TypeError in JETAnalyzer

[goerch]

When checking this MWE

using Flux
using Dates

channels = 64
in_channels = 3
num_channels = [3,64,64,128,128,256,256,512,512]

# discriminator

function block((in_channels,out_channels); stride = 1, use_batch_norm = true)
    layers = []
    push!(layers, Conv((3,3),in_channels => out_channels,pad = 1,stride = stride))
    if use_batch_norm
        push!(layers, BatchNorm(out_channels))
    end
    #push!(layers, x -> leakyrelu.(x,0.2f0))
    return layers
end

discriminator = Chain(
    reduce(vcat,[block(num_channels[i] => num_channels[i+1];
            stride = 1 + (i+1) % 2,
            use_batch_norm = i!=1) for i = 1:length(num_channels)-1 ])...,
    AdaptiveMeanPool((1,1)),
    Conv((1,1), num_channels[end] => 1024),
    #x -> leakyrelu.(x,0.2f0),
    Conv((1,1), 1024 => 1),
) |> gpu


function resblock(channels)
    return SkipConnection(Chain(
            Conv((3,3),channels => channels, pad=1),
            BatchNorm(channels),
            #Prelu(),
            Conv((3,3),channels => channels, pad=1),
            BatchNorm(channels),
        )
        , +)
end


function upsample(in_channels, up_scale)
    return [
        Conv((3,3),in_channels => in_channels*up_scale^2,pad=1),
        PixelShuffle(up_scale),
        #Prelu(),
    ]
end

generator = Chain(
    Conv((9,9),3 => channels, pad = 4),
    #Prelu(),

    SkipConnection(Chain(
        # test with different number of residual blocks
        resblock(channels),
        resblock(channels),
        resblock(channels),
        resblock(channels),
        resblock(channels),
        Conv((3,3),channels => channels, pad=1),
        BatchNorm(channels)),+),
    upsample(channels, 2)...,
    upsample(channels, 2)...,
    Conv((9,9),channels => 3,σ, pad=4),
) |> gpu;

hr_images = randn(Float32,88,88,3,32)
lr_images = randn(Float32,22,22,3,32)

hr_images = gpu(hr_images)
lr_images = gpu(lr_images)

# check foreward
@show sum(discriminator(generator(lr_images)))

params_g = Flux.params(generator)

@info "generator $(Dates.now())"

# Taking gradient of generator
loss_g, back = @time Flux.pullback(params_g) do
    sum(discriminator(generator(lr_images)))
end

with report_file I got

ERROR: TypeError: in typeassert, expected Vector{Any}, got a value of type Vector{Core.MethodInstance}
Stacktrace:
  [1] finish(me::Core.Compiler.InferenceState, analyzer::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}})
    @ JET C:\Users\Win10\.julia\packages\JET\iloOP\src\abstractinterpret\typeinfer.jl:703
  [2] _typeinf(analyzer::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, frame::Core.Compiler.InferenceState)
    @ JET C:\Users\Win10\.julia\packages\JET\iloOP\src\abstractinterpret\typeinfer.jl:613
  [3] typeinf(interp::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, frame::Core.Compiler.InferenceState)
    @ Core.Compiler .\compiler\typeinfer.jl:209
  [4] typeinf(analyzer::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, frame::Core.Compiler.InferenceState)
    @ JET C:\Users\Win10\.julia\packages\JET\iloOP\src\abstractinterpret\typeinfer.jl:528
  [5] typeinf_edge(interp::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, method::Method, atypes::Any, sparams::Core.SimpleVector, caller::Core.Compiler.InferenceState)
    @ Core.Compiler .\compiler\typeinfer.jl:823
  [6] typeinf_edge
    @ C:\Users\Win10\.julia\packages\JET\iloOP\src\abstractinterpret\typeinfer.jl:347 [inlined]
  [7] abstract_call_method(interp::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, method::Method, sig::Any, sparams::Core.SimpleVector, hardlimit::Bool, sv::Core.Compiler.InferenceState)
    @ Core.Compiler .\compiler\abstractinterpretation.jl:504
  [8] abstract_call_method
    @ C:\Users\Win10\.julia\packages\JET\iloOP\src\abstractinterpret\typeinfer.jl:170 [inlined]
  [9] abstract_call_gf_by_type(interp::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, f::Any, fargs::Vector{Any}, argtypes::Vector{Any}, atype::Any, sv::Core.Compiler.InferenceState, max_methods::Int64)
    @ Core.Compiler .\compiler\abstractinterpretation.jl:105
 [10] abstract_call_gf_by_type
    @ C:\Users\Win10\.julia\packages\JET\iloOP\src\analyzers\jetanalyzer.jl:331 [inlined]
 [11] abstract_call_known(interp::JET.JETAnalyzer{JET.BasicPass{typeof(JET.basic_function_filter)}}, f::Any, fargs::Vector{Any}, argtypes::Vector{Any}, sv::Core.Compiler.InferenceState, max_methods::Int64)
    @ Core.Compiler .\compiler\abstractinterpretation.jl:1339

on Julia 1.7.0-rc3 and 1.8.0-DEV.