vortex_array::compute

Trait ComputeFnVTable

Source 
pub trait ComputeFnVTable:
    'static
    + Send
    + Sync {
    // Required methods
    fn invoke(
        &self,
        args: &InvocationArgs<'_>,
        kernels: &[ArcRef<dyn Kernel>],
    ) -> VortexResult<Output>;
    fn return_dtype(&self, args: &InvocationArgs<'_>) -> VortexResult<DType>;
    fn return_len(&self, args: &InvocationArgs<'_>) -> VortexResult<usize>;
    fn is_elementwise(&self) -> bool;
}
Expand description

VTable for the implementation of a compute function.

Required Methods§

Source

fn invoke( &self, args: &InvocationArgs<'_>, kernels: &[ArcRef<dyn Kernel>], ) -> VortexResult<Output>

Invokes the compute function entry-point with the given input arguments and options.

The entry-point logic can short-circuit compute using statistics, update result array statistics, search for relevant compute kernels, and canonicalize the inputs in order to successfully compute a result.

Source

fn return_dtype(&self, args: &InvocationArgs<'_>) -> VortexResult<DType>

Computes the return type of the function given the input arguments.

All kernel implementations will be validated to return the DType as computed here.

Source

fn return_len(&self, args: &InvocationArgs<'_>) -> VortexResult<usize>

Computes the return length of the function given the input arguments.

All kernel implementations will be validated to return the len as computed here. Scalars are considered to have length 1.

Source

fn is_elementwise(&self) -> bool

Returns whether the function operates elementwise, i.e. the output is the same shape as the input and no information is shared between elements.

Examples include add, subtract, and, cast, fill_null etc. Examples that are not elementwise include sum, count, min, fill_forward etc.

All input arrays to an elementwise function must have the same length.

Implementors§