Exception raised when debugging Flux.jl code

Tooling VS Code
1

The below code runs fine but when I run it under the VS Code debugger I get an ErrorException: Method is @generated; try ‘code_lowered’ instead.

using Flux

input = rand(28)
label = rand(10)

model = Chain(
  Dense(28 => 10)
)

model(input)

opt_state = Flux.setup(Adam(), model)

for epoch in 1:100
  Flux.train!(model, [(input, label)], opt_state) do m, x, y
    Flux.mse(m(x), y)
  end
end

Stacktrace:
 [1] train!(loss::var"#1#2", model::Chain{Tuple{Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, data::Vector{Tuple{Vector{Float64}, Vector{Float64}}}, opt::NamedTuple{(:layers,), Tuple{Tuple{NamedTuple{(:weight, :bias, :σ), Tuple{Optimisers.Leaf{Optimisers.Adam{Float64}, Tuple{Matrix{Float32}, Matrix{Float32}, Tuple{Float64, Float64}}}, Optimisers.Leaf{Optimisers.Adam{Float64}, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float64, Float64}}}, Tuple{}}}}}}; cb::Nothing)
   @ Flux.Train ~/.julia/packages/ProgressLogging/6KXlp/src/ProgressLogging.jl:385
 [2] train!(loss::var"#1#2", model::Chain{Tuple{Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, data::Vector{Tuple{Vector{Float64}, Vector{Float64}}}, opt::NamedTuple{(:layers,), Tuple{Tuple{NamedTuple{(:weight, :bias, :σ), Tuple{Optimisers.Leaf{Optimisers.Adam{Float64}, Tuple{Matrix{Float32}, Matrix{Float32}, Tuple{Float64, Float64}}}, Optimisers.Leaf{Optimisers.Adam{Float64}, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float64, Float64}}}, Tuple{}}}}}})
   @ Flux.Train ~/.julia/packages/Flux/FWgS0/src/train.jl:102
 [3] top-level scope
   @ ~/Code/grokking-drl/test_flux.jl:15

  [052768ef] CUDA v4.1.4
  [587475ba] Flux v0.13.15
  [b98c9c47] Pipe v1.3.0
  [438e738f] PyCall v1.95.1

I’m using Julia v1.8.5.