fastdeploy::function Namespace Reference

All C++ FDTensor Operation APIs are defined inside this namespace. More...

Functions
void	Cast (const FDTensor &x, FDTensor *out, FDDataType output_dtype)
void	Clip (const FDTensor &x, double min, double max, FDTensor *out)
void	Concat (const std::vector< FDTensor > &x, FDTensor *out, int axis)
FASTDEPLOY_DECL void	CudaCast (const FDTensor &in, FDTensor *out, cudaStream_t stream)
void	Cumprod (const FDTensor &x, FDTensor *out, int axis)
void	Add (const FDTensor &x, const FDTensor &y, FDTensor *out)
void	Subtract (const FDTensor &x, const FDTensor &y, FDTensor *out)
void	Multiply (const FDTensor &x, const FDTensor &y, FDTensor *out)
void	Divide (const FDTensor &x, const FDTensor &y, FDTensor *out)
void	Maximum (const FDTensor &x, const FDTensor &y, FDTensor *out)
void	Full (const Scalar &value, const std::vector< int64_t > &shape, FDTensor *out, FDDataType dtype)
void	FullLike (const FDTensor &x, const Scalar &value, FDTensor *out, FDDataType dtype)
void	GatherAlongAxis (const FDTensor &x, const FDTensor &index, FDTensor *result, int axis)
void	GaussianRandom (const std::vector< int64_t > &shape, FDTensor *out, FDDataType dtype, float mean, float std, int seed)
void	IsNan (const FDTensor &x, FDTensor *out, FDDataType dtype)
void	IsInf (const FDTensor &x, FDTensor *out, FDDataType dtype)
void	IsFinite (const FDTensor &x, FDTensor *out, FDDataType dtype)
void	Linspace (double start, double end, int num, FDTensor *out, FDDataType dtype)
void	Sqrt (const FDTensor &x, FDTensor *out)
void	Log (const FDTensor &x, FDTensor *out)
void	Round (const FDTensor &x, FDTensor *out)
void	Exp (const FDTensor &x, FDTensor *out)
void	Abs (const FDTensor &x, FDTensor *out)
void	Ceil (const FDTensor &x, FDTensor *out)
void	Floor (const FDTensor &x, FDTensor *out)
void	Pad (const FDTensor &x, FDTensor *out, const std::vector< int > &pads, float value)
void	Quantile (const FDTensor &x, const std::vector< double > &q, const std::vector< int > &axis, FDTensor *out)
void	Max (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	Min (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	Sum (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	All (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	Any (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	Mean (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	Prod (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims, bool keep_dim, bool reduce_all)
void	ArgMax (const FDTensor &x, FDTensor *out, int64_t axis, FDDataType output_dtype, bool keep_dim, bool flatten)
void	ArgMin (const FDTensor &x, FDTensor *out, int64_t axis, FDDataType output_dtype, bool keep_dim, bool flatten)
void	Slice (const FDTensor &x, const std::vector< int64_t > &axes, const std::vector< int64_t > &starts, const std::vector< int64_t > &ends, FDTensor *out)
void	Softmax (const FDTensor &x, FDTensor *out, int axis)
void	Sort (const FDTensor &x, FDTensor *out, FDTensor *indices, int axis=0, bool descending=false, FDDataType indices_type=FDDataType::INT64)
	Performs sorting on the input tensor along the given axis and outputs two tensors, Output(Out) and Output(Indices). They reserve the same shape with Input(X), and Output(Out) represents the sorted tensor while Output(Indices) gives the sorted order along the given axis Attr(axis). More...
void	Split (const FDTensor &x, const std::vector< int > &num_or_sections, std::vector< FDTensor > *out, int axis)
void	Tile (const FDTensor &x, const std::vector< int64_t > &repeat_times, FDTensor *out)
void	Transpose (const FDTensor &x, FDTensor *out, const std::vector< int64_t > &dims)

Detailed Description

All C++ FDTensor Operation APIs are defined inside this namespace.

Function Documentation

Abs()

FASTDEPLOY_DECL void fastdeploy::function::Abs	(	const FDTensor &	x,
		FDTensor *	out
	)

This operator is used to perform elementwise abs for input X. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Add()

FASTDEPLOY_DECL void fastdeploy::function::Add	(	const FDTensor &	x,
		const FDTensor &	y,
		FDTensor *	out
	)

Excute the add operation for input FDTensors. *out = x + y.

Parameters

x	The input tensor.
y	The input tensor.
out	The output tensor which stores the result.

All()

FASTDEPLOY_DECL void fastdeploy::function::All	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the all operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Any()

FASTDEPLOY_DECL void fastdeploy::function::Any	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the any operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

ArgMax()

FASTDEPLOY_DECL void fastdeploy::function::ArgMax	(	const FDTensor &	x,
		FDTensor *	out,
		int64_t	axis,
		FDDataType	output_dtype = FDDataType::INT64,
		bool	keep_dim = false,
		bool	flatten = false
	)

Excute the argmax operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
axis	The axis which will be reduced.
output_dtype	The data type of output FDTensor, INT64 or INT32, default to INT64.
keep_dim	Whether to keep the reduced dims, default false.
flatten	Whether to flatten FDTensor to get the argmin index, default false.

ArgMin()

FASTDEPLOY_DECL void fastdeploy::function::ArgMin	(	const FDTensor &	x,
		FDTensor *	out,
		int64_t	axis,
		FDDataType	output_dtype = FDDataType::INT64,
		bool	keep_dim = false,
		bool	flatten = false
	)

Excute the argmin operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
axis	The axis which will be reduced.
output_dtype	The data type of output FDTensor, INT64 or INT32, default to INT64.
keep_dim	Whether to keep the reduced dims, default false.
flatten	Whether to flatten FDTensor to get the argmin index, default false.

Cast()

FASTDEPLOY_DECL void fastdeploy::function::Cast	(	const FDTensor &	x,
		FDTensor *	out,
		FDDataType	output_dtype
	)

Cast x to output data type element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.
output_dtype	The type of output tensor.

Ceil()

FASTDEPLOY_DECL void fastdeploy::function::Ceil	(	const FDTensor &	x,
		FDTensor *	out
	)

Computes ceil of x element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Clip()

FASTDEPLOY_DECL void fastdeploy::function::Clip	(	const FDTensor &	x,
		double	min,
		double	max,
		FDTensor *	out
	)

This operator clip all elements in input into the range [ min, max ]. Support float32, float64, int32, int64

Parameters

x	The input tensor.
min	The lower bound
max	The uppper bound
out	The output tensor which stores the result.

Concat()

FASTDEPLOY_DECL void fastdeploy::function::Concat	(	const std::vector< FDTensor > &	x,
		FDTensor *	out,
		int	axis = 0
	)

Excute the concatenate operation for input FDTensor along given axis.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
axis	Axis which will be concatenated.

CudaCast()

FASTDEPLOY_DECL void fastdeploy::function::CudaCast	(	const FDTensor &	in,
		FDTensor *	out,
		cudaStream_t	stream
	)

Cast the type of the data in GPU buffer.

Parameters

in	The input tensor.
out	The output tensor
stream	CUDA stream

Cumprod()

FASTDEPLOY_DECL void fastdeploy::function::Cumprod	(	const FDTensor &	x,
		FDTensor *	out,
		int	axis = 0
	)

Excute the concatenate operation for input FDTensor along given axis.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
axisi	Axis which will be concatenated.

Divide()

FASTDEPLOY_DECL void fastdeploy::function::Divide	(	const FDTensor &	x,
		const FDTensor &	y,
		FDTensor *	out
	)

Excute the divide operation for input FDTensors. *out = x / y.

Parameters

x	The input tensor.
y	The input tensor.
out	The output tensor which stores the result.

Exp()

FASTDEPLOY_DECL void fastdeploy::function::Exp	(	const FDTensor &	x,
		FDTensor *	out
	)

Computes exp of x element-wise with a natural number e as the base, element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Floor()

FASTDEPLOY_DECL void fastdeploy::function::Floor	(	const FDTensor &	x,
		FDTensor *	out
	)

Computes floor of x element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Full()

FASTDEPLOY_DECL void fastdeploy::function::Full	(	const Scalar &	value,
		const std::vector< int64_t > &	shape,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::FP32
	)

Fill the value to tensor

Parameters

value	The value to be filled in tensor
shape	The shape of output tensor.
out	The output tensor which stores the result.
dtype	The data type of output tensor. Default to float32

FullLike()

FASTDEPLOY_DECL void fastdeploy::function::FullLike	(	const FDTensor &	x,
		const Scalar &	value,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::FP32
	)

Fill the value to tensor

Parameters

x	The input tensor.
value	The value to be filled in tensor
out	The output tensor which stores the result.
dtype	The data type of output tensor. Default to float32

GatherAlongAxis()

FASTDEPLOY_DECL void fastdeploy::function::GatherAlongAxis	(	const FDTensor &	x,
		const FDTensor &	index,
		FDTensor *	result,
		int	axis
	)

Output is obtained by gathering entries of axis of x indexed by index and concatenate them together.

Parameters

x	The input tensor.
index	The index of a tensor to gather.
out	The output tensor which stores the result.
axis	Axis which will be gathered.

GaussianRandom()

void fastdeploy::function::GaussianRandom	(	const std::vector< int64_t > &	shape,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::FP32,
		float	mean = 0.0f,
		float	std = 1.0f,
		int	seed = 0
	)

Output is obtained by gathering entries of axis of x indexed by index and concatenate them together.

Parameters

shape	The output tensor shape.
out	the output tensor.
mean	mean value of gaussian random
std	standard value of gaussian random
seed	The seed of random generator.
dtype	The data type of the output Tensor.

IsFinite()

FASTDEPLOY_DECL void fastdeploy::function::IsFinite	(	const FDTensor &	x,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::BOOL
	)

Return whether every element of input tensor is finite or not.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dtype	The output data type

IsInf()

FASTDEPLOY_DECL void fastdeploy::function::IsInf	(	const FDTensor &	x,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::BOOL
	)

Return whether every element of input tensor is Inf or not.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dtype	The output data type

IsNan()

FASTDEPLOY_DECL void fastdeploy::function::IsNan	(	const FDTensor &	x,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::BOOL
	)

Return whether every element of input tensor is NaN or not.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dtype	The output data type

Linspace()

FASTDEPLOY_DECL void fastdeploy::function::Linspace	(	double	start,
		double	end,
		int	num,
		FDTensor *	out,
		FDDataType	dtype = FDDataType::FP32
	)

Return fixed number of evenly spaced values within a given interval.

Parameters

start	The input start is start variable of range.
end	The input stop is start variable of range.
num	The input num is given num of the sequence.
out	The output tensor which stores the result.
dtype	The data type of output tensor, default to float32.

Log()

FASTDEPLOY_DECL void fastdeploy::function::Log	(	const FDTensor &	x,
		FDTensor *	out
	)

Calculates the natural log of the given input Tensor, element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Max()

FASTDEPLOY_DECL void fastdeploy::function::Max	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the maximum operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Maximum()

FASTDEPLOY_DECL void fastdeploy::function::Maximum	(	const FDTensor &	x,
		const FDTensor &	y,
		FDTensor *	out
	)

Excute the maximum operation for input FDTensors. *out = max(x, y).

Parameters

x	The input tensor.
y	The input tensor.
out	The output tensor which stores the result.

Mean()

FASTDEPLOY_DECL void fastdeploy::function::Mean	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the mean operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Min()

FASTDEPLOY_DECL void fastdeploy::function::Min	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the minimum operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Multiply()

FASTDEPLOY_DECL void fastdeploy::function::Multiply	(	const FDTensor &	x,
		const FDTensor &	y,
		FDTensor *	out
	)

Excute the multiply operation for input FDTensors. *out = x * y.

Parameters

x	The input tensor.
y	The input tensor.
out	The output tensor which stores the result.

Pad()

FASTDEPLOY_DECL void fastdeploy::function::Pad	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int > &	pads,
		float	pad_value = 0
	)

Excute the pad operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
pads	The size of padding for each dimension, for 3-D tensor, the pads should be [1d-left, 1d-right, 2d-left, 2d-right, 3d-left, 3d-right]
pad_value	The value which will fill into out tensor

Prod()

FASTDEPLOY_DECL void fastdeploy::function::Prod	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the product operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Quantile()

FASTDEPLOY_DECL void fastdeploy::function::Quantile	(	const FDTensor &	x,
		const std::vector< double > &	q,
		const std::vector< int > &	axis,
		FDTensor *	out
	)

Compute the quantile of the input along the specified axis. If any values in a reduced row are NaN, then the quantiles for that reduction will be NaN.

Parameters

x	The input tensor.
q	The q for calculate quantile, which should be in range [0, 1].
axis	The axis along which to calculate quantile. axis should be int or list of int.
out	The output tensor which stores the result.

Round()

FASTDEPLOY_DECL void fastdeploy::function::Round	(	const FDTensor &	x,
		FDTensor *	out
	)

Rounds the values in the input to the nearest integer value, element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Slice()

FASTDEPLOY_DECL void fastdeploy::function::Slice	(	const FDTensor &	x,
		const std::vector< int64_t > &	axes,
		const std::vector< int64_t > &	starts,
		const std::vector< int64_t > &	ends,
		FDTensor *	out
	)

This operator produces a slice of input along multiple axes.

Parameters

x	The input tensor.
axes	Axes that starts and ends apply to.
starts	If starts is a list or tuple, the elements of it should be integers or Tensors with shape [1]. If starts is an Tensor, it should be an 1-D Tensor. It represents starting indices of corresponding axis in axes
ends	If ends is a list or tuple, the elements of it should be integers or Tensors with shape [1]. If ends is an Tensor, it should be an 1-D Tensor . It represents ending indices of corresponding axis in axes.
out	The output tensor which stores the result.

Softmax()

FASTDEPLOY_DECL void fastdeploy::function::Softmax	(	const FDTensor &	x,
		FDTensor *	out,
		int	axis = -1
	)

Excute the softmax operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
axis	The axis to be computed softmax value.

Sort()

FASTDEPLOY_DECL void fastdeploy::function::Sort	(	const FDTensor &	x,
		FDTensor *	out,
		FDTensor *	indices,
		int	axis = 0,
		bool	descending = false,
		FDDataType	indices_type = FDDataType::INT64
	)

Performs sorting on the input tensor along the given axis and outputs two tensors, Output(Out) and Output(Indices). They reserve the same shape with Input(X), and Output(Out) represents the sorted tensor while Output(Indices) gives the sorted order along the given axis Attr(axis).

Parameters

x	The input of sort
out	The sorted tensor of sort op, with the same shape as x
indices	The indices of a tensor giving the sorted order, with the same shape as x
axis	The axis along which to sort the tensor. When axis < 0, the actual axis will be the |axis|'th counting backwards
descending	The descending attribute is a flag to tell algorithm how to sort the input data. If descending is true, will sort by descending order, else if false, sort by ascending order
indices_type	The data type of indices, default to int64

Split()

FASTDEPLOY_DECL void fastdeploy::function::Split	(	const FDTensor &	x,
		const std::vector< int > &	num_or_sections,
		std::vector< FDTensor > *	out,
		int	axis = 0
	)

Split the input tensor into multiple sub-Tensors.

Parameters

x	The input tensor.
num_or_sections	f num_or_sections is an int, then num_or_sections indicates the number of equal sized sub-Tensors that the x will be divided into.
out	The output vector tensor which stores the result.
axis	Axis which will be splitted.

Sqrt()

FASTDEPLOY_DECL void fastdeploy::function::Sqrt	(	const FDTensor &	x,
		FDTensor *	out
	)

Calculates the sqrt of the given input Tensor, element-wise. Only for float type FDTensor

Parameters

x	The input tensor.
out	The output tensor which stores the result.

Subtract()

FASTDEPLOY_DECL void fastdeploy::function::Subtract	(	const FDTensor &	x,
		const FDTensor &	y,
		FDTensor *	out
	)

Excute the subtract operation for input FDTensors. *out = x - y.

Parameters

x	The input tensor.
y	The input tensor.
out	The output tensor which stores the result.

Sum()

FASTDEPLOY_DECL void fastdeploy::function::Sum	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims,
		bool	keep_dim = false,
		bool	reduce_all = false
	)

Excute the sum operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which will be reduced.
keep_dim	Whether to keep the reduced dims, default false.
reduce_all	Whether to reduce all dims, default false.

Tile()

FASTDEPLOY_DECL void fastdeploy::function::Tile	(	const FDTensor &	x,
		const std::vector< int64_t > &	repeat_times,
		FDTensor *	out
	)

Construct a new Tensor by repeating x the number of times given by repeat_times. After tiling, the value of the i’th dimension of the output is equal to x.shape[i]*repeat_times[i]. Both the number of dimensions of x and the number of elements in repeat_times should be less than or equal to 6.Support all data types.

Parameters

x	The input tensor.
repeat_times	The lower bound
out	The output tensor which stores the result.

Transpose()

FASTDEPLOY_DECL void fastdeploy::function::Transpose	(	const FDTensor &	x,
		FDTensor *	out,
		const std::vector< int64_t > &	dims
	)

Excute the transpose operation for input FDTensor along given dims.

Parameters

x	The input tensor.
out	The output tensor which stores the result.
dims	The vector of axis which the input tensor will transpose.