributes &properties, const std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const
 Executes the comprehensive backward pass of a unary operation.
 
virtual void forward (const Tensor< float, MR > &input, const std::vector< std::shared_ptr< Tensor< float, MR > > > &parameters, const OperationAttributes &properties, Tensor< float, MR > &output, std::vector< std::shared_ptr< Tensor< float, MR > > > &output_state) const=0
 Executes the forward pass of a unary operation.
 
- Public Member Functions inherited from Mila::Dnn::Compute::OperationBase< TDeviceType, TInput1, TInput2, TOutput >
 OperationBase (OperationType operation_type, std::shared_ptr< DeviceContext > context)
 Constructs an OperationBase object with a specific device context and compute precision.
 
virtual ~OperationBase ()=default
 Virtual destructor for the OperationBase class.
 
std::shared_ptr< DeviceContextgetDeviceContext () const
 Gets the device context associated with this operation.
 
DeviceType getDeviceType () const
 Gets the device type for this operation.
 
OperationType getOperationType () const
 Gets the operation type enumeration value.
 

Private Attributes

SoftmaxConfig config_
 Configuration for the Softmax operation.
 

Detailed Description

CPU implementation of the softmax operation for neural networks.

This class provides a CPU-based implementation of the softmax operation, which converts a vector of real numbers into a probability distribution. The softmax function is commonly used in classification tasks as the final activation function of a neural network.

Template Parameters
TInputThe data type of the input tensor elements.
TDataTypeThe data type used for computation and output (defaults to the input type).

Member Typedef Documentation

◆ MR

◆ OperationBase

Constructor & Destructor Documentation

◆ CpuSoftmaxOp() [1/2]

Mila::Dnn::Compute::CpuSoftmaxOp::CpuSoftmaxOp ( const SoftmaxConfig config)
inline

Constructs a new CPU Softmax operation with the default device context.

Initializes the operation with a CPU device context.

◆ CpuSoftmaxOp() [2/2]

Mila::Dnn::Compute::CpuSoftmaxOp::CpuSoftmaxOp ( std::shared_ptr< DeviceContext context,
const SoftmaxConfig config 
)
inline

Constructs a new CPU Softmax operation with a specific device context.

Parameters
contextThe device context to use for this operation.
Exceptions
std::runtime_errorIf the context is not for a CPU device.

Member Function Documentation

◆ backward()

void Mila::Dnn::Compute::CpuSoftmaxOp::backward ( const Tensor< float, MR > &  input,
const Tensor< float, MR > &  output,
const Tensor< float, MR > &  output_gradient,
const std::vector< std::shared_ptr< Tensor< float, MR > > > &  parameters,
std::vector< std::shared_ptr< Tensor< float, MR > > > &  parameter_gradients,
Tensor< float, MR > &  input_gradient,
const OperationAttributes properties,
const std::vector< std::shared_ptr< Tensor< float, MR > > > &  output_state 
) const
inline

Performs the backward pass of the softmax operation.

Computes gradients with respect to inputs based on the output gradient. For softmax: dL/dx_i = ?_j (dL/dy_j * (y_i * (?_ij - y_j))) where ?_ij is the Kronecker delta.

Parameters
inputInput tensor from the forward pass.
outputOutput tensor from the forward pass (softmax probabilities).
output_gradientGradient of the loss with respect to the output.
parametersParameters used in forward pass (not used in this operation).
parameter_gradientsGradients for parameters (not used in this operation).
input_gradientGradient of the loss with respect to the input.
propertiesAdditional attributes for the operation.
output_stateCache tensors from forward pass.

◆ forward()

void Mila::Dnn::Compute::CpuSoftmaxOp::forward ( const Tensor< float, MR > &  input,
const std::vector< std::shared_ptr< Tensor< float, MR > > > &  parameters,
const OperationAttributes properties,
Tensor< float, MR > &  output,
std::vector< std::shared_ptr< Tensor< float, MR > > > &  output_state 
) const
inlineoverride

Performs the forward pass of the softmax operation.

Converts input logits into a probability distribution by taking the exponential of each element and normalizing by their sum.

Parameters
inputInput tensor containing logits.
parametersAdditional input parameters (not used in this operation).
propertiesAdditional attributes for the operation.
outputOutput tensor to store the resulting probability distribution.
output_stateCache for storing intermediate results (used in backward pass).
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◆ getName()

std::string Mila::Dnn::Compute::CpuSoftmaxOp::getName ( ) const
inlineoverridevirtual

Gets the name of this operation.

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

Implements Mila::Dnn::Compute::OperationBase< TDeviceType, TInput1, TInput2, TOutput >.

Member Data Documentation

◆ config_

SoftmaxConfig Mila::Dnn::Compute::CpuSoftmaxOp::config_
private

Configuration for the Softmax operation.


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