Struct tract_core::ops::nn::Lrn

pub struct Lrn { /* fields omitted */ }

Methods

impl Lrn

pub fn new(alpha: f32, beta: f32, bias: f32, size: usize) -> Self

Constructs a new Lrn.

Trait Implementations

impl InferenceRulesOp for Lrn

fn rules<'r, 'p: 'r, 's: 'r>(
    &'s self,
    s: &mut Solver<'r>,
    inputs: &'p [TensorProxy],
    outputs: &'p [TensorProxy]
) -> InferenceResult

Registers the inference rules of the operator.

fn as_op(&self) -> &dyn Op

fn as_op_mut(&mut self) -> &mut dyn Op

fn to_typed(
    &self,
    _source: &InferenceModel,
    node: &InferenceNode,
    target: &mut TypedModel,
    mapping: &HashMap<OutletId, OutletId>
) -> TractResult<TVec<OutletId>>

fn nboutputs(&self) -> TractResult<usize>

impl StatelessOp for Lrn

fn eval(&self, inputs: TVec<Arc<Tensor>>) -> TractResult<TVec<Arc<Tensor>>>

impl Op for Lrn

fn name(&self) -> Cow<str>

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

fn incorporate(
    &self,
    _model: &InferenceModel,
    _node: &InferenceNode
) -> TractResult<Option<InferenceModelPatch>>

Early pass on inference model, after analyse, but before translation to typed network. Meant to deal with some framework idiosyncrasies that manifest with temporaries nodes that can run some form of inference but require refactoring the network before it can be evaluated.

fn declutter(
    &self,
    _model: &TypedModel,
    _node: &TypedNode
) -> TractResult<Option<TypedModelPatch>>

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

fn codegen(
    &self,
    _model: &TypedModel,
    _node: &TypedNode
) -> TractResult<Option<TypedModelPatch>>

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

fn fuse(
    &self,
    _model: &TypedModel,
    _node: &TypedNode
) -> TractResult<Option<TypedModelPatch>>

Fuse op after codegen to deal with local optimisations.

fn cost(&self, _inputs: &[&TypedTensorInfo]) -> TractResult<TVec<(Cost, TDim)>>

Computes a cost hint of the operation.

fn nested_models(&self) -> Vec<(Cow<str>, &dyn Model)>

Nested models, with label (for audit).

fn validation(&self) -> Validation

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

fn axes_info(
    &self,
    _model: &TypedModel,
    _node: &TypedNode
) -> TractResult<AxesInfo>

fn same_as(&self, _other: &dyn Op) -> bool

Compare two ops.

fn info(&self) -> TractResult<Vec<String>>

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

fn is_canonic(&self) -> bool

impl TypedOp for Lrn

fn as_op(&self) -> &dyn Op

Reinterpret the TypedOp as an Op.

fn as_op_mut(&mut self) -> &mut dyn Op

Reinterpret the TypedOp as an Op, mutably.

fn output_facts(
    &self,
    inputs: &[&TypedTensorInfo]
) -> TractResult<TVec<TypedTensorInfo>>

Deduce output facts from input facts.

fn dispose_dummy_axis(
    &self,
    model: &TypedModel,
    node: &TypedNode,
    axis: usize
) -> TractResult<Option<Box<dyn TypedOp>>>

Transforms the op in an equivalent one, discarding one dummy axis (of dim assumed to be 1).

fn pulsify(
    &self,
    _source: &NormalizedModel,
    node: &NormalizedNode,
    _target: &mut PulsedModel,
    _mapping: &HashMap<OutletId, OutletId>,
    _pulse: usize
) -> TractResult<TVec<OutletId>>

Translate an op in a normalized network (no constants) to a pulsing form, if possible.

fn nested_model_multipliers(
    &self,
    inputs: &[&TypedTensorInfo]
) -> Vec<(Cow<str>, f32)>

Nested model multipliers, with label (for profiling).

impl Default for Lrn

fn default() -> Lrn

Returns the "default value" for a type.

impl Clone for Lrn

fn clone(&self) -> Lrn

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Lrn

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

Formats the value using the given formatter.