Tensor¶
matrix_transpose
function¶
template <typename T, index_t Dims>
void matrix_transpose(T *out, const T *in,
shape<Dims> shape)
Matrix transpose. Accepts vec, complex and other compound types
tensor
class¶
template <typename T, index_t NDims> tensor
tensor holds or references multidimensional data and provides a way to access individual elements and perform complex operations on the data.
The number of elements in each axis of the array is defined by its shape.
Template param T
element type
Template param NDims
number of dimensions
tensor_iterator
class¶
tensor_iterator
Tensor iterator. Iterates through flattened array
tensor<T, NDims>
function¶
constexpr tensor()
: m_data(0), m_size(0), m_is_contiguous(false), m_shape
Default constructor. Creates tensor with null shape
tensor(T *data, const shape_type &shape,
const shape_type &strides,
memory_finalizer finalizer)
: m_data(data), m_size(size_of_shape(shape)),
m_is_contiguous(
strides ==
internal_generic::strides_for_shape(shape)),
m_shape(shape), m_strides(strides),
m_finalizer(std::move(finalizer))
Construct from external pointer, shape, strides and finalizer
tensor(T *data, const shape_type &shape,
memory_finalizer finalizer)
: m_data(data), m_size(size_of_shape(shape)),
m_is_contiguous(true), m_shape(shape),
m_strides(internal_generic::strides_for_shape(shape)),
m_finalizer(std::move(finalizer))
Construct from external pointer, shape and finalizer with default strides
explicit tensor(const shape_type &shape)
: m_size(size_of_shape(shape)), m_is_contiguous(true),
m_shape(shape),
m_strides(internal_generic::strides_for_shape(shape))
Construct from shape and allocate memory
tensor(const shape_type &shape, const shape_type &strides)
: m_size(size_of_shape(shape)),
m_is_contiguous(
strides ==
internal_generic::strides_for_shape(shape)),
m_shape(shape), m_strides(strides)
Construct from shape, strides and allocate memory
tensor(const shape_type &shape, T value) : tensor(shape)
Construct from shape, allocate memory and fill with value
tensor(const shape_type &shape, const shape_type &strides,
T value)
: tensor(shape, strides)
Construct from shape, strides, allocate memory and fill with value
tensor(const shape_type &shape,
const std::initializer_list<T> &values)
: tensor(shape)
Construct from shape, allocate memory and fill with flat list
template <typename U, KFR_ENABLE_IF(std::is_convertible_v<
U, T> &&dims == 1)>
tensor(const std::initializer_list<U> &values)
: tensor(shape_type(values.size()))
Initialize with braced list. Defined for 1D tensor only
template <typename U, KFR_ENABLE_IF(std::is_convertible_v<
U, T> &&dims == 2)>
tensor(const std::initializer_list<std::initializer_list<U>>
&values)
: tensor(
shape_type(values.size(), values.begin()->size()))
Initialize with braced list. Defined for 2D tensor only
template <typename U, KFR_ENABLE_IF(std::is_convertible_v<
U, T> &&dims == 3)>
tensor(const std::initializer_list<std::initializer_list<
std::initializer_list<U>>> &values)
: tensor(shape_type(values.size(),
values.begin()->size(),
values.begin()->begin()->size()))
Initialize with braced list. Defined for 3D tensor only
template <typename U, KFR_ENABLE_IF(std::is_convertible_v<
U, T> &&dims == 4)>
tensor(const std::initializer_list<std::initializer_list<
std::initializer_list<std::initializer_list<U>>>>
&values)
: tensor(shape_type(
values.size(), values.begin()->size(),
values.begin()->begin()->size(),
values.begin()->begin()->begin()->size()))
Initialize with braced list. Defined for 4D tensor only
Auto-generated from sources, Revision 6aea976a464de59d522d0c629e64bf0c044e6777, https://github.com/kfrlib/kfr/blob/6aea976a464de59d522d0c629e64bf0c044e6777/include/kfr/