def TreeEq

bendtorch-core@0.1.0.0 · src/tensor/permute_build_proof.bend:668

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/main.bend as Storage
import bendtorch-core@0.1.0.0/src/tensor/contracts/binary_storage_proof.bend as Owned
import bendtorch-core@0.1.0.0/src/storage/LAWS.bend as StorageLaws
import bendtorch-core@0.1.0.0/src/storage/api.bend as Api

668def TreeEq(+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}, +depth: Nat, +base: Nat, -result: Array<F32> & (Array<F32> & Array<F32>)) -> Type:
669  {Pair.fst(Array<F32>, Array<F32> & Array<F32>, result) == spec(input, axes, fill, ops, count, depth, base) : Array<F32>} &
670    {Pair.snd(Array<F32>, Array<F32> & Array<F32>, result) == (Api.arr((Api.Right{} <> Owned.norm(U32.to_nat(Shape.count(input)), ops, Nil{})), ds, fill), Array.new(F32, 0n, 0.0)) : Array<F32> & Array<F32>}