Enum BackendTensor 

pub enum BackendTensor<B: Backend> {
    Float(FloatTensor<B>),
    AdFloat(FloatTensor<Autodiff<B>>),
    Int(IntTensor<B>),
    AdInt(IntTensor<Autodiff<B>>),
    Bool(BoolTensor<B>),
    AdBool(BoolTensor<Autodiff<B>>),
    Quantized(QuantizedTensor<B>),
    AdQuantized(QuantizedTensor<Autodiff<B>>),
}

Variants

Float(FloatTensor<B>)

AdFloat(FloatTensor<Autodiff<B>>)

Int(IntTensor<B>)

AdInt(IntTensor<Autodiff<B>>)

Bool(BoolTensor<B>)

AdBool(BoolTensor<Autodiff<B>>)

Quantized(QuantizedTensor<B>)

AdQuantized(QuantizedTensor<Autodiff<B>>)

Implementations

impl<B: Backend> BackendTensor<B>

pub fn context(&self) -> AutodiffContext

pub fn with_context(self, context: AutodiffContext) -> Self

pub fn device(&self) -> B::Device

Trait Implementations

impl<B: Clone + Backend> Clone for BackendTensor<B>

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<B: Debug + Backend> Debug for BackendTensor<B>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<B: Backend> QTensorPrimitive for BackendTensor<B>

fn scheme(&self) -> &QuantScheme

Returns the quantization settings for the given tensor.

fn acc_precision(&self) -> QuantAcc

The precision used for the accumulation in various kernels.

fn propagation(&self) -> QuantPropagation

How quantization is propagated during computation.

fn default_scheme() -> QuantScheme

Returns the default tensor quantization scheme.

impl<B: Backend> TensorMetadata for BackendTensor<B>

fn dtype(&self) -> DType

The dtype of the tensor.

fn shape(&self) -> Shape

The shape of the tensor.

fn rank(&self) -> usize

The number of dimensions of the tensor.

fn can_mut(&self) -> bool

Whether the backend considers this tensor’s storage eligible for in-place mutation. Implementations without ownership information return false.