def mapping_values

bendtorch-core@0.1.0.0 · src/autograd/reduce_PROOF.bend:142

import Base
import bendtorch-core@0.1.0.0/src/shape/core.bend as Shape
import bendtorch-core@0.1.0.0/src/tensor/core.bend as Core
import bendtorch-core@0.1.0.0/src/tensor/elementwise_totality.bend as Totality
import bendtorch-core@0.1.0.0/src/autograd/reduce_LAWS.bend as Laws

142def mapping_values(-input: Core.Dynamic, -target: Shape.Shape, -plan: Shape.BroadcastPlan, -output: Core.Dynamic,
143  model: {Totality.dimensions(output) == Shape.dimensions(target) : List<&2, U32>} &
144    (@+values: List<&2, F32> -> @-listed: Laws.Listed(input, values) ->
145      @+index: U32 -> @inside: {Nat.is_lt(U32.to_nat(index), Shape.logical_numel(Shape.dimensions(target))) == True{} : Bool} ->
146        {Core.checked_observe_dynamic(output, index) == Laws.planned_fiber(values, index, Shape.logical_numel(Totality.dimensions(input)), Done{plan}) : Maybe<&2, F32>})) ->
147  @+values: List<&2, F32> -> @-listed: Laws.Listed(input, values) ->
148    @+index: U32 -> @inside: {Nat.is_lt(U32.to_nat(index), Shape.logical_numel(Shape.dimensions(target))) == True{} : Bool} ->
149      {Core.checked_observe_dynamic(output, index) == Laws.planned_fiber(values, index, Shape.logical_numel(Totality.dimensions(input)), Done{plan}) : Maybe<&2, F32>}:
150  (dimensions, mapped) = model
151  mapped