def words_at

bendtorch-core@0.1.0.0 · src/autograd/reduce_replayed_proof.bend:969

import Base
import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape
import bendtorch-core@0.1.0.0/src/storage/LAWS.bend as StorageLaws
import bendtorch-core@0.1.0.0/src/storage/arith.bend as Arith
import bendtorch-core@0.1.0.0/src/tensor/contracts/replayed.bend as Replayed
import bendtorch-core@0.1.0.0/src/tensor/contracts/LAWS.bend as Laws
import bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend as ReduceLaws

969def words_at(+shape: Shape.Shape, +fill: F32, +ops: List<&2, StorageLaws.Op>, +count: Nat, +position: Nat,
970  below: {Nat.is_lt(position, count) == True{} : Bool}) ->
971  {ReduceLaws.word_at(Laws.words(shape, fill, ops, count), position) ==
972    Some{Replayed.value(shape, fill, ops, U32.from_nat(position))} : Maybe<&2, F32>}:
973  match count:
974    case 0n:
975      Empty.absurd({ReduceLaws.word_at(Nil{}, position) == Some{Replayed.value(shape, fill, ops, U32.from_nat(position))} : Maybe<&2, F32>},
976        Arith.lt_zero(position, below))
977    case 1n+previous:
978      words_step(shape, fill, ops, previous, position, below, Shape.bool_case(Nat.is_eq(position, previous)),
979        inside => words_at(shape, fill, ops, previous, position, inside))