vt::Tensor#

template<size_t N>
using vt::Shape = std::array<size_t, N>#
template<size_t N>
size_t vt::get_size(const Shape<N> &shape)#

Helper function to calculate the size of a tensor.

Parameters:

shape – Shape of the tensor.

Template Parameters:

N – Number of dimensions of the tensor.

Returns:

size: Size of the tensor.

template<size_t N>
Shape<N> vt::get_strides(const Shape<N> &shape, const Order order)#

Helper function to calculate the strides of a tensor.

Parameters:

  • shape – Shape of the tensor.

  • order – Order of the tensor.

Template Parameters:

N – Number of dimensions of the tensor.

Returns:

strides: Strides of the tensor.

template<size_t N, typename ...Args>
Shape<sizeof...(Args) + N> vt::expand_shape(const Shape<N> &shape, Args... args)#

Helper function to expand the shape.

Parameters:

  • shape – Shape

  • args – New dimensions to be expanded.

Template Parameters:

  • N – Shape dimensions.

  • Args – Variadic template for mulitple arguments.

Returns:

Shape: Expanded shape.

template<typename T, size_t N>
class Tensor#

Forward declaration of the Tensor class.

Tensor class. It is used to represent a tensor from thrust device vector. The concept of the tesnor is similar to the numpy array in Python. It stored a shared pointer to the data, and shape, strides, start index of the tensor.

Template Parameters:

  • T – Data type of the tensor.

  • N – Number of dimensions of the tensor.

Subclassed by vt::TensorCondProxy< T, N >, vt::TensorSliceProxy< T, N >

Public Functions

inline Tensor(const Shape<N> &shape, const Order order)#

Construct a new tensor object from a shape.

Parameters:

  • shape – Shape of the tensor.

  • order – Order of the tensor.

inline Tensor(const std::shared_ptr<vector_type> &data, const Shape<N> &shape, const Order order)#

Construct a new tensor object from a shared vector and a shape.

Parameters:

  • data – A shared vector

  • shape – Shape of the tensor.

  • order – Order of the tensor.

inline Tensor(const std::shared_ptr<vector_type> &data, const Shape<N> &shape, const Shape<N> &strides, size_t start, const Order order, bool contiguous = true)#

Construct a new tensor object from a shared vector and a shape, strides, start index.

Parameters:

  • data – A shared vector

  • shape – Shape of the tensor.

  • strides – Strides of the tensor.

  • start – Start index of the tensor.

  • order – Order of the tensor.

  • contiguous – contiguous flag of the tensor.

template<typename ...Args>
inline Tensor<T, sizeof...(Args)> reshape(Args... args) const#

Reshape the array to a new shape. If the tensor has been contiguous, the method will copy the tensor and reshape the new tensor.

Template Parameters:

Args – Variadic template for mulitple arguments.

Parameters:

args – New shape for the tensor.

Returns:

Tensor: The reshaped tensor.

inline Tensor<T, N - 1> operator[](size_t index) const#

Operator for indexing the tensor along the last axis (row-major order). Notice that the method doesn’t gauranttee the contiguity of the tensor. If the tensor has been transposed, the return slice would not be contiguous.

Parameters:

index – The index of the tensor.

Returns:

Tensor: The sliced tensor.

inline TensorCondProxy<T, N> operator[](const Tensor<bool, N> &cond) const#

Operator for indexing the tensor based on the condition.

Parameters:

cond – A boolean tensor with the same shape as the tensor.

Returns:

TensorCondProxy: The tensor conditional proxy object.

template<typename ...Args>
inline TensorSliceProxy<T, N> operator()(Args... args) const#

Operator for slicing the tensor. It could receive multiple slices through explicit Slice constructor.

Parameters:

args – Slices to be applied to the tensor.

Template Parameters:

Args – Variadic template for mulitple arguments.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline TensorSliceProxy<T, N> operator()(std::array<Slice, N> &slices) const#

Operator for slicing the tensor.

Parameters:

slices – An array of slices to be applied to the tensor.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline TensorSliceProxy<T, 1> operator()(Slice s) const#

Operator for slicing the tensor. It supports one Slice implicit conversion for tensor.

Parameters:

s – Slice to be applied to the tensor.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline TensorSliceProxy<T, 2> operator()(Slice s1, Slice s2) const#

Operator for slicing the tensor. It supports two Slice implicit conversion for tensor.

Parameters:

  • s1 – Slice to be applied to the tensor.

  • s2 – Slice to be applied to the tensor.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline TensorSliceProxy<T, 3> operator()(Slice s1, Slice s2, Slice s3) const#

Operator for slicing the tensor. It supports three Slice implicit conversion for tensor.

Parameters:

  • s1 – Slice to be applied to the tensor.

  • s2 – Slice to be applied to the tensor.

  • s3 – Slice to be applied to the tensor.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline TensorSliceProxy<T, N> operator()(const EllipsisT &e, Slice s) const#

Operator for slicing the tensor. It supports Ellipsis and Slice implicit conversion for tensor.

Parameters:

  • e – Ellipsis to be applied to the tensor.

  • s – Slice to be applied to the tensor.

Returns:

TensorSliceProxy: The tensor slice proxy object.

inline Tensor<T, N + 1> operator()(const EllipsisT &e, const NewAxisT &n) const#

Operator to add a new axis at the last axis to the tensor.

Parameters:

  • e – Ellipsis to be applied to the tensor.

  • n – NewAxis to be applied to the tensor.

Returns:

Tensor: The new tensor object.

inline Tensor<T, N + 1> operator()(const NewAxisT &n, const EllipsisT &e) const#

Operator to add a new axis at the first axis to the tensor.

Parameters:

  • n – NewAxis to be applied to the tensor.

  • e – Ellipsis to be applied to the tensor.

Returns:

Tensor: The new tensor object.

inline Tensor operator+=(const T value) const#

Operator for in-place addition of a vector and a scalar.

Parameters:

value – The scalar value to be added.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator-=(const T value) const#

Operator for in-place minus of a vector and a scalar.

Parameters:

value – The scalar value to be minus.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator*=(const T value) const#

Operator for in-place multiplication of a vector and a scalar.

Parameters:

value – The scalar value to be multiplied.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator/=(const T value) const#

Operator for in-place division of a vector and a scalar.

Parameters:

value – The scalar value to be divided.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator+=(const Tensor &other) const#

Operator for in-place addition of two vectors.

Parameters:

other – The other tensor to be added.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator-=(const Tensor &other) const#

Operator for in-place minus of two vectors.

Parameters:

other – The other tensor to be minus.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator*=(const Tensor &other) const#

Operator for in-place multiplication of two vectors.

Parameters:

other – The other tensor to be multiplied.

Returns:

Tensor: The left-hand side tensor object.

inline Tensor operator/=(const Tensor &other) const#

Operator for in-place division of two vectors.

Parameters:

other – The other tensor to be divided.

Returns:

Tensor: The left-hand side tensor object.

inline TensorIterator<typename vector_type::iterator, N> begin() const#

Return the begin iterator for the Tensor.

Returns:

TensorIterator: The iterator points to the 1st index of the tensor.

inline TensorIterator<typename vector_type::iterator, N> end() const#

Return the end iterator for the Tensor.

Returns:

TensorIterator: The iterator points to the last index of the tensor.

inline Tensor apply_slices(const std::array<Slice, N> &slices) const#

Apply slices the tensor and return the new tensor object.

Parameters:

slices – The slices to be applied to the tensor.

Returns:

Tensor: The new tensor object.

template<typename U>
inline Tensor<U, N> astype()#

Casts the array to given data type.

Template Parameters:

U – The data type to cast.

Returns:

Tensor<U, N>: The new tensor object.

inline T *raw_ptr() const#

Return the raw pointer of the tensor.

Returns:

T*: The raw pointer of the tensor.

inline bool contiguous() const#

Return the contiguous flag of the tensor.

Returns:

bool: The contiguous flag of the tensor.

inline Order order() const#

Return the order of the tensor.

Returns:

Order: The order of the tensor.

inline size_t size() const#

Return the size of the tensor.

Returns:

size_t: The size of the tensor.

inline size_t start() const#

Return the start index of the tensor.

Returns:

size_t: The start index of the tensor.

inline Shape<N> shape() const#

Return the shape of the tensor.

Returns:

Shape: The shape of the tensor.

inline Shape<N> strides() const#

Return the strides of the tensor.

Returns:

Shape: The strides of the tensor.

inline std::shared_ptr<vector_type> data() const#

Return the shared pointer of the data.

Returns:

std::shared_ptr<vector_type>: The shared pointer of the data.

inline void set_strides(Shape<N> strides)#

Set the strides of the tensor.

Parameters:

strides – The strides of the tensor.