Struct OptBinByScalar

pub struct OptBinByScalar {
    pub binop: Box<dyn BinMiniOp>,
    /* private fields */
}

Fields

binop: Box<dyn BinMiniOp>

Trait Implementations

impl Clone for OptBinByScalar

fn clone(&self) -> OptBinByScalar

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for OptBinByScalar

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

Formats the value using the given formatter.

impl EvalOp for OptBinByScalar

fn is_stateless(&self) -> bool

fn eval( &self, inputs: SmallVec<[TValue; 4]>, ) -> Result<SmallVec<[TValue; 4]>, Error>

fn eval_with_session( &self, session: &SessionState, inputs: SmallVec<[TValue; 4]>, ) -> Result<SmallVec<[TValue; 4]>, Error>

fn state( &self, session: &mut SessionState, node_id: usize, ) -> Result<Option<Box<dyn OpState>>, Error>

impl Op for OptBinByScalar

fn name(&self) -> Cow<'_, str>

fn same_as(&self, other: &(dyn Op + 'static)) -> bool

Compare two ops.

fn as_typed(&self) -> Option<&(dyn TypedOp + 'static)>

fn validation(&self) -> Validation

The kind of accuracy check that should be performed on operation when testing them.

fn info(&self) -> Result<Vec<String>, Error>

Short (one-line) strings giving hints on internal implementation or important configuration details to be displayed in dumps.

impl TypedOp for OptBinByScalar

fn output_facts( &self, inputs: &[&TypedFact], ) -> Result<SmallVec<[TypedFact; 4]>, Error>

Deduce output facts from input facts.

fn cost( &self, inputs: &[&TypedFact], ) -> Result<SmallVec<[(Cost, TDim); 4]>, Error>

Computes a cost hint of the operation.

fn as_op(&self) -> &(dyn Op + 'static)

Reinterpret the TypedOp as an Op.

fn as_op_mut(&mut self) -> &mut (dyn Op + 'static)

Reinterpret the TypedOp as an Op, mutably.

fn axes_mapping( &self, inputs: &[&TypedFact], outputs: &[&TypedFact], ) -> Result<AxesMapping, Error>

fn fuse( &self, _model: &Graph<TypedFact, Box<dyn TypedOp>>, _node: &Node<TypedFact, Box<dyn TypedOp>>, ) -> Result<Option<ModelPatch<TypedFact, Box<dyn TypedOp>>>, Error>

Fuse op after codegen to deal with local optimisations.

fn declutter_with_session( &self, session: &mut OptimizerSession<'_>, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, ) -> Result<Option<ModelPatch<TypedFact, Box<dyn TypedOp>>>, Error>

Declutter the op to the tract_core operator set as much as possible.

fn declutter( &self, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, ) -> Result<Option<ModelPatch<TypedFact, Box<dyn TypedOp>>>, Error>

Declutter the op to the tract_core operator set as much as possible.

fn suggested_axis_changes( &self, ) -> Result<SmallVec<[(InOut, AxisOp); 4]>, Error>

fn change_axes( &self, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, io: InOut, change: &AxisOp, ) -> Result<Option<AxisChangeConsequence>, Error>

fn slice( &self, patch: &mut ModelPatch<TypedFact, Box<dyn TypedOp>>, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, prefix: &str, inputs: &[OutletId], output_axis: usize, start: &TDim, end: &TDim, ) -> Result<Option<SmallVec<[OutletId; 4]>>, Error>

fn quantize( &self, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, dt: DatumType, scale: f32, zero_point: i32, ) -> Result<Option<Box<dyn TypedOp>>, Error>

Transforms the op in an equivalent one, operating on dt (i8 or u8).

fn concretize_dims( &self, source: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, target: &mut Graph<TypedFact, Box<dyn TypedOp>>, mapping: &HashMap<OutletId, OutletId>, values: &SymbolValues, ) -> Result<SmallVec<[OutletId; 4]>, Error>

Transform the op into by providing a value to one or more symbols.

fn codegen( &self, model: &Graph<TypedFact, Box<dyn TypedOp>>, node: &Node<TypedFact, Box<dyn TypedOp>>, ) -> Result<Option<ModelPatch<TypedFact, Box<dyn TypedOp>>>, Error>

Translate the op into the most efficient form possible for execution.

fn nested_model_multipliers( &self, inputs: &[&TypedFact], ) -> Vec<(Cow<'_, str>, TDim)>

Nested model multipliers, with label (for profiling).