Documentation
¶
Index ¶
- func BroadcastIndex(index int, shape, outputShape []int, broadcast bool) int
- func BroadcastShapes(a, b []int) (shape []int, broadcastA, broadcastB bool, err error)
- func SameShape[T Numeric](a, b *Tensor[T]) bool
- type Numeric
- type Tensor
- func (t *Tensor[T]) At(indices ...int) (T, error)
- func (t *Tensor[T]) Copy() *Tensor[T]
- func (t *Tensor[T]) Data() []T
- func (t *Tensor[T]) Dims() int
- func (t *Tensor[T]) Each(f func(val T))
- func (t *Tensor[T]) Reshape(newShape []int) (*Tensor[T], error)
- func (t *Tensor[T]) Set(value T, indices ...int) error
- func (t *Tensor[T]) SetData(data []T)
- func (t *Tensor[T]) SetShape(shape []int)
- func (t *Tensor[T]) SetStrides(strides []int)
- func (t *Tensor[T]) Shape() []int
- func (t *Tensor[T]) ShapeEquals(other *Tensor[T]) bool
- func (t *Tensor[T]) Size() int
- func (t *Tensor[T]) Slice(ranges ...[2]int) (*Tensor[T], error)
- func (t *Tensor[T]) Strides() []int
- func (t *Tensor[T]) String() string
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func BroadcastIndex ¶
BroadcastIndex computes the index into a tensor for a broadcasting operation.
func BroadcastShapes ¶
BroadcastShapes computes the output shape for a broadcasting operation.
Types ¶
type Numeric ¶
type Numeric interface {
~int | ~int8 | ~int16 | ~int32 | ~int64 |
~uint | ~uint32 | ~uint64 |
~float32 | ~float64 |
float8.Float8 |
float16.Float16
}
Numeric defines the constraint for numeric types that can be used in Tensors.
type Tensor ¶
type Tensor[T Numeric] struct { // contains filtered or unexported fields }
Tensor represents an n-dimensional array of a generic numeric type T.
func New ¶
New creates a new Tensor with the given shape and initializes it with the provided data. If data is nil, it allocates a new slice of the appropriate size. The length of the data slice must match the total number of elements calculated from the shape.
func (*Tensor[T]) At ¶
At retrieves the value at the specified indices. It returns an error if the number of indices does not match the tensor's dimensions or if any index is out of bounds.
func (*Tensor[T]) Data ¶
func (t *Tensor[T]) Data() []T
Data returns a slice representing the underlying data of the tensor.
func (*Tensor[T]) Each ¶
func (t *Tensor[T]) Each(f func(val T))
Each iterates over each element of the tensor and applies the given function. This is useful for operations that need to read every value, respecting strides.
func (*Tensor[T]) Reshape ¶
Reshape returns a new Tensor with a different shape that shares the same underlying data. The new shape must have the same total number of elements as the original tensor. This operation is a "view" and does not copy the data.
func (*Tensor[T]) Set ¶
Set updates the value at the specified indices. It returns an error if the number of indices does not match the tensor's dimensions, if any index is out of bounds, or if the tensor is a read-only view.
func (*Tensor[T]) SetData ¶
func (t *Tensor[T]) SetData(data []T)
SetData sets the underlying data of the tensor.
func (*Tensor[T]) SetStrides ¶
SetStrides sets the tensor's strides.
func (*Tensor[T]) ShapeEquals ¶
ShapeEquals returns true if the shapes of two tensors are identical.
func (*Tensor[T]) Slice ¶
Slice creates a new Tensor view for the specified range. A slice is defined by a start and end index for each dimension. The returned tensor shares the same underlying data.
Source Files