def cell_spec

bendtorch-core@0.1.0.0 · src/tensor/batched_matmul_PROOF.bend:266

import Base
import bendtorch-core@0.1.0.0/src/storage/model.bend as Model
import bendtorch-core@0.1.0.0/src/tensor/matmul.bend as Matrix
import bendtorch-core@0.1.0.0/src/tensor/batched_matmul.bend as Batched
import bendtorch-core@0.1.0.0/src/tensor/batched_matmul_LAWS.bend as Laws
import bendtorch-core@0.1.0.0/src/tensor/elementwise_parallel_proof.bend as Parallel

266# What the cell function computes is what CellSpec names.
267def cell_spec(+lo: Matrix.Order, +ro: Matrix.Order, +inner: Nat, +rows: Nat, +columns: Nat, +l1: Nat, +l2: Nat, +r1: Nat, +r2: Nat, +o2: Nat,
268  +position: Nat, +dl: Nat, +dr: Nat, A: Array<F32>, B: Array<F32>, inside: Bool, -observed: Maybe<&2, F32>,
269  -computed: {observed == Some{Pair.fst(F32, Array<F32> & Array<F32>, cell_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, A, B, inside))} : Maybe<&2, F32>},
270  -left_valid: Model.Balanced(F32, dl, A), -right_valid: Model.Balanced(F32, dr, B)) ->
271  Parallel.Fact<Laws.CellSpec(dl, dr, A, B, lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, inside, observed)>:
272  match inside:
273    case False{}:
274      Parallel.Fact{computed}
275    case True{}:
276      Parallel.Fact{{\{StridedRun: values => logical => fold => left_kept => right_kept =>
277        Laws.CellAt{Pair.fst(F32, Array<F32> & Array<F32>, cell_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, A, B, True{})),
278          computed, values, logical, fold}} :
279        StridedRun<inner, dl, dr, A, B, Matrix.stride(lo, rows), Matrix.stride(ro, columns),
280          Batched.left_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position),
281          Batched.right_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position), 0.0,
282          cell_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, A, B, True{})> ->
283        Laws.CellAt<dl, dr, A, B, lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, observed>}(
284        {\{Parallel.Fact: p => p} :
285          Parallel.Fact<StridedRun<inner, dl, dr, A, B, Matrix.stride(lo, rows), Matrix.stride(ro, columns),
286            Batched.left_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position),
287            Batched.right_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position), 0.0,
288            cell_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, A, B, True{})>> ->
289          StridedRun<inner, dl, dr, A, B, Matrix.stride(lo, rows), Matrix.stride(ro, columns),
290            Batched.left_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position),
291            Batched.right_start(Laws.layout_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2), position), 0.0,
292            cell_of(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, A, B, True{})>}(
293          dot_run(lo, ro, inner, rows, columns, l1, l2, r1, r2, o2, position, dl, dr, A, B, left_valid, right_valid)))}