Inheritance diagram for dlprim::InnerProduct:

Public Member Functions
	InnerProduct (Context &ctx, InnerProductConfig const &cfg)

virtual char const *	operator_type () const
	name of the operator type

void	initialize_params (std::vector< Tensor > &parameters, ExecutionContext const &e)
	Set default parameters iniitalization.

virtual void	setup (std::vector< TensorSpecs > const &in, std::vector< TensorSpecs > &out, std::vector< TensorSpecs > &parameters, size_t &workspace)
	Convigure operator. More...

virtual void	reshape (std::vector< Shape > const &in, std::vector< Shape > &out, size_t &ws)
	Reshape layer according to new input size. More...

virtual void	forward (std::vector< Tensor > &input, std::vector< Tensor > &output, std::vector< Tensor > &parameters, Tensor &workspace, ExecutionContext const &ctx)
	Enqueue forward propogation computations. More...

virtual void	backward (std::vector< TensorAndGradient > &input, std::vector< TensorAndGradient > &output, std::vector< TensorAndGradient > &parameters, Tensor &workspace, ExecutionContext const &ctx)
	Enqueue backward propogation computations. More...

Public Member Functions inherited from dlprim::Operator
	Operator (Context const &ctx)
	Create operator for specific context (device/platform)

SharedResource &	shared_resource ()
	Getter for object that is shared between operators accross the net, for example random numbers generator.

void	shared_resource (std::shared_ptr< SharedResource > r)
	Setter of the shared resource.

virtual void	mode (CalculationsMode mode)
	Can be called with both train and predict before setup() is called. afterwards if original mode was train - it can be switched to predict and back but if original mode was predict it can't be switched to train. More...

virtual CalculationsMode	mode ()
	get current mode

	Operator (Operator const &)=delete
	operator non-copyable/moveable More...

void	operator= (Operator const &)=delete

	Operator (Operator &&)=delete

void	operator= (Operator &&)=delete

virtual bool	alias_generator ()
	returns true of the operator is alias - generation - it only changes the shape of tensor but not its content it actually does not perform any operation but only changes semantics, in this casse input and output are aliases of each other

Protected Member Functions
void	forward_cpu (Tensor &in, Tensor &out, Tensor &M, Tensor *bias)

void	backward_filter_cpu (Tensor &dy, Tensor &x, Tensor &dM, float factor)

void	backward_data_cpu (Tensor &dy, Tensor &dx, Tensor &M, float factor)

Protected Attributes
InnerProductConfig	config_

DataType	dtype_

std::unique_ptr< core::IPForward >	ip_

std::unique_ptr< core::IPBackwardData >	bwd_ip_

std::unique_ptr< core::IPBackwardFilter >	bwd_weights_ip_

std::unique_ptr< Operator >	activation_

std::unique_ptr< BWBias >	bwd_bias_

Protected Attributes inherited from dlprim::Operator
Context	ctx_
	OpenCL/CPU Context to work with.

CalculationsMode	mode_
	computaions mode

std::shared_ptr< SharedResource >	shared_resource_

Member Function Documentation

virtual void dlprim::InnerProduct::backward	(	std::vector< TensorAndGradient > &	,
		std::vector< TensorAndGradient > &	,
		std::vector< TensorAndGradient > &	,
		Tensor &	,
		ExecutionContext const &
	)

virtual

Enqueue backward propogation computations.

Parameters

input	- inputs and their gradients marked for computatins
output	- outputs and their gradients
parameters	- parameters parameters and their gradients
workspace	- workspace as required
ctx	- execution context

Note: actual inputs are

inputs[index].data
outputs[index].data
outputs[index].diff
parameters[index].data

And it computes in backpropogation

inputs[index].diff
parameters[index].diff

If computation is not needed TensorAndGradient::requires_gradient need to be set to false

Reimplemented from dlprim::Operator.

virtual void dlprim::InnerProduct::forward	(	std::vector< Tensor > &	input,
		std::vector< Tensor > &	output,
		std::vector< Tensor > &	parameters,
		Tensor &	workspace,
		ExecutionContext const &	ctx
	)

virtual

Enqueue forward propogation computations.

Parameters

input	- input tesnosrs (X)
output	- output tesnors (Y)
parameters	- parameters for computation
workspace	- workspace as required
ctx	- execution context

Implements dlprim::Operator.

virtual void dlprim::InnerProduct::reshape	(	std::vector< Shape > const &	in,
		std::vector< Shape > &	out,
		size_t &	workspace
	)

virtual

Reshape layer according to new input size.

Parameters

in	- new input tensor sizes
out	- new output tesor sizes
workspace	- new workspace size needed

Implements dlprim::Operator.

virtual void dlprim::InnerProduct::setup	(	std::vector< TensorSpecs > const &	in,
		std::vector< TensorSpecs > &	out,
		std::vector< TensorSpecs > &	parameters,
		size_t &	workspace
	)

virtual

Convigure operator.

Parameters

in	- a list of expected input tensors
out	- a list of output tensots - that opertor calculates in fwd propogation
parameters	- a list of parameters need for computation. If parameter should not participate in gradient desend it should be marked as not trainable
workspace	size needed for computations in bytes - not preserved between different calls

Implements dlprim::Operator.

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

include/dlprim/ops/inner_product.hpp

Public Member Functions

Protected Member Functions

Protected Attributes

Member Function Documentation