def sum_decision_status
bendtorch-core@0.1.0.0 · src/tensor/reduction_PROOF.bend:771
import bendtorch-core@0.1.0.0/src/tensor/reduction_PROOF.bend as ReductionPROOF
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/reduction.bend as Reduction
import bendtorch-core@0.1.0.0/src/tensor/math_totality.bend as Totality
import bendtorch-core@0.1.0.0/src/tensor/transform_LAWS.bend as TransformLaws
import bendtorch-core@0.1.0.0/src/tensor/transform_totality.bend as TransformTotality
771def sum_decision_status(+fuel: Nat, +shape: Shape.Shape, +cursor: Nat, +accumulator: F32,
772 decision: Shape.BoolCase<Nat.is_eq(U32.to_nat(U32.from_nat(cursor)), cursor)>,
773 tensor: Core.Tensor<shape>,
774 -exact: {U32.to_nat(U32.from_nat(cursor)) == cursor : Nat},
775 -inside: {Nat.is_lt(U32.to_nat(U32.from_nat(cursor)), Shape.logical_numel(Shape.dimensions(shape))) == True{} : Bool},
776 -rec: @tensor: Core.Tensor<shape> -> @+value: F32 -> Totality.Status<Core.Error, Core.Tensor<shape> & F32,
777 Reduction.natural_sum_loop(fuel, shape, tensor, 1n+cursor, value)>) ->
778 Totality.Status<Core.Error, Core.Tensor<shape> & F32, Reduction.sum_decided(shape,
779 tensor => value => Reduction.natural_sum_loop(fuel, shape, tensor, 1n+cursor, value), tensor, cursor, U32.from_nat(cursor), accumulator, decision)>:
780 match decision:
781 case Shape.BFalse{equal}:
782 Totality.Status{Empty.absurd({False{} == True{} : Bool}, conversion_clash(U32.to_nat(U32.from_nat(cursor)), cursor, exact, equal))}
783 case Shape.BTrue{equal}:
784 sum_read_status(fuel, shape, cursor, accumulator, Core.read_flat(shape, tensor, U32.from_nat(cursor)),
785 {\{TransformTotality.ReadSuccess: successful => successful} :
786 TransformTotality.ReadSuccess<shape, tensor, U32.from_nat(cursor)> ->
787 {TransformTotality.read_succeeded(shape, Core.read_flat(shape, tensor, U32.from_nat(cursor))) == True{} : Bool}}(
788 TransformLaws.tensor_read_valid_success(shape, tensor, U32.from_nat(cursor), inside)), rec)