def product_tree_certified
bendtorch-core@0.1.0.0 · src/tensor/matmul.bend:674
import bendtorch-core@0.1.0.0/src/tensor/matmul.bend as Matmul
import Base
import bendtorch-core@0.1.0.0/src/tensor/parallel.bend as Parallel
674def product_tree_certified(+layout: Layout, +depth: Nat, +count: Nat, +base: Nat, state: Array<F32> & Array<F32>) ->
675 Parallel.Certified<(Array<F32> & Array<F32>), depth, product_tree(layout, depth, count, base, state)>:
676 match depth:
677 case 0n:
678 Parallel.tree_certified(~Layout, ~Array<F32>, ~Array<F32>, ~product_cell_at, layout, 0n, count, base, state)
679 case 1n+d1:
680 match d1:
681 case 0n:
682 Parallel.tree_certified(~Layout, ~Array<F32>, ~Array<F32>, ~product_cell_at, layout, 1n, count, base, state)
683 case 1n+d2:
684 match d2:
685 case 0n:
686 Parallel.tree_certified(~Layout, ~Array<F32>, ~Array<F32>, ~product_cell_at, layout, 2n, count, base, state)
687 case 1n+d3:
688 match d3:
689 case 0n:
690 block_or_tree_certified(layout, count, base, state, one_row(layout, count, base))
691 case 1n+d4:
692 Parallel.node_certified(~Array<F32>, ~Array<F32>, d1, l => r => product_tree(layout, d1, count, Parallel.upper(d1, base), (l, r)),
693 product_tree(layout, d1, count, base, state), product_tree_certified(layout, d1, count, base, state),
694 l => r => product_tree_certified(layout, d1, count, Parallel.upper(d1, base), (l, r)))