Struct JitTensor

pub struct JitTensor<R>
where
    R: JitRuntime,
{
    pub client: ComputeClient<<R as Runtime>::Server, <R as Runtime>::Channel>,
    pub handle: Handle,
    pub shape: Shape,
    pub device: <R as Runtime>::Device,
    pub strides: Vec<usize>,
    /* private fields */
}

The basic tensor primitive struct.

Fields

client: ComputeClient<<R as Runtime>::Server, <R as Runtime>::Channel>

Compute client for the runtime.

handle: Handle

The buffer where the data are stored.

shape: Shape

The shape of the tensor.

device: <R as Runtime>::Device

The device of the tensor.

strides: Vec<usize>

The strides of the tensor.

Implementations

impl<R> JitTensor<R>

where R: JitRuntime,

pub fn new( client: ComputeClient<<R as Runtime>::Server, <R as Runtime>::Channel>, handle: Handle, shape: Shape, device: <R as Runtime>::Device, strides: Vec<usize>, dtype: DType, ) -> JitTensor<R>

Constructs a new JitTensor.

impl<R> JitTensor<R>

where R: JitRuntime,

pub fn new_contiguous( client: ComputeClient<<R as Runtime>::Server, <R as Runtime>::Channel>, device: <R as Runtime>::Device, shape: Shape, handle: Handle, dtype: DType, ) -> JitTensor<R>

Create a new tensor with a contiguous memory layout.

pub fn to_client( &self, client: ComputeClient<<R as Runtime>::Server, <R as Runtime>::Channel>, device: <R as Runtime>::Device, ) -> JitTensor<R>

Change the context of the current tensor and return the newly transferred tensor.

pub fn as_handle_ref(&self) -> TensorHandleRef<'_, R>

Return the reference to a tensor handle.

pub fn as_tensor_arg<'a, E>(&'a self, vectorisation: u8) -> TensorArg<'a, R>

where E: JitElement,

Return the reference to a tensor argument.

pub fn as_array_arg<E>(&self, vectorisation: u8) -> ArrayArg<'_, R>

where E: JitElement,

Return the reference to an array argument.

pub fn copy(&self) -> JitTensor<R>

Copy the current tensor.

pub fn can_mut(&self) -> bool

Check if the tensor is safe to mutate.

pub fn assert_is_on_same_device(&self, other: &JitTensor<R>)

Assert that both tensors are on the same device.

pub fn is_contiguous(&self) -> bool

Check if the current tensor is contiguous.

pub fn is_contiguous_buffer(&self) -> bool

Check if the current tensor has a contiguous backing buffer (no overlap and no empty memory regions within the shape).

Trait Implementations

impl<R> Clone for JitTensor<R>

where R: JitRuntime,

fn clone(&self) -> JitTensor<R>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<R> Debug for JitTensor<R>

where R: JitRuntime,

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

Formats the value using the given formatter.

impl<R> From<JitTensor<R>> for JitFusionHandle<R>

where R: JitRuntime,

fn from(value: JitTensor<R>) -> JitFusionHandle<R>

Converts to this type from the input type.

impl<R, E> From<JitTensor<R>> for TensorHandle<R, E>

where R: JitRuntime, E: JitElement,

fn from(val: JitTensor<R>) -> TensorHandle<R, E>

Converts to this type from the input type.

impl<R> QTensorPrimitive for JitTensor<R>

where R: JitRuntime,

fn scheme(&self) -> &QuantizationScheme

Returns the quantization scheme for the given tensor.

impl<R> TensorMetadata for JitTensor<R>

where R: JitRuntime,

fn dtype(&self) -> DType

The dtype of the tensor.

fn shape(&self) -> Shape

The shape of the tensor.