type StridedRun

bendtorch-core@0.1.0.0 · src/tensor/batched_matmul_PROOF.bend:93

import Base
import bendtorch-core@0.1.0.0/src/tensor/matmul.bend as Matrix
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

93# A run of `Matrix.product_run` from offsets lp and rp: its total folds the
94# factor pairs it read, and both arrays come back unchanged.
95type StridedRun<-fuel: Nat, -dl: Nat, -dr: Nat, -A: Array<F32>, -B: Array<F32>, -ls: Nat, -rs: Nat, -lp: Nat, -rp: Nat,
96  -accumulator: F32, -result: F32 & (Array<F32> & Array<F32>)> is Data:
97  StridedRun{-values: List<&2, DotFold.Factors>, -logical: Laws.Strided(fuel, dl, dr, A, B, ls, rs, lp, rp, values),
98    -fold: {Pair.fst(F32, Array<F32> & Array<F32>, result) == DotFold.dot_fold(values, accumulator) : F32},
99    -left_kept: {Pair.fst(Array<F32>, Array<F32>, Pair.snd(F32, Array<F32> & Array<F32>, result)) == A : Array<F32>},
100    -right_kept: {Pair.snd(Array<F32>, Array<F32>, Pair.snd(F32, Array<F32> & Array<F32>, result)) == B : Array<F32>}}