#include <tensor.hpp>

Public Member Functions
xt::xarray< T > &	data ()
	Get the underlying xtensor array.

const xt::xarray< T > &	data () const
	Get the underlying xtensor array (const)

Constructors
	Tensor ()
	Default constructor creating an empty tensor.

	Tensor (const std::vector< size_t > &shape)
	Constructor creating a tensor with specified shape.

	Tensor (size_t rows, size_t cols)
	Constructor creating a 2D tensor (matrix) with specified dimensions.

	Tensor (const std::vector< size_t > &shape, T value)
	Constructor creating a tensor filled with a specific value.

	Tensor (size_t rows, size_t cols, T value)
	Constructor creating a 2D tensor (matrix) filled with a specific value.

	Tensor (std::initializer_list< std::initializer_list< T > > list)
	Constructor from initializer list (2D matrix)

	Tensor (const xt::xarray< T > &data)
	Constructor from xtensor array.

Element Access
template<typename... Args>
T &	operator() (Args... indices)
	Access tensor element at specified position (mutable)

template<typename... Args>
const T &	operator() (Args... indices) const
	Access tensor element at specified position (const)

T &	at (size_t row, size_t col)
	Access 2D tensor element at specified position (mutable) - backward compatibility.

const T &	at (size_t row, size_t col) const
	Access 2D tensor element at specified position (const) - backward compatibility.

Arithmetic Operations
Tensor	operator+ (const Tensor &other) const
	Tensor element-wise addition operator.

Tensor	operator- (const Tensor &other) const
	Tensor element-wise subtraction operator.

Tensor	operator* (const Tensor &other) const
	Tensor element-wise multiplication operator.

Tensor	matmul (const Tensor &other) const
	Matrix multiplication operator (for 2D tensors)

Tensor	operator* (T scalar) const
	Scalar multiplication operator.

Tensor Operations
Tensor	transpose () const
	Compute the transpose of the tensor (for 2D tensors)

Tensor	transpose (const std::vector< size_t > &axes) const
	Transpose along specified axes.

Tensor	reshape (const std::vector< size_t > &new_shape) const
	Reshape the tensor to new dimensions.

Tensor	reshape (size_t new_rows, size_t new_cols) const
	Reshape the tensor to new 2D dimensions (backward compatibility)

Tensor	view (const std::vector< size_t > &new_shape) const
	Create a view of the tensor with new shape.

Tensor	squeeze (int axis=-1) const
	Squeeze dimensions of size 1.

Tensor	unsqueeze (size_t axis) const
	Add a dimension of size 1.

T	determinant () const
	Calculate the determinant of the matrix (for 2D square tensors)

Tensor	inverse () const
	Calculate the inverse of the matrix (for 2D square tensors)

auto	eigenvalues () const
	Calculate eigenvalues of the matrix (for 2D square tensors)

Utility Methods
size_t	rows () const
	Get the number of rows.

size_t	cols () const
	Get the number of columns.

size_t	size () const
	Get the total number of elements.

std::tuple< size_t, size_t >	shape () const
	Get the shape of the matric in one step.

Static Public Member Functions
Static Factory Methods
static Tensor	zeros (const std::vector< size_t > &shape)
	Create a zero tensor.

static Tensor	zeros (size_t rows, size_t cols)
	Create a zero matrix (backward compatibility)

static Tensor	ones (const std::vector< size_t > &shape)
	Create a tensor filled with ones.

static Tensor	ones (size_t rows, size_t cols)
	Create a matrix filled with ones (backward compatibility)

static Tensor	full (const std::vector< size_t > &shape, T value)
	Create a tensor filled with a specific value.

static Tensor	identity (size_t size)
	Create an identity matrix (2D tensor)

static Tensor	random (const std::vector< size_t > &shape)
	Create a random tensor with values between 0 and 1.

static Tensor	random (const std::vector< size_t > &shape, T min, T max)
	Create a random tensor with values between min and max.

static Tensor	random (size_t rows, size_t cols)
	Create a matrix with random values between 0 and 1 (backward compatibility)

static Tensor	random (size_t rows, size_t cols, T min, T max)
	Create a matrix with random values (backward compatibility)

static Tensor	from_array (const xt::xarray< T > &array)
	Create a tensor from an existing xt::xarray.

Friends
template<typename U >
std::ostream &	operator<< (std::ostream &os, const Tensor< U > &tensor)

template<typename U >
Tensor< U >	dot (const Tensor< U > &a, const Tensor< U > &b)

template<typename U >
U	sum (const Tensor< U > &tensor)

template<typename U >
U	mean (const Tensor< U > &tensor)

Detailed Description

template<typename T>
class utils::Tensor< T >

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/ml/kmeans.hpp, /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/ml/pca.hpp, /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/ml/svm.hpp, and /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/data_loader.hpp.

Definition at line 48 of file tensor.hpp.

Constructor & Destructor Documentation

◆ Tensor() [1/7]

template<typename T >

utils::Tensor< T >::Tensor ( )

inline

Default constructor creating an empty tensor.

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 58 of file tensor.hpp.

◆ Tensor() [2/7]

template<typename T >

utils::Tensor< T >::Tensor ( const std::vector< size_t > & shape )

explicit

Constructor creating a tensor with specified shape.

Parameters

shape Shape of the tensor

Definition at line 13 of file tensor.cpp.

◆ Tensor() [3/7]

template<typename T >

utils::Tensor< T >::Tensor	(	size_t	rows,
		size_t	cols
	)

Constructor creating a 2D tensor (matrix) with specified dimensions.

Parameters

rows	Number of rows
cols	Number of columns

Definition at line 21 of file tensor.cpp.

◆ Tensor() [4/7]

template<typename T >

utils::Tensor< T >::Tensor	(	const std::vector< size_t > &	shape,
		T	value
	)

Constructor creating a tensor filled with a specific value.

Parameters

shape	Shape of the tensor
value	Value to fill the tensor with

Definition at line 17 of file tensor.cpp.

◆ Tensor() [5/7]

template<typename T >

utils::Tensor< T >::Tensor	(	size_t	rows,
		size_t	cols,
		T	value
	)

Constructor creating a 2D tensor (matrix) filled with a specific value.

Parameters

rows	Number of rows
cols	Number of columns
value	Value to fill the tensor with

Definition at line 25 of file tensor.cpp.

◆ Tensor() [6/7]

template<typename T >

utils::Tensor< T >::Tensor ( std::initializer_list< std::initializer_list< T > > list )

Constructor from initializer list (2D matrix)

Parameters

list	Nested initializer list representing matrix data

Definition at line 37 of file tensor.cpp.

◆ Tensor() [7/7]

template<typename T >

utils::Tensor< T >::Tensor ( const xt::xarray< T > & data )

explicit

Constructor from xtensor array.

Parameters

data	xtensor array data

Definition at line 29 of file tensor.cpp.

Member Function Documentation

◆ at() [1/2]

template<typename T >

T & utils::Tensor< T >::at	(	size_t	row,
		size_t	col
	)

Access 2D tensor element at specified position (mutable) - backward compatibility.

Parameters

row	Row index (0-based)
col	Column index (0-based)

Returns: Reference to the element

Exceptions

std::out_of_range if indices are invalid

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 55 of file tensor.cpp.

◆ at() [2/2]

template<typename T >

const T & utils::Tensor< T >::at	(	size_t	row,
		size_t	col
	)		const

Access 2D tensor element at specified position (const) - backward compatibility.

Parameters

row	Row index (0-based)
col	Column index (0-based)

Returns: Const reference to the element

Exceptions

std::out_of_range if indices are invalid

Definition at line 60 of file tensor.cpp.

◆ cols()

template<typename T >

size_t utils::Tensor< T >::cols ( ) const

inline

Get the number of columns.

Returns: Number of columns

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 296 of file tensor.hpp.

◆ data() [1/2]

template<typename T >

xt::xarray< T > & utils::Tensor< T >::data ( )

inline

Get the underlying xtensor array.

Returns: Reference to the xtensor array

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 409 of file tensor.hpp.

◆ data() [2/2]

template<typename T >

const xt::xarray< T > & utils::Tensor< T >::data ( ) const

inline

Get the underlying xtensor array (const)

Returns: Const reference to the xtensor array

Definition at line 415 of file tensor.hpp.

◆ determinant()

template<typename T >

T utils::Tensor< T >::determinant ( ) const

Calculate the determinant of the matrix (for 2D square tensors)

Returns: Determinant value

Exceptions

std::invalid_argument if tensor is not 2D square

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 233 of file tensor.cpp.

◆ eigenvalues()

template<typename T >

auto utils::Tensor< T >::eigenvalues ( ) const

Calculate eigenvalues of the matrix (for 2D square tensors)

Returns: Eigenvalues

Exceptions

std::invalid_argument if tensor is not 2D square

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 256 of file tensor.cpp.

◆ from_array()

template<typename T >

Tensor< T > utils::Tensor< T >::from_array ( const xt::xarray< T > & array )

static

Create a tensor from an existing xt::xarray.

Parameters

array The xt::xarray to wrap

Returns: Tensor wrapping the array

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 348 of file tensor.cpp.

◆ full()

template<typename T >

Tensor< T > utils::Tensor< T >::full	(	const std::vector< size_t > &	shape,
		T	value
	)

static

Create a tensor filled with a specific value.

Parameters

shape	Shape of the tensor
value	Value to fill the tensor with

Returns: Tensor filled with the specified value

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 289 of file tensor.cpp.

◆ identity()

template<typename T >

Tensor< T > utils::Tensor< T >::identity ( size_t size )

static

Create an identity matrix (2D tensor)

Parameters

size	Size of the square identity matrix

Returns: Identity tensor

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 294 of file tensor.cpp.

◆ inverse()

template<typename T >

Tensor< T > utils::Tensor< T >::inverse ( ) const

Calculate the inverse of the matrix (for 2D square tensors)

Returns: Inverse tensor

Exceptions

std::invalid_argument if tensor is not 2D square or singular

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 243 of file tensor.cpp.

◆ matmul()

template<typename T >

Tensor< T > utils::Tensor< T >::matmul ( const Tensor< T > & other ) const

Matrix multiplication operator (for 2D tensors)

Parameters

other Tensor to multiply with

Returns: Result of matrix multiplication

Exceptions

std::invalid_argument if tensor dimensions are incompatible for matrix multiplication

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 111 of file tensor.cpp.

◆ ones() [1/2]

template<typename T >

Tensor< T > utils::Tensor< T >::ones ( const std::vector< size_t > & shape )

static

Create a tensor filled with ones.

Parameters

shape Shape of the tensor

Returns: Tensor filled with ones

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 277 of file tensor.cpp.

◆ ones() [2/2]

template<typename T >

Tensor< T > utils::Tensor< T >::ones	(	size_t	rows,
		size_t	cols
	)

static

Create a matrix filled with ones (backward compatibility)

Parameters

rows	Number of rows
cols	Number of columns

Returns: Tensor filled with ones with 2D shape

Definition at line 284 of file tensor.cpp.

◆ operator()() [1/2]

template<typename T >

template<typename... Args>

T & utils::Tensor< T >::operator() ( Args... indices )

Access tensor element at specified position (mutable)

Parameters

indices Variable number of indices for n-dimensional access

Returns: Reference to the element

Exceptions

std::out_of_range if indices are invalid

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 432 of file tensor.hpp.

◆ operator()() [2/2]

template<typename T >

template<typename... Args>

const T & utils::Tensor< T >::operator() ( Args... indices ) const

Access tensor element at specified position (const)

Parameters

indices Variable number of indices for n-dimensional access

Returns: Const reference to the element

Exceptions

std::out_of_range if indices are invalid

Definition at line 438 of file tensor.hpp.

◆ operator*() [1/2]

template<typename T >

Tensor< T > utils::Tensor< T >::operator* ( const Tensor< T > & other ) const

Tensor element-wise multiplication operator.

Parameters

other Tensor to multiply with

Returns: Result of element-wise tensor multiplication

Exceptions

std::invalid_argument if tensor shapes don't match

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 93 of file tensor.cpp.

◆ operator*() [2/2]

template<typename T >

Tensor< T > utils::Tensor< T >::operator* ( T scalar ) const

Scalar multiplication operator.

Parameters

scalar Scalar value to multiply with

Returns: Result of scalar multiplication

Definition at line 104 of file tensor.cpp.

◆ operator+()

template<typename T >

Tensor< T > utils::Tensor< T >::operator+ ( const Tensor< T > & other ) const

Tensor element-wise addition operator.

Parameters

other Tensor to add

Returns: Result of tensor addition

Exceptions

std::invalid_argument if tensor shapes don't match

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 71 of file tensor.cpp.

◆ operator-()

template<typename T >

Tensor< T > utils::Tensor< T >::operator- ( const Tensor< T > & other ) const

Tensor element-wise subtraction operator.

Parameters

other Tensor to subtract

Returns: Result of tensor subtraction

Exceptions

std::invalid_argument if tensor shapes don't match

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 82 of file tensor.cpp.

◆ random() [1/4]

template<typename T >

Tensor< T > utils::Tensor< T >::random ( const std::vector< size_t > & shape )

static

Create a random tensor with values between 0 and 1.

Parameters

shape Shape of the tensor

Returns: Random tensor

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 302 of file tensor.cpp.

◆ random() [2/4]

template<typename T >

Tensor< T > utils::Tensor< T >::random	(	const std::vector< size_t > &	shape,
		T	min,
		T	max
	)

static

Create a random tensor with values between min and max.

Parameters

shape	Shape of the tensor
min	Minimum random value
max	Maximum random value

Returns: Random tensor

Definition at line 313 of file tensor.cpp.

◆ random() [3/4]

template<typename T >

Tensor< T > utils::Tensor< T >::random	(	size_t	rows,
		size_t	cols
	)

static

Create a matrix with random values between 0 and 1 (backward compatibility)

Parameters

rows	Number of rows
cols	Number of columns

Returns: Random tensor with 2D shape

Definition at line 324 of file tensor.cpp.

◆ random() [4/4]

template<typename T >

Tensor< T > utils::Tensor< T >::random	(	size_t	rows,
		size_t	cols,
		T	min,
		T	max
	)

static

Create a matrix with random values (backward compatibility)

Parameters

rows	Number of rows
cols	Number of columns
min	Minimum random value
max	Maximum random value

Returns: Random tensor with 2D shape

Definition at line 336 of file tensor.cpp.

◆ reshape() [1/2]

template<typename T >

Tensor< T > utils::Tensor< T >::reshape ( const std::vector< size_t > & new_shape ) const

Reshape the tensor to new dimensions.

Parameters

new_shape New shape for the tensor

Returns: Reshaped tensor

Exceptions

std::invalid_argument if total size doesn't match

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 156 of file tensor.cpp.

◆ reshape() [2/2]

template<typename T >

Tensor< T > utils::Tensor< T >::reshape	(	size_t	new_rows,
		size_t	new_cols
	)		const

Reshape the tensor to new 2D dimensions (backward compatibility)

Parameters

new_rows	New number of rows
new_cols	New number of columns

Returns: Reshaped tensor

Exceptions

std::invalid_argument if total size doesn't match

Definition at line 170 of file tensor.cpp.

◆ rows()

template<typename T >

size_t utils::Tensor< T >::rows ( ) const

inline

Get the number of rows.

Returns: Number of rows

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 290 of file tensor.hpp.

◆ shape()

template<typename T >

std::tuple< size_t, size_t > utils::Tensor< T >::shape ( ) const

inline

Get the shape of the matric in one step.

Returns: Shape (rows, cols) in tuple

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 308 of file tensor.hpp.

◆ size()

template<typename T >

size_t utils::Tensor< T >::size ( ) const

inline

Get the total number of elements.

Returns: Total size (rows * cols)

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 302 of file tensor.hpp.

◆ squeeze()

template<typename T >

Tensor< T > utils::Tensor< T >::squeeze ( int axis = -1 ) const

Squeeze dimensions of size 1.

Parameters

axis	Optional axis to squeeze (if -1, squeeze all dimensions of size 1)

Returns: Squeezed tensor

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 189 of file tensor.cpp.

◆ transpose() [1/2]

template<typename T >

Tensor< T > utils::Tensor< T >::transpose ( ) const

Compute the transpose of the tensor (for 2D tensors)

Returns: Transposed tensor

Exceptions

std::invalid_argument if tensor is not 2D

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 128 of file tensor.cpp.

◆ transpose() [2/2]

template<typename T >

Tensor< T > utils::Tensor< T >::transpose ( const std::vector< size_t > & axes ) const

Transpose along specified axes.

Parameters

axes	Axes to transpose

Returns: Transposed tensor

Definition at line 139 of file tensor.cpp.

◆ unsqueeze()

template<typename T >

Tensor< T > utils::Tensor< T >::unsqueeze ( size_t axis ) const

Add a dimension of size 1.

Parameters

axis	Axis where to add the dimension

Returns: Tensor with added dimension

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 220 of file tensor.cpp.

◆ view()

template<typename T >

Tensor< T > utils::Tensor< T >::view ( const std::vector< size_t > & new_shape ) const

Create a view of the tensor with new shape.

Parameters

new_shape New shape for the view

Returns: Tensor view with new shape

Exceptions

std::invalid_argument if total size doesn't match

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 175 of file tensor.cpp.

◆ zeros() [1/2]

template<typename T >

Tensor< T > utils::Tensor< T >::zeros ( const std::vector< size_t > & shape )

static

Create a zero tensor.

Parameters

shape Shape of the tensor

Returns: Zero tensor

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

Definition at line 267 of file tensor.cpp.

◆ zeros() [2/2]

template<typename T >

Tensor< T > utils::Tensor< T >::zeros	(	size_t	rows,
		size_t	cols
	)

static

Create a zero matrix (backward compatibility)

Parameters

rows	Number of rows
cols	Number of columns

Returns: Zero tensor with 2D shape

Definition at line 272 of file tensor.cpp.

Friends And Related Symbol Documentation

◆ dot

template<typename T >

template<typename U >

Tensor< U > dot	(	const Tensor< U > &	a,
		const Tensor< U > &	b
	)

friend

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

◆ mean

template<typename T >

template<typename U >

U mean ( const Tensor< U > & tensor )

friend

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

◆ operator<<

template<typename T >

template<typename U >

std::ostream & operator<<	(	std::ostream &	os,
		const Tensor< U > &	tensor
	)

friend

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

◆ sum

template<typename T >

template<typename U >

U sum ( const Tensor< U > & tensor )

friend

Examples: /home/runner/work/deep-learning-algo-impls/deep-learning-algo-impls/include/utils/tensor.hpp.

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

include/utils/tensor.hpp
src/utils/tensor.cpp

Public Member Functions

Static Public Member Functions

Friends

Detailed Description

Constructor & Destructor Documentation

◆ Tensor() [1/7]

◆ Tensor() [2/7]

◆ Tensor() [3/7]

◆ Tensor() [4/7]

◆ Tensor() [5/7]

◆ Tensor() [6/7]

◆ Tensor() [7/7]

Member Function Documentation

◆ at() [1/2]

◆ at() [2/2]

◆ cols()

◆ data() [1/2]

◆ data() [2/2]

◆ determinant()

◆ eigenvalues()

◆ from_array()

◆ full()

◆ identity()

◆ inverse()

◆ matmul()

◆ ones() [1/2]

◆ ones() [2/2]

◆ operator()() [1/2]

◆ operator()() [2/2]

◆ operator*() [1/2]

◆ operator*() [2/2]

◆ operator+()

◆ operator-()

◆ random() [1/4]

◆ random() [2/4]

◆ random() [3/4]

◆ random() [4/4]

◆ reshape() [1/2]

◆ reshape() [2/2]

◆ rows()

◆ shape()

◆ size()

◆ squeeze()

◆ transpose() [1/2]

◆ transpose() [2/2]

◆ unsqueeze()

◆ view()

◆ zeros() [1/2]

◆ zeros() [2/2]

Friends And Related Symbol Documentation

◆ dot

◆ mean

◆ operator<<

◆ sum