def tree_join_eq

bendtorch-core@0.1.0.0 · src/tensor/permute_build_proof.bend:725

import Base
import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape
import bendtorch-core@0.1.0.0/src/tensor/layout.bend as Layout
import bendtorch-core@0.1.0.0/src/storage/model.bend as Model
import bendtorch-core@0.1.0.0/src/storage/main.bend as Storage
import bendtorch-core@0.1.0.0/src/tensor/parallel.bend as Parallel
import bendtorch-core@0.1.0.0/src/storage/LAWS.bend as StorageLaws

725def tree_join_eq(+input: Shape.Shape, +axes: List<&2, U32>, +fill: F32, +ops: List<&2, StorageLaws.Op>, +plan: Layout.Plan<input, axes>, +ds: Nat, +fits: {Storage.bounds(ds, U32.to_nat(Shape.count(input))) == True{} : Bool}, +count: Nat, +exact: {count == Shape.logical_numel(Shape.dimensions(Layout.output(input, axes, plan))) : Nat}, +inner: Nat, +base: Nat, -a: Array<F32>, high: Array<F32> & (Array<F32> & Array<F32>),
726  ea: {a == spec(input, axes, fill, ops, count, inner, base) : Array<F32>},
727  facts: TreeEq(input, axes, fill, ops, plan, ds, fits, count, exact, inner, Nat.add(Model.capacity(inner), base), high)) ->
728  TreeEq(input, axes, fill, ops, plan, ds, fits, count, exact, 1n+inner, base, Parallel.join(~(Array<F32> & Array<F32>), a, high)):
729  (b, inputs) = high
730  (eb, kept) = facts
731  (%Equal.sym(Array<F32>, a, spec(input, axes, fill, ops, count, inner, base), ea) : {ANode{_, b} == ANode{spec(input, axes, fill, ops, count, inner, base), spec(input, axes, fill, ops, count, inner, Nat.add(Model.capacity(inner), base))} : Array<F32>}
732   %Equal.sym(Array<F32>, b, spec(input, axes, fill, ops, count, inner, Nat.add(Model.capacity(inner), base)), eb) : {ANode{spec(input, axes, fill, ops, count, inner, base), _} == ANode{spec(input, axes, fill, ops, count, inner, base), spec(input, axes, fill, ops, count, inner, Nat.add(Model.capacity(inner), base))} : Array<F32>}
733   {==}, kept)