def run_extend

bendtorch-core@0.1.0.0 · src/tensor/batched_matmul_PROOF.bend:102

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/batched_matmul_LAWS.bend as Laws
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

102def run_extend(+rest: Nat, +dl: Nat, +dr: Nat, -A: Array<F32>, -B: Array<F32>, +ls: Nat, +rs: Nat, +lp: Nat, +rp: Nat,
103  -accumulator: F32, -x: F32, -y: F32,
104  -ex: {Model.observe(F32, dl, A, Refinement.route(dl, U32.from_nat(lp))) == Some{x} : Maybe<&2, F32>},
105  -ey: {Model.observe(F32, dr, B, Refinement.route(dr, U32.from_nat(rp))) == Some{y} : Maybe<&2, F32>},
106  -result: F32 & (Array<F32> & Array<F32>),
107  -run: Parallel.Fact<StridedRun<rest, dl, dr, A, B, ls, rs, Nat.add(ls, lp), Nat.add(rs, rp), F32.add(accumulator, F32.mul(x, y)), result>>) ->
108  Parallel.Fact<StridedRun<1n+rest, dl, dr, A, B, ls, rs, lp, rp, accumulator, result>>:
109  Parallel.Fact{{\{StridedRun: values => logical => fold => left_kept => right_kept =>
110    StridedRun{DotFold.Factors{x, y} <> values, Laws.StridedStep{ex, ey, logical}, fold, left_kept, right_kept}} :
111      StridedRun<rest, dl, dr, A, B, ls, rs, Nat.add(ls, lp), Nat.add(rs, rp), F32.add(accumulator, F32.mul(x, y)), result> ->
112      StridedRun<1n+rest, dl, dr, A, B, ls, rs, lp, rp, accumulator, result>}(
113    {\{Parallel.Fact: p => p} : Parallel.Fact<StridedRun<rest, dl, dr, A, B, ls, rs, Nat.add(ls, lp), Nat.add(rs, rp), F32.add(accumulator, F32.mul(x, y)), result>> ->
114      StridedRun<rest, dl, dr, A, B, ls, rs, Nat.add(ls, lp), Nat.add(rs, rp), F32.add(accumulator, F32.mul(x, y)), result>}(run))}