Zygote has a problem of derivation in the loss function

I have a problem with Flux. Unfortunately Zygote cannot derive my loss function and I am not sure what it is. It would be nice if someone could help me with this problem.
My loss function looks like this:

function loss_ungelabelt2(X,Y)
    a_list = Float32[]
    b_list = Float32[]
    mix_res = Float32[]
    λ::Float32 = 0.3
    loss::Float32 = 0
    for i in 1:2  #eigentlich size(X,4)  
        a = X[:,:,:,rand(1:size(X,4))] 
        b = X[:,:,:,rand(1:size(X,4))]
        mix = λ .* a .+ (1 - λ) .* b
        mix_res=reshape([mix_res...,mix...],size(mix)...,:) # einzelne Elemente 
    y_mix = model(mix_res)
    y_a = model(a_list)
    y_b = model(b_list)
    println("a", size(y_a))
    println("b", size(y_b))
    y_mix_ab =  λ .* y_a .+ (1 - λ) .* y_b 
    quadrat_loss = sum(abs2,y_mix .- y_mix_ab)
    return quadrat_loss

I get this error:

MethodError: no method matching size(::NTuple{784,Float32})
Closest candidates are:
  size(::Tuple, !Matched::Integer) at tuple.jl:22
  size(!Matched::Flux.OneHotVector) at /Users/lisa/.julia/packages/Flux/IjMZL/src/onehot.jl:8
  size(!Matched::ZMQ.Message) at /Users/lisa/.julia/packages/ZMQ/R3wSD/src/message.jl:95

 [1] unbroadcast(::Array{Float32,3}, ::NTuple{784,Float32}) at /Users/lisa/.julia/packages/Zygote/seGHk/src/lib/broadcast.jl:53
 [2] (::Zygote.var"#1107#1109"{NTuple{784,Float32}})(::Array{Float32,3}) at /Users/lisa/.julia/packages/Zygote/seGHk/src/lib/broadcast.jl:74
 [3] map(::Zygote.var"#1107#1109"{NTuple{784,Float32}}, ::Tuple{Array{Float32,3},Array{Float32,3}}) at ./tuple.jl:158
 [4] (::Zygote.var"#1106#1108"{Tuple{Array{Float32,3},Array{Float32,3}}})(::NTuple{784,Float32}) at /Users/lisa/.julia/packages/Zygote/seGHk/src/lib/broadcast.jl:74
 [5] (::Zygote.var"#3852#back#1110"{Zygote.var"#1106#1108"{Tuple{Array{Float32,3},Array{Float32,3}}}})(::NTuple{784,Float32}) at /Users/lisa/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49
 [6] loss_ungelabelt2 at ./In[13]:14 [inlined]
 [7] (::typeof(∂(loss_ungelabelt2)))(::Float32) at /Users/lisa/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [8] (::Zygote.var"#41#42"{typeof(∂(loss_ungelabelt2))})(::Float32) at /Users/lisa/.julia/packages/Zygote/seGHk/src/compiler/interface.jl:45
 [9] gradient(::Function, ::Array{Float32,4}, ::Vararg{Any,N} where N) at /Users/lisa/.julia/packages/Zygote/seGHk/src/compiler/interface.jl:54
 [10] top-level scope at In[14]:1
 [11] include_string(::Function, ::Module, ::String, ::String) at ./loading.jl:1091

I would be very grateful for an answer.

what abt this size(::NTuple{N,T}) where {N, T} = N

What exactly do you mean by this?
Because I am not quite sure where this mistake comes from. The sizes in the code are multidimensional. And only the lengths are 784.

the size function does not support arguments of type NTuple{N,Float32}. @xiaodai 's solution is to add a method to size as: size(::NTuple{N,T}) where {N, T} = N. It should solve the problem reported i.e. missing a size method.

Ah okay. Thanks a lot!
Sry, I don’t usually work with Julia and I am a little helpless.
But if I add the line Base.size(::NTuple{N,T}) where {N, T} = N I get an argumentError: invalid tuple dimension 2

You could do that, it might fix it. (Or it might not)
Its not the real solution though, and it is kind of a bad thing to do, it is type piracy (overloading a function you don’t own on a set of types none of which you own).

This is a bug in Zygote. you should report it on the Zygote issue tracker.
Its not something you have done wrong.

I did some poking
The error is this line https://github.com/FluxML/Zygote.jl/blob/ed366f32c0f520567526040d9f8acaf0d83613c3/src/lib/broadcast.jl#L52
where zygote tries to take size(x̄)
is turning out to be a Tuple which don’t have size defined on them.
Only length.
However, that is just a symptom, as that line should be fine,
because if x is an Array,
then should also be an Array.

So something is going wrong somewhere else that is causing it to be a Tuple.
It needs to be fixed in Zygote.

Thank you for the effort! I have already reported it and I hope it can be fixed without much effort and time.