Scalar indexing error using prod(...)

This might not be a bug, but at the least it seems to be a mysterious error.

I'm using Flux and in the loss function (which is processed by Zygote and so uses ChainRules.jl), I'm using prod. The surprising thing was that it ran for several iterations before failing with a scalar index error.

I'm guessing the error happens when it goes into this branch because it finds a zero somewhere. That would explain why some iterations occur before hitting this error. I don't know if the code can be changed to avoid scalar indexing, or maybe a more informative error, or maybe it's just something I need to better understand.

Stacktrace:
  [1] error(s::String)
    @ Base .\error.jl:35
  [2] assertscalar(op::String)
    @ GPUArraysCore C:\Users\joel\.julia\packages\GPUArraysCore\uOYfN\src\GPUArraysCore.jl:103
  [3] getindex(::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, ::Int64, ::Int64)
    @ GPUArrays C:\Users\joel\.julia\packages\GPUArrays\5XhED\src\host\indexing.jl:9
  [4] maybeview
    @ .\views.jl:149 [inlined]
  [5] ∇prod_dims!(dx::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, #unused#::Val{1}, x::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, dy::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, y::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
    @ ChainRules C:\Users\joel\.julia\packages\ChainRules\9sNmB\src\rulesets\Base\mapreduce.jl:287
  [6] ∇prod_dims(vald::Val{1}, x::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, dy::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, y::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
    @ ChainRules C:\Users\joel\.julia\packages\ChainRules\9sNmB\src\rulesets\Base\mapreduce.jl:278
  [7] (::ChainRules.var"#1683#1686"{CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, Int64, CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, ChainRulesCore.ProjectTo{AbstractArray, NamedTuple{(:element, :axes), Tuple{ChainRulesCore.ProjectTo{Float32, NamedTuple{(), Tuple{}}}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}}}}, CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}})()
    @ ChainRules C:\Users\joel\.julia\packages\ChainRules\9sNmB\src\rulesets\Base\mapreduce.jl:265
  [8] unthunk
    @ C:\Users\joel\.julia\packages\ChainRulesCore\0t04l\src\tangent_types\thunks.jl:204 [inlined]
  [9] unthunk
    @ C:\Users\joel\.julia\packages\ChainRulesCore\0t04l\src\tangent_types\thunks.jl:237 [inlined]
 [10] wrap_chainrules_output
    @ C:\Users\joel\.julia\packages\Zygote\4rucm\src\compiler\chainrules.jl:110 [inlined]
 [11] map
    @ .\tuple.jl:274 [inlined]
 [12] wrap_chainrules_output
    @ C:\Users\joel\.julia\packages\Zygote\4rucm\src\compiler\chainrules.jl:111 [inlined]
 [13] ZBack
    @ C:\Users\joel\.julia\packages\Zygote\4rucm\src\compiler\chainrules.jl:211 [inlined]
 [14] (::Zygote.var"#kw_zpullback#53"{ChainRules.var"#prod_pullback#1684"{Int64, CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}, ChainRulesCore.ProjectTo{AbstractArray, NamedTuple{(:element, :axes), Tuple{ChainRulesCore.ProjectTo{Float32, NamedTuple{(), Tuple{}}}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}}}}, CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}}})(dy::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
    @ Zygote C:\Users\joel\.julia\packages\Zygote\4rucm\src\compiler\chainrules.jl:237
...

Start by reproducing the prod failure with the Flux, Zygote, ChainRules, and CuArray setup shown in the stack trace. Read src/rulesets/Base/mapreduce.jl around lines 265 and 287, then determine the expected behavior for zero-containing inputs. Done means either avoiding the scalar-indexing error or documenting and reporting it more clearly.