def dot_extend

bendtorch-core@0.1.0.0 · src/tensor/matmul_parallel_proof.bend:47

import Base
import bendtorch-core@0.1.0.0/src/storage/model.bend as Model
import bendtorch-core@0.1.0.0/src/storage/refinement.bend as Refinement
import bendtorch-core@0.1.0.0/src/tensor/matmul.bend as Matrix
import bendtorch-core@0.1.0.0/src/tensor/dot_fold.bend as DotFold
import bendtorch-core@0.1.0.0/src/tensor/elementwise_parallel_proof.bend as Parallel

47def dot_extend(+rest: Nat, +dl: Nat, +dr: Nat, -A: Array<F32>, -B: Array<F32>, +inner: Nat, +columns: Nat,
48  +row: Nat, +column: Nat, +cursor: Nat, -accumulator: F32, -x: F32, -y: F32,
49  -ex: {Model.observe(F32, dl, A, Refinement.route(dl, Matrix.left_index(inner, row, cursor))) == Some{x} : Maybe<&2, F32>},
50  -ey: {Model.observe(F32, dr, B, Refinement.route(dr, Matrix.right_index(columns, column, cursor))) == Some{y} : Maybe<&2, F32>},
51  -result: F32 & (Array<F32> & Array<F32>),
52  -run: Parallel.Fact<DotRun<rest, dl, dr, A, B, inner, columns, row, column, 1n+cursor, F32.add(accumulator, F32.mul(x, y)), result>>) ->
53  Parallel.Fact<DotRun<1n+rest, dl, dr, A, B, inner, columns, row, column, cursor, accumulator, result>>:
54  Parallel.Fact{{\{DotRun: values => logical => fold => left_kept => right_kept =>
55    DotRun{DotFold.Factors{x, y} <> values, ArrStep{ex, ey, logical}, fold, left_kept, right_kept}} :
56      DotRun<rest, dl, dr, A, B, inner, columns, row, column, 1n+cursor, F32.add(accumulator, F32.mul(x, y)), result> ->
57      DotRun<1n+rest, dl, dr, A, B, inner, columns, row, column, cursor, accumulator, result>}(
58    {\{Parallel.Fact: p => p} : Parallel.Fact<DotRun<rest, dl, dr, A, B, inner, columns, row, column, 1n+cursor, F32.add(accumulator, F32.mul(x, y)), result>> ->
59      DotRun<rest, dl, dr, A, B, inner, columns, row, column, 1n+cursor, F32.add(accumulator, F32.mul(x, y)), result>}(run))}