def tree_eq

bendtorch-core@0.1.0.0 · src/tensor/permute_build_proof.bend:765

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/tensor/permute_build.bend as Build
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/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

765def tree_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}, +depth: Nat, +base: Nat) -> TreeEq(input, axes, fill, ops, plan, ds, fits, count, exact, depth, base, Parallel.tree(~Build.Recipe, ~Array<F32>, ~Array<F32>, ~Build.cell, Build.recipe(Build.Request{input, axes}), depth, count, base, (Api.arr((Api.Right{} <> Owned.norm(U32.to_nat(Shape.count(input)), ops, Nil{})), ds, fill), Array.new(F32, 0n, 0.0)))):
766  match depth:
767    case 0n:
768      cell_eq(input, axes, fill, ops, plan, ds, fits, count, exact, base, Nat.is_lt(base, count), {==})
769    case 1n+inner:
770      match inner:
771        case 0n:
772          pair_eq(input, axes, fill, ops, plan, ds, fits, count, exact, base, Build.cell(Build.recipe(Build.Request{input, axes}), base, (Api.arr((Api.Right{} <> Owned.norm(U32.to_nat(Shape.count(input)), ops, Nil{})), ds, fill), Array.new(F32, 0n, 0.0)), Nat.is_lt(base, count)), cell_eq(input, axes, fill, ops, plan, ds, fits, count, exact, base, Nat.is_lt(base, count), {==}))
773        case 1n+below:
774          tree_node_eq(input, axes, fill, ops, plan, ds, fits, count, exact, inner, base, Parallel.tree(~Build.Recipe, ~Array<F32>, ~Array<F32>, ~Build.cell, Build.recipe(Build.Request{input, axes}), inner, count, base, (Api.arr((Api.Right{} <> Owned.norm(U32.to_nat(Shape.count(input)), ops, Nil{})), ds, fill), Array.new(F32, 0n, 0.0))), tree_eq(input, axes, fill, ops, plan, ds, fits, count, exact, inner, base), tree_eq(input, axes, fill, ops, plan, ds, fits, count, exact, inner, Nat.add(Model.capacity(inner), base)))