neml2::utils Namespace Reference

Functions
template<>
bool	parse_ (bool &val, const std::string &raw_str)
template<>
bool	parse_vector_ (std::vector< bool > &vals, const std::string &raw_str)
template<>
bool	parse_ (VariableName &val, const std::string &raw_str)
template<>
bool	parse_ (TensorShape &val, const std::string &raw_str)
template<>
Device	parse (const std::string &raw_str)
template<>
bool	parse_ (Device &val, const std::string &raw_str)
TraceableTensorShape	extract_batch_sizes (const ATensor &tensor, Size batch_dim)
	Extract the batch shape of a tensor given batch dimension The extracted batch shape will be traceable.
std::shared_ptr< jit::Graph >	last_executed_optimized_graph ()
	Print last evaluated optimized graph.
std::string	demangle (const char *name)
	Demangle a piece of cxx abi type information.
std::string	join (const std::vector< std::string > &strs, const std::string &delim)
std::vector< std::string >	split (const std::string &str, const std::string &delims)
std::string	trim (const std::string &str, const std::string &white_space)
bool	start_with (std::string_view str, std::string_view prefix)
bool	end_with (std::string_view str, std::string_view suffix)
Size	storage_size (TensorShapeRef shape)
	The flattened storage size of a tensor with given shape.
TensorShape	pad_prepend (TensorShapeRef s, Size dim, Size pad=1)
	Pad shape s to dimension dim by prepending sizes of pad.
ATensor	pad_prepend (const ATensor &s, Size dim, Size pad)
TraceableTensorShape	broadcast_batch_sizes (const std::vector< Tensor > &tensors)
	Find the broadcast batch shape of all the tensors The returned batch shape will be traceable.
template<typename T >
std::string	parse_failure_message (const std::string &raw_str)
template<typename T >
bool	parse_ (T &val, const std::string &raw_str)
template<typename T >
T	parse (const std::string &raw_str)
template<typename T >
bool	parse_vector_ (std::vector< T > &vals, const std::string &raw_str)
template<typename T >
std::vector< T >	parse_vector (const std::string &raw_str)
template<typename T >
bool	parse_vector_vector_ (std::vector< std::vector< T > > &vals, const std::string &raw_str)
template<typename T >
std::vector< std::vector< T > >	parse_vector_vector (const std::string &raw_str)
template<>
bool	parse_< bool > (bool &, const std::string &raw_str)
template<>
bool	parse_vector_< bool > (std::vector< bool > &, const std::string &raw_str)
	This special one is for the evil std::vector<bool>!
template<>
bool	parse_< TensorShape > (TensorShape &, const std::string &raw_str)
template<>
bool	parse_< VariableName > (VariableName &, const std::string &raw_str)
template<>
Device	parse< Device > (const std::string &raw_str)
template<>
bool	parse_< Device > (Device &, const std::string &raw_str)
template<typename... S>
TraceableTensorShape	add_traceable_shapes (const S &... shape)
template<typename T , typename... Args>
void	stream_all (std::ostringstream &ss, T &&val, Args &&... args)
template<typename T >
std::string	stringify (const T &t)
template<>
std::string	stringify (const bool &t)
template<class... T>
bool	broadcastable (const T &... tensors)
template<class... T>
bool	batch_broadcastable (const T &... tensors)
template<class... T>
bool	base_broadcastable (const T &... tensors)
template<class... T>
Size	broadcast_batch_dim (const T &...)
	The batch dimension after broadcasting.
template<class... T>
bool	sizes_same (T &&... shapes)
	Check if all shapes are the same.
template<class... T>
bool	sizes_broadcastable (const T &... shapes)
	Check if the shapes are broadcastable.
template<class... T>
TensorShape	broadcast_sizes (const T &... shapes)
	Return the broadcast shape of all the shapes.
template<typename... S>
TensorShape	add_shapes (const S &...)
template<class... T>
Size	broadcast_batch_dim (const T &... tensor)
template<typename... S>
TensorShape	add_shapes (const S &... shape)

Function Documentation

add_shapes() [1/2]

template<typename... S>

TensorShape add_shapes

(

const S &...

shape

)

add_shapes() [2/2]

template<typename... S>

TensorShape add_shapes

(

const S &

...

)

add_traceable_shapes()

template<typename... S>

TraceableTensorShape add_traceable_shapes

(

const S &...

shape

)

base_broadcastable()

template<class... T>

bool base_broadcastable

(

const T &...

tensors

)

Test if the tensors are base-broadcastable.

See also

sizes_broadcastable

batch_broadcastable()

template<class... T>

bool batch_broadcastable

(

const T &...

tensors

)

Test if the tensors are batch-broadcastable.

See also

sizes_broadcastable

broadcast_batch_dim() [1/2]

template<class... T>

Size broadcast_batch_dim

(

const T &...

tensor

)

broadcast_batch_dim() [2/2]

template<class... T>

Size broadcast_batch_dim

(

const T &

...

)

The batch dimension after broadcasting.

This should be as simple as the maximum batch_dim() among all arguments.

broadcast_batch_sizes()

TraceableTensorShape broadcast_batch_sizes

(

const std::vector< Tensor > &

tensors

)

Find the broadcast batch shape of all the tensors The returned batch shape will be traceable.

See also

neml2::TraceableTensorShape

Pre-pad ones to the shapes

Braodcast

broadcast_sizes()

template<class... T>

TensorShape broadcast_sizes

(

const T &...

shapes

)

Return the broadcast shape of all the shapes.

broadcastable()

template<class... T>

bool broadcastable

(

const T &...

tensors

)

Two tensors are said to be broadcastable if

1. Base shapes are the same
2. Batch shapes are broadcastable (see sizes_broadcastable)

demangle()

std::string demangle

(

const char *

name

)

Demangle a piece of cxx abi type information.

end_with()

bool end_with	(	std::string_view	str,
		std::string_view	suffix )

extract_batch_sizes()

TraceableTensorShape extract_batch_sizes	(	const ATensor &	tensor,
		Size	batch_dim )

Extract the batch shape of a tensor given batch dimension The extracted batch shape will be traceable.

See also

neml2::TraceableTensorShape

join()

std::string join	(	const std::vector< std::string > &	strs,
		const std::string &	delim )

last_executed_optimized_graph()

std::shared_ptr< jit::Graph > last_executed_optimized_graph

(

)

Print last evaluated optimized graph.

pad_prepend() [1/2]

ATensor pad_prepend	(	const ATensor &	s,
		Size	dim,
		Size	pad )

pad_prepend() [2/2]

TensorShape pad_prepend	(	TensorShapeRef	s,
		Size	dim,
		Size	pad = 1 )

Pad shape s to dimension dim by prepending sizes of pad.

Parameters

s	The original shape to pad
dim	The resulting dimension
pad	The values used to pad the shape, default to 1

Returns

TensorShape The padded shape with dimension dim

parse() [1/2]

template<typename T >

T parse

(

const std::string &

raw_str

)

parse() [2/2]

template<>

Device parse

(

const std::string &

raw_str

)

parse< Device >()

template<>

Device parse< Device >

(

const std::string &

raw_str

)

parse_() [1/5]

template<>

bool parse_	(	bool &	val,
		const std::string &	raw_str )

parse_() [2/5]

template<>

bool parse_	(	Device &	val,
		const std::string &	raw_str )

parse_() [3/5]

template<typename T >

bool parse_	(	T &	val,
		const std::string &	raw_str )

parse_() [4/5]

template<>

bool parse_	(	TensorShape &	val,
		const std::string &	raw_str )

parse_() [5/5]

template<>

bool parse_	(	VariableName &	val,
		const std::string &	raw_str )

parse_< bool >()

template<>

bool parse_< bool >	(	bool &	,
		const std::string &	raw_str )

parse_< Device >()

template<>

bool parse_< Device >	(	Device &	,
		const std::string &	raw_str )

parse_< TensorShape >()

template<>

bool parse_< TensorShape >	(	TensorShape &	,
		const std::string &	raw_str )

parse_< VariableName >()

template<>

bool parse_< VariableName >	(	VariableName &	,
		const std::string &	raw_str )

parse_failure_message()

template<typename T >

std::string parse_failure_message

(

const std::string &

raw_str

)

parse_vector()

template<typename T >

std::vector< T > parse_vector

(

const std::string &

raw_str

)

parse_vector_() [1/2]

template<>

bool parse_vector_	(	std::vector< bool > &	vals,
		const std::string &	raw_str )

parse_vector_() [2/2]

template<typename T >

bool parse_vector_	(	std::vector< T > &	vals,
		const std::string &	raw_str )

parse_vector_< bool >()

template<>

bool parse_vector_< bool >	(	std::vector< bool > &	,
		const std::string &	raw_str )

This special one is for the evil std::vector<bool>!

parse_vector_vector()

template<typename T >

std::vector< std::vector< T > > parse_vector_vector

(

const std::string &

raw_str

)

parse_vector_vector_()

template<typename T >

bool parse_vector_vector_	(	std::vector< std::vector< T > > &	vals,
		const std::string &	raw_str )

sizes_broadcastable()

template<class... T>

bool sizes_broadcastable

(

const T &...

shapes

)

Check if the shapes are broadcastable.

Shapes are said to be broadcastable if, starting from the trailing dimension and iterating backward, the dimension sizes either are equal, one of them is 1, or one of them does not exist.

sizes_same()

template<class... T>

bool sizes_same

(

T &&...

shapes

)

Check if all shapes are the same.

split()

std::vector< std::string > split	(	const std::string &	str,
		const std::string &	delims )

start_with()

bool start_with	(	std::string_view	str,
		std::string_view	prefix )

storage_size()

Size storage_size

(

TensorShapeRef

shape

)

The flattened storage size of a tensor with given shape.

For example,

storage_size({}) == 1;
storage_size({0}) == 0;
storage_size({1}) == 1;
storage_size({1, 2, 3}) == 6;
storage_size({5, 1, 1}) == 5;

stream_all()

template<typename T , typename... Args>

void stream_all	(	std::ostringstream &	ss,
		T &&	val,
		Args &&...	args )

stringify() [1/2]

template<>

std::string stringify ( const bool & t )

inline

stringify() [2/2]

template<typename T >

std::string stringify

(

const T &

t

)

trim()

std::string trim	(	const std::string &	str,
		const std::string &	white_space )