Namespaces
	cuda
	common utils for cuda

	helper
	Helper functions.

	random

Classes
struct	csr_idx_check
	Indices should be non-negative, less than the number of columns and in ascending order per row. More...

struct	csr_indptr_check
	IndPtr should be non-negative, in non-decreasing order, start with 0 and end with value equal with size of indices. More...

class	LazyAllocArray

class	ObjectPool
	Object pool for fast allocation and deallocation. More...

struct	ObjectPoolAllocatable
	Helper trait class for easy allocation and deallocation. More...

struct	rsp_idx_check
	Indices of RSPNDArray should be non-negative, less than the size of first dimension and in ascending order. More...

struct	StaticArray
	Static array. This code is borrowed from struct Shape<ndim>, except that users can specify the type of the elements of the statically allocated array. The object instance of the struct is copyable between CPU and GPU. More...

Typedefs
typedef std::mt19937	RANDOM_ENGINE
	Random Engine. More...

Functions
bool	SetupDefaultBlobsIn (const std::vector< NDArray > &src, const std::vector< NDArray > bufs, std::vector< TBlob > blobs, std::vector< NDArray > temp_src, std::vector< NDArray > temp_dst, std::unordered_map< uint32_t, uint32_t > *idx_map)

bool	SetupDefaultBlobsOut (const std::vector< NDArray > &src, const std::vector< NDArray > bufs, std::vector< OpReqType > req, std::vector< TBlob > blobs, std::vector< NDArray > temp_src, std::vector< NDArray > *temp_dst)

void	SetupDefaultBlobsInOut (const std::vector< NDArray > &ndinputs, const std::vector< NDArray > &ndoutputs, const std::vector< NDArray > in_bufs, const std::vector< NDArray > out_bufs, std::vector< OpReqType > req, std::vector< TBlob > input_blobs, std::vector< TBlob > output_blobs, std::vector< NDArray > pre_temp_src, std::vector< NDArray > pre_temp_dst, std::vector< NDArray > post_temp_src, std::vector< NDArray > post_temp_dst, std::unordered_map< uint32_t, uint32_t > in_temp_idx_map, const std::vector< uint32_t > &mutate_idx)

void	CastNonDefaultStorage (const std::vector< NDArray > &src, const std::vector< NDArray > &dst, const OpContext &ctx, const bool is_gpu)

bool	SameType (const nnvm::NodeAttrs &attrs, std::vector< int > iattr, std::vector< int > oattr)
	The default type inference function, which assigns all undefined types to the same type of one of the inputs or outputs. More...

bool	DefaultStorageType (const nnvm::NodeAttrs &attrs, const int dev_mask, DispatchMode dispatch_mode, std::vector< int > iattr, std::vector< int > *oattr)
	The default storage type inference function, which assigns all undefined storage types to kDefaultStorage. If all of input and output storage types are kDefaultStorage, DispatchMode::kFCompute is assigned to dispatch_mode. Otherwise, DispatchMode::kFComputeFallback is assigned to dispatch_mode. More...

template<typename xpu >
void	CheckFormatWrapper (const RunContext &rctx, const NDArray &input, const TBlob &err_cpu, const bool full_check)

template<typename xpu >
void	CheckFormatCSRImpl (const RunContext &rctx, const NDArray &input, const TBlob &err_cpu, const bool full_check)
	Check the validity of CSRNDArray. More...

template<typename xpu >
void	CheckFormatRSPImpl (const RunContext &rctx, const NDArray &input, const TBlob &err_cpu, const bool full_check)
	Check the validity of RowSparseNDArray. More...

template<typename xpu >
void	CheckFormatImpl (const RunContext &rctx, const NDArray &input, const TBlob &err_cpu, const bool full_check)

template<typename xpu >
void	SparseRetainOpForwardRspWrapper (mshadow::Stream< xpu > s, const NDArray &input_nd, const TBlob &idx_data, const OpReqType req, NDArray output_nd)
	Pick rows specified by user input index array from a row sparse ndarray and save them in the output sparse ndarray. More...

template<typename xpu >
void	CastStorageDispatch (const OpContext &ctx, const NDArray &input, const NDArray &output)

bool	ContainsOnlyStorage (const StorageTypeVector &vstorage, const NDArrayStorageType stype)
	returns true if all storage types in `vstorage` are the same as target `stype`. false is returned for empty inputs. More...

bool	ContainsOnlyStorage (const StorageTypeVector &vstorage, const NDArrayStorageType stype1, const NDArrayStorageType stype2, bool *has_both)
	returns true if all storage types in `vstorage` are the same as target `stype1` or `stype2'. Sets boolean if both found. false is returned for empty inputs. More...

bool	ContainsOnlyStorage (const std::vector< NDArray > &ndarrays, const NDArrayStorageType stype)
	returns true if the storage types of arrays in `ndarrays` are the same as target `stype`. false is returned for empty inputs. More...

bool	ContainsOnlyStorage (const std::vector< NDArray > &ndarrays, const NDArrayStorageType stype1, const NDArrayStorageType stype2, bool *has_both)
	returns true if the storage types of arrays in `ndarrays` are the same as targets `stype1` or `stype2`. false is returned for empty inputs. More...

std::string	dispatch_mode_string (const DispatchMode x)
	get string representation of dispatch_mode More...

std::string	stype_string (const int x)
	get string representation of storage_type More...

std::string	dev_type_string (const int dev_type)
	get string representation of device type More...

std::string	operator_stype_string (const nnvm::NodeAttrs &attrs, const int dev_mask, const std::vector< int > &in_attrs, const std::vector< int > &out_attrs)
	get string representation of the operator stypes More...

std::string	operator_string (const nnvm::NodeAttrs &attrs, const OpContext &ctx, const std::vector< NDArray > &inputs, const std::vector< OpReqType > &req, const std::vector< NDArray > &outputs)
	get string representation of the operator More...

void	LogOnce (const std::string &message)
	log message once. Intended for storage fallback warning messages. More...

void	LogStorageFallback (const nnvm::NodeAttrs &attrs, const int dev_mask, const std::vector< int > in_attrs, const std::vector< int > out_attrs)
	log storage fallback event More...

int	GetNumThreadsPerGPU ()

int	GetExecNumMatchColor ()

template<typename T , typename V >
V	ParallelAccumulate (const T *a, const int n, V start)

template<typename RandomIt , typename Compare >
void	ParallelSortHelper (RandomIt first, size_t len, size_t grainsize, const Compare &comp)
	Helper function for ParallelSort. DO NOT call this function directly. Use the interface ParallelSort instead. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h. More...

template<typename RandomIt , typename Compare >
void	ParallelSort (RandomIt first, RandomIt last, size_t num_threads, Compare comp)
	Sort the elements in the range [first, last) into the ascending order defined by the comparator comp. If the length of the range [first, last) is greater than a certain threshold, the range will be recursively divided into two and assign two threads to sort each half range. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h. More...

template<typename RandomIt >
void	ParallelSort (RandomIt first, RandomIt last, size_t num_threads)
	Sort the elements in the range [first, last) into ascending order. The elements are compared using the default < operator. If the length of the range [first, last) is greater than a certain threshold, the range will be recursively divided into two and assign two threads to sort each half range. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h. More...

template<class T , class... Args>
helper::UniqueIf< T >::SingleObject	MakeUnique (Args &&...args)
	Constructs an object of type `T` and wraps it in a `std::unique_ptr`. More...

template<class T >
helper::UniqueIf< T >::UnknownBound	MakeUnique (size_t n)
	Constructs an object of type `T` and wraps it in a `std::unique_ptr`. More...

template<class T , class... Args>
helper::UniqueIf< T >::KnownBound	MakeUnique (Args &&...args)=delete
	Constructs an object of type `T` and wraps it in a `std::unique_ptr`. More...

template<typename FCompType >
FCompType	GetFCompute (const nnvm::Op *op, const std::string &name, const Context &ctx)

Typedef Documentation

typedef std::mt19937 mxnet::common::RANDOM_ENGINE

Random Engine.

Function Documentation

void mxnet::common::CastNonDefaultStorage	(	const std::vector< NDArray > &	src,
		const std::vector< NDArray > &	dst,
		const OpContext &	ctx,
		const bool	is_gpu
	)

inline

template<typename xpu >

void mxnet::common::CastStorageDispatch	(	const OpContext &	ctx,
		const NDArray &	input,
		const NDArray &	output
	)

template<typename xpu >

void mxnet::common::CheckFormatCSRImpl	(	const RunContext &	rctx,
		const NDArray &	input,
		const TBlob &	err_cpu,
		const bool	full_check
	)

Check the validity of CSRNDArray.

Parameters

rctx	Execution context.
input	Input NDArray of CSRStorage.
err_cpu	Error number on cpu.
full_check	If true, rigorous check, O(N) operations, otherwise basic check, O(1) operations.

template<typename xpu >

void mxnet::common::CheckFormatImpl	(	const RunContext &	rctx,
		const NDArray &	input,
		const TBlob &	err_cpu,
		const bool	full_check
	)

template<typename xpu >

void mxnet::common::CheckFormatRSPImpl	(	const RunContext &	rctx,
		const NDArray &	input,
		const TBlob &	err_cpu,
		const bool	full_check
	)

Check the validity of RowSparseNDArray.

Parameters

rctx	Execution context.
input	Input NDArray of RowSparseStorage.
err_cpu	Error number on cpu.
full_check	If true, rigorous check, O(N) operations, otherwise basic check, O(1) operations.

template<typename xpu >

void mxnet::common::CheckFormatWrapper	(	const RunContext &	rctx,
		const NDArray &	input,
		const TBlob &	err_cpu,
		const bool	full_check
	)

bool mxnet::common::ContainsOnlyStorage	(	const StorageTypeVector &	vstorage,
		const NDArrayStorageType	stype
	)

inline

returns true if all storage types in vstorage are the same as target stype. false is returned for empty inputs.

bool mxnet::common::ContainsOnlyStorage	(	const StorageTypeVector &	vstorage,
		const NDArrayStorageType	stype1,
		const NDArrayStorageType	stype2,
		bool *	has_both
	)

inline

returns true if all storage types in vstorage are the same as target stype1 or `stype2'. Sets boolean if both found. false is returned for empty inputs.

bool mxnet::common::ContainsOnlyStorage	(	const std::vector< NDArray > &	ndarrays,
		const NDArrayStorageType	stype
	)

inline

returns true if the storage types of arrays in ndarrays are the same as target stype. false is returned for empty inputs.

bool mxnet::common::ContainsOnlyStorage	(	const std::vector< NDArray > &	ndarrays,
		const NDArrayStorageType	stype1,
		const NDArrayStorageType	stype2,
		bool *	has_both
	)

inline

returns true if the storage types of arrays in ndarrays are the same as targets stype1 or stype2. false is returned for empty inputs.

bool mxnet::common::DefaultStorageType	(	const nnvm::NodeAttrs &	attrs,
		const int	dev_mask,
		DispatchMode *	dispatch_mode,
		std::vector< int > *	iattr,
		std::vector< int > *	oattr
	)

inline

The default storage type inference function, which assigns all undefined storage types to kDefaultStorage. If all of input and output storage types are kDefaultStorage, DispatchMode::kFCompute is assigned to dispatch_mode. Otherwise, DispatchMode::kFComputeFallback is assigned to dispatch_mode.

std::string mxnet::common::dev_type_string ( const int dev_type )

inline

get string representation of device type

std::string mxnet::common::dispatch_mode_string ( const DispatchMode x )

inline

get string representation of dispatch_mode

int mxnet::common::GetExecNumMatchColor ( )

inline

template<typename FCompType >

FCompType mxnet::common::GetFCompute	(	const nnvm::Op *	op,
		const std::string &	name,
		const Context &	ctx
	)

int mxnet::common::GetNumThreadsPerGPU ( )

inline

void mxnet::common::LogOnce ( const std::string & message )

inline

log message once. Intended for storage fallback warning messages.

void mxnet::common::LogStorageFallback	(	const nnvm::NodeAttrs &	attrs,
		const int	dev_mask,
		const std::vector< int > *	in_attrs,
		const std::vector< int > *	out_attrs
	)

inline

log storage fallback event

template<class T , class... Args>

helper::UniqueIf<T>::SingleObject mxnet::common::MakeUnique ( Args &&... args )

delete

Constructs an object of type T and wraps it in a std::unique_ptr.

Parameters

args	List of arguments with which an instance of `T` will be constructed.

Returns: std::unique_ptr of an instance of type T.

Constructs a non-array type T. The arguments args are passed to the constructor of T. The function does not participate in the overload resolution if T is an array type.

template<class T >

helper::UniqueIf<T>::UnknownBound mxnet::common::MakeUnique ( size_t n )

Constructs an object of type T and wraps it in a std::unique_ptr.

Parameters

n	The size of the array to construct.

Returns: std::unique_ptr of an instance of type T.

Constructs an array of unknown bound T. The function does not participate in the overload resolution unless T is an array of unknown bound.

template<class T , class... Args>

helper::UniqueIf<T>::KnownBound mxnet::common::MakeUnique ( Args &&... args )

delete

Constructs an object of type T and wraps it in a std::unique_ptr.

Parameters

args	List of arguments with which an instance of `T` will be constructed.

Constructs an arrays of known bound is disallowed.

Parameters

args	List of arguments with which an instance of `T` will be constructed.

Returns: std::unique_ptr of an instance of type T.

Constructs a non-array type T. The arguments args are passed to the constructor of T. The function does not participate in the overload resolution if T is an array type.

std::string mxnet::common::operator_string	(	const nnvm::NodeAttrs &	attrs,
		const OpContext &	ctx,
		const std::vector< NDArray > &	inputs,
		const std::vector< OpReqType > &	req,
		const std::vector< NDArray > &	outputs
	)

inline

get string representation of the operator

std::string mxnet::common::operator_stype_string	(	const nnvm::NodeAttrs &	attrs,
		const int	dev_mask,
		const std::vector< int > &	in_attrs,
		const std::vector< int > &	out_attrs
	)

inline

get string representation of the operator stypes

template<typename T , typename V >

V mxnet::common::ParallelAccumulate	(	const T *	a,
		const int	n,
		V	start
	)

template<typename RandomIt , typename Compare >

void mxnet::common::ParallelSort	(	RandomIt	first,
		RandomIt	last,
		size_t	num_threads,
		Compare	comp
	)

Sort the elements in the range [first, last) into the ascending order defined by the comparator comp. If the length of the range [first, last) is greater than a certain threshold, the range will be recursively divided into two and assign two threads to sort each half range. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h.

template<typename RandomIt >

void mxnet::common::ParallelSort	(	RandomIt	first,
		RandomIt	last,
		size_t	num_threads
	)

Sort the elements in the range [first, last) into ascending order. The elements are compared using the default < operator. If the length of the range [first, last) is greater than a certain threshold, the range will be recursively divided into two and assign two threads to sort each half range. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h.

template<typename RandomIt , typename Compare >

void mxnet::common::ParallelSortHelper	(	RandomIt	first,
		size_t	len,
		size_t	grainsize,
		const Compare &	comp
	)

Helper function for ParallelSort. DO NOT call this function directly. Use the interface ParallelSort instead. Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h.

bool mxnet::common::SameType	(	const nnvm::NodeAttrs &	attrs,
		std::vector< int > *	iattr,
		std::vector< int > *	oattr
	)

inline

The default type inference function, which assigns all undefined types to the same type of one of the inputs or outputs.

bool mxnet::common::SetupDefaultBlobsIn	(	const std::vector< NDArray > &	src,
		const std::vector< NDArray > *	bufs,
		std::vector< TBlob > *	blobs,
		std::vector< NDArray > *	temp_src,
		std::vector< NDArray > *	temp_dst,
		std::unordered_map< uint32_t, uint32_t > *	idx_map
	)

inline

void mxnet::common::SetupDefaultBlobsInOut	(	const std::vector< NDArray > &	ndinputs,
		const std::vector< NDArray > &	ndoutputs,
		const std::vector< NDArray > *	in_bufs,
		const std::vector< NDArray > *	out_bufs,
		std::vector< OpReqType > *	req,
		std::vector< TBlob > *	input_blobs,
		std::vector< TBlob > *	output_blobs,
		std::vector< NDArray > *	pre_temp_src,
		std::vector< NDArray > *	pre_temp_dst,
		std::vector< NDArray > *	post_temp_src,
		std::vector< NDArray > *	post_temp_dst,
		std::unordered_map< uint32_t, uint32_t > *	in_temp_idx_map,
		const std::vector< uint32_t > &	mutate_idx
	)

inline

bool mxnet::common::SetupDefaultBlobsOut	(	const std::vector< NDArray > &	src,
		const std::vector< NDArray > *	bufs,
		std::vector< OpReqType > *	req,
		std::vector< TBlob > *	blobs,
		std::vector< NDArray > *	temp_src,
		std::vector< NDArray > *	temp_dst
	)

inline

template<typename xpu >

void mxnet::common::SparseRetainOpForwardRspWrapper	(	mshadow::Stream< xpu > *	s,
		const NDArray &	input_nd,
		const TBlob &	idx_data,
		const OpReqType	req,
		NDArray *	output_nd
	)

Pick rows specified by user input index array from a row sparse ndarray and save them in the output sparse ndarray.

std::string mxnet::common::stype_string ( const int x )

inline

get string representation of storage_type

Namespaces

Classes

Typedefs

Functions

Typedef Documentation

Function Documentation