OperatorProperty is a object that stores all information about Operator. It also contains method to generate context(device) specific operators. More...

#include <operator.h>

Collaboration diagram for mxnet::OperatorProperty:

Public Member Functions
virtual	~OperatorProperty ()
	virtual destructor More...

virtual void	Init (const std::vector< std::pair< std::string, std::string > > &kwargs)=0
	Initialize the Operator by setting the parameters This function need to be called before all other functions. More...

virtual std::map< std::string, std::string >	GetParams () const =0
	Get a map representation of internal parameters. This can be used by Init to recover the state of OperatorProperty. More...

virtual std::vector< std::string >	ListArguments () const
	Get input arguments of the Operator. More...

virtual std::vector< std::string >	ListOutputs () const
	Get name of output values of Operator. More...

virtual std::vector< std::string >	ListAuxiliaryStates () const
	Get name of auxiliary states of Operator. More...

virtual int	NumOutputs () const

virtual int	NumVisibleOutputs () const
	get number of visible return values during Symbol creation. If NumVisibleOutputs() = k, and NumOutputs() = n. The first k returns will be presented in the resulting symbol. More...

virtual bool	InferShape (mxnet::ShapeVector in_shape, mxnet::ShapeVector out_shape, mxnet::ShapeVector *aux_shape) const =0
	infer the shapes of outputs and unknown input arguments More...

virtual bool	InferType (std::vector< int > in_type, std::vector< int > out_type, std::vector< int > *aux_type) const
	infer the data types of outputs and unknown input arguments More...

virtual OperatorProperty *	Copy () const =0
	Copy this OperatorProperty. More...

virtual Operator *	CreateOperator (Context ctx) const =0
	Create a Operator on specific context. More...

virtual Operator *	CreateOperatorEx (Context ctx, mxnet::ShapeVector in_shape, std::vector< int > in_type) const
	Create a Operator on specific context and input shape/type. More...

virtual std::string	TypeString () const =0
	return the type string of the Operator subclasses override this function. More...

virtual std::vector< ResourceRequest >	ForwardResource (const mxnet::ShapeVector &in_shape) const
	Declare additional resource required in forward pass. These additional resources will be presented in OpContext.requested in the same order of the returned Resource. More...

virtual std::vector< ResourceRequest >	BackwardResource (const mxnet::ShapeVector &in_shape) const
	Declare additional resource required in backward pass. These additional resources will be presented in OpContext.requested in the same order of the returned Resource. More...

virtual std::vector< int >	DeclareBackwardDependency (const std::vector< int > &out_grad, const std::vector< int > &in_data, const std::vector< int > &out_data) const
	Declare the input requirement of Backward pass. More...

virtual std::vector< std::pair< int, void * > >	ForwardInplaceOption (const std::vector< int > &in_data, const std::vector< void * > &out_data) const
	Get possible forward inplace options. This function enables optimization to reuse memory of inputs in output. Only override when necessary, by default in-place is disabled. More...

virtual std::vector< std::pair< int, void * > >	BackwardInplaceOption (const std::vector< int > &out_grad, const std::vector< int > &in_data, const std::vector< int > &out_data, const std::vector< void * > &in_grad) const
	Get possible backward inplace options. This function enables optimization to reuse memory of inputs in output. Only override when necessary, by default in-place is disabled. More...

template<typename T >
std::vector< T >	BackwardInputs (const std::vector< T > &out_grad, const std::vector< T > &in_data, const std::vector< T > &out_data) const
	Get Backward Input Dependency for generic types of data. Normally T can be pointer of Symbol::DataEntry, or NDArray. This function will select the result list of T according to DeclareBackwardDependency. More...

virtual ExecType	exec_type () const

Static Public Member Functions
static OperatorProperty *	Create (const char *type_name)
	create OperatorProperty More...

Detailed Description

OperatorProperty is a object that stores all information about Operator. It also contains method to generate context(device) specific operators.

It also contains various functions that can be optimally overriden to provide optimization chance for computation engine.

Constructor & Destructor Documentation

virtual mxnet::OperatorProperty::~OperatorProperty ( )

inlinevirtual

virtual destructor

Member Function Documentation

virtual std::vector<std::pair<int, void*> > mxnet::OperatorProperty::BackwardInplaceOption	(	const std::vector< int > &	out_grad,
		const std::vector< int > &	in_data,
		const std::vector< int > &	out_data,
		const std::vector< void * > &	in_grad
	)		const

inlinevirtual

Get possible backward inplace options. This function enables optimization to reuse memory of inputs in output. Only override when necessary, by default in-place is disabled.

The reason for void* type in the in_grad is to distinguish the order of mappings between the two, compiler will report error when in_data and out_data's order in the pair get reversed.

// The following code says in_grad[0] can share data with in_data[0]
vector<pair<int,int> > BackwardInplaceOption(
 const std::vector<int> &out_grad,
 const std::vector<int> &in_data,
 const std::vector<int> &out_data,
 const std::vector<int> &in_grad) const {
 return {in_data[0], in_grad[0]}};
}

Parameters

in_data	The input data in forward pass.
out_data	The output data in forward pass.
in_grad	Gradient of inputs in backward pass.
out_grad	Gradient of outputs in backward pass.

Returns: list of pair of that maps input->output, indicating possible in place operations.

template<typename T >

std::vector<T> mxnet::OperatorProperty::BackwardInputs	(	const std::vector< T > &	out_grad,
		const std::vector< T > &	in_data,
		const std::vector< T > &	out_data
	)		const

inline

Get Backward Input Dependency for generic types of data. Normally T can be pointer of Symbol::DataEntry, or NDArray. This function will select the result list of T according to DeclareBackwardDependency.

Parameters

in_data	the input data in forward pass.
out_data	the output data in forward pass.
out_grad	gradient of outputs in backward pass.

Template Parameters

T	the generic type parameter.

Returns: vector of inputs the Backward Operation depends on.

See also: DeclareBackwardDependency

virtual std::vector<ResourceRequest> mxnet::OperatorProperty::BackwardResource ( const mxnet::ShapeVector & in_shape ) const

inlinevirtual

Declare additional resource required in backward pass. These additional resources will be presented in OpContext.requested in the same order of the returned Resource.

Parameters

in_shape The input shape to the operator, corresponds to shapes of in_data.

Returns: Additional resource request

virtual OperatorProperty* mxnet::OperatorProperty::Copy ( ) const

pure virtual

Copy this OperatorProperty.

Returns: a pointer to the copied OperatorProperty

static OperatorProperty* mxnet::OperatorProperty::Create ( const char * type_name )

static

create OperatorProperty

Parameters

type_name the type string of the OperatorProperty

Returns: a new constructed OperatorProperty

virtual Operator* mxnet::OperatorProperty::CreateOperator ( Context ctx ) const

pure virtual

Create a Operator on specific context.

virtual Operator* mxnet::OperatorProperty::CreateOperatorEx	(	Context	ctx,
		mxnet::ShapeVector *	in_shape,
		std::vector< int > *	in_type
	)		const

inlinevirtual

Create a Operator on specific context and input shape/type.

Parameters

ctx	context of this operator
in_shape	shape of the input ndarrays
in_type	dtype of the input ndarrays

Returns: the created operator

virtual std::vector<int> mxnet::OperatorProperty::DeclareBackwardDependency	(	const std::vector< int > &	out_grad,
		const std::vector< int > &	in_data,
		const std::vector< int > &	out_data
	)		const

inlinevirtual

Declare the input requirement of Backward pass.

Only the returned list of variables will be used in Backward. This function is used for memory optimization. It is advised to override and only return what is actually needed. If this function is not overriden, all the variables will be valid in Backward.

// The following code declares Backward need out_grad[0], in_data[0],in_data[1]
vector<int> BackwardInputs(const vector<int> &out_grad,
 const vector<int> &in_data,
 const vector<int> &out_data) const {
 return {out_grad[0], in_data[0], in_data[1]};
}

Parameters

out_grad	gradient of outputs in backward pass.
in_data	the input data in forward pass.
out_data	the output data in forward pass.

Returns: an integer vector indicating the input requirments

See also: BackwardInputs

virtual ExecType mxnet::OperatorProperty::exec_type ( ) const

inlinevirtual

Returns: execution type of the operator

virtual std::vector<std::pair<int, void*> > mxnet::OperatorProperty::ForwardInplaceOption	(	const std::vector< int > &	in_data,
		const std::vector< void * > &	out_data
	)		const

inlinevirtual

Get possible forward inplace options. This function enables optimization to reuse memory of inputs in output. Only override when necessary, by default in-place is disabled.

The reason for void* type in the out_data is to distinguish the order of mappings between the two, compiler will report error when in_data and out_data's order in the pair get reversed.

// The following code says out_data[0] can share data with in_data[0]
vector<pair<int, void*> > ForwardInplaceOption(const vector<int> &in_data,
 const vector<void*> &out_data) const {
 return {{in_data[0], out_data[0]}};
}

Parameters

in_data	The input data in forward pass.
out_data	The output data in forward pass.

Returns: list of pair of that maps input->output, indicating possible in place operations.

virtual std::vector<ResourceRequest> mxnet::OperatorProperty::ForwardResource ( const mxnet::ShapeVector & in_shape ) const

inlinevirtual

Declare additional resource required in forward pass. These additional resources will be presented in OpContext.requested in the same order of the returned Resource.

Parameters

in_shape The input shape to the operator, corresponds to shapes of in_data.

Returns: Additional resource request

virtual std::map<std::string, std::string> mxnet::OperatorProperty::GetParams ( ) const

pure virtual

Get a map representation of internal parameters. This can be used by Init to recover the state of OperatorProperty.

virtual bool mxnet::OperatorProperty::InferShape	(	mxnet::ShapeVector *	in_shape,
		mxnet::ShapeVector *	out_shape,
		mxnet::ShapeVector *	aux_shape
	)		const

pure virtual

infer the shapes of outputs and unknown input arguments

Parameters

in_shape the shape of input arguments of the operator this should be of same length as the vector returned by DescribeArgs in_shape allows unknown elements, which are checked by shape.ndim() == 0. For unknown shapes, InferShape will try to fill in the correct Shape in in_shape For known shapes, InferShape will check shape consistency

common practice: set the shape of data input, and usually weight's shape can be inferred

Parameters

out_shape	the shape of outputs of the operator InferShape will modify the vector to fill output mxnet::TShape
aux_shape	the shape of auxiliary states of the operator InferShape will modify the vector to fill output mxnet::TShape

Returns: true if the shape inference is successful, false if there is not enough information.

Exceptions

dmlc::Error if the known arg_shapes are inconsistent.

virtual bool mxnet::OperatorProperty::InferType	(	std::vector< int > *	in_type,
		std::vector< int > *	out_type,
		std::vector< int > *	aux_type
	)		const

inlinevirtual

infer the data types of outputs and unknown input arguments

Parameters

in_type the type of input arguments of the operator this should be of same length as the vector returned by DescribeArgs in_type allows unknown elements, which are checked by type.ndim() == 0. For unknown types, Infertype will try to fill in the correct type in in_type For known types, Infertype will check type consistency

common practice: set the type of data input, and usually weight's type can be inferred

Parameters

out_type	the type of outputs of the operator Infertype will modify the vector to fill output Ttype
aux_type	the type of auxiliary states of the operator Infertype will modify the vector to fill output Ttype

Returns: true if the type inference is successful, false if there is not enough information.

Exceptions

dmlc::Error if the known arg_types are inconsistent.

virtual void mxnet::OperatorProperty::Init ( const std::vector< std::pair< std::string, std::string > > & kwargs )

pure virtual

Initialize the Operator by setting the parameters This function need to be called before all other functions.

Parameters

kwargs the keyword arguments parameters

virtual std::vector<std::string> mxnet::OperatorProperty::ListArguments ( ) const

inlinevirtual

Get input arguments of the Operator.

Returns: vector of arguments.

virtual std::vector<std::string> mxnet::OperatorProperty::ListAuxiliaryStates ( ) const

inlinevirtual

Get name of auxiliary states of Operator.

Returns: name of return values.

virtual std::vector<std::string> mxnet::OperatorProperty::ListOutputs ( ) const

inlinevirtual

Get name of output values of Operator.

Returns: name of output values.

virtual int mxnet::OperatorProperty::NumOutputs ( ) const

inlinevirtual

Returns: number of real return values of the Operator

virtual int mxnet::OperatorProperty::NumVisibleOutputs ( ) const

inlinevirtual

get number of visible return values during Symbol creation. If NumVisibleOutputs() = k, and NumOutputs() = n. The first k returns will be presented in the resulting symbol.

The rest of the returns can be used for auxiliary states for Backward. For example, Dropout will return [data, mask], with NumVisibleOutputs() == 1. So when user call sym = Dropout(input), only data is presented in sym. But all the returns will be presented in out_data parameter of Backward if requested.

Returns: number of default return values

virtual std::string mxnet::OperatorProperty::TypeString ( ) const

pure virtual

return the type string of the Operator subclasses override this function.

Returns: The type string.

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

include/mxnet/operator.h

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation