def fitted_mapping

bendtorch-core@0.1.0.0 · src/autograd/reduce_PROOF.bend:366

import Base
import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape
import bendtorch-core@0.1.0.0/src/tensor/core.bend as Core
import bendtorch-core@0.1.0.0/src/tensor/layout.bend as Layout
import bendtorch-core@0.1.0.0/src/autograd/reduce.bend as Reduce
import bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend as Laws

366def fitted_mapping(+shape: Shape.Shape, tensor: Core.Tensor<shape>, +target: Shape.Shape, +plan: Shape.BroadcastPlan, same: Bool,
367  -decided: {same == Layout.words_same(Shape.dimensions(Shape.output_shape(plan)), Shape.dimensions(shape)) : Bool},
368  -left: {Shape.dimensions(Shape.left_shape(plan)) == Shape.dimensions(target) : List<&2, U32>},
369  -right: {Shape.dimensions(Shape.right_shape(plan)) == Shape.dimensions(shape) : List<&2, U32>}) ->
370  Holds<Laws.MappingWith(Core.Packed{shape, tensor}, target, Done{plan}, Reduce.fitted(Core.Packed{shape, tensor}, target, plan, same))>:
371  match same:
372    case False{}:
373      Holds{Unit{}}
374    case True{}:
375      Holds{{\{Holds: proof => proof} :
376        Holds<Laws.MappingWith(Core.Packed{shape, tensor}, target, Done{plan}, Reduce.parallel_allocated(Core.Packed{shape, tensor}, target, plan, Core.new(target, 0.0)))> ->
377        Laws.MappingWith(Core.Packed{shape, tensor}, target, Done{plan}, Reduce.parallel_allocated(Core.Packed{shape, tensor}, target, plan, Core.new(target, 0.0)))}(
378        parallel_mapping(shape, tensor, target, plan, Core.new(target, 0.0), {==}, left, right,
379          {\{Holds: proof => proof} :
380            Holds<{Shape.logical_numel(Shape.dimensions(Shape.output_shape(plan))) == Shape.logical_numel(Shape.dimensions(shape)) : Nat}> ->
381            {Shape.logical_numel(Shape.dimensions(Shape.output_shape(plan))) == Shape.logical_numel(Shape.dimensions(shape)) : Nat}}(
382            output_numel(shape, plan, decided))))}