Comments (7)
darsnack
commented on May 22, 2024
Yeah there were some last minute changes to that PR to create this "backbone/head" structure. Those changes will need to be reflected in FastAI.jl. Thanks for catching this!
from fastai.jl.
cdsousa
commented on May 22, 2024
Doing backbone = Metalhead.ResNet50(pretrain=true).layers[1], which I thing is the correct way, gives an error in the methodmodel(method, backbone) part, something like
layer SkipConnection(Chain(.........), index 6 in Chain, gave an error with input of size (16, 16, 1024, 1)
Do you think this has some easy fix or will it take a big effort to fix?
I'd like to help but I have no knowledge about this stuff.
from fastai.jl.
darsnack
commented on May 22, 2024
It seems like it could be an easy fix, but the complete stack trace will tell us the actual error. Do you mind posting that?
from fastai.jl.
cdsousa
commented on May 22, 2024
Sure thing. Here it is:
┌ Error: layer SkipConnection(Chain(Parallel(+, Chain(Conv((1, 1), 1024 => 512, stride=2, bias=false), BatchNorm(512, relu), Conv((3, 3), 512 => 512, pad=1, bias=false), BatchNorm(512, relu), Conv((1, 1), 512 => 2048, bias=false), BatchNorm(2048, relu)), Chain(Conv((1, 1), 1024 => 2048, stride=2, bias=false), BatchNorm(2048, relu))), Chain(Parallel(+, Chain(Conv((1,
1), 2048 => 512, bias=false), BatchNorm(512, relu), Conv((3, 3), 512 => 512, pad=1, bias=false), BatchNorm(512, relu), Conv((1, 1), 512 => 2048, bias=false), BatchNorm(2048, relu)), identity), Parallel(+, Chain(Conv((1, 1), 2048 => 512, bias=false), BatchNorm(512, relu), Conv((3, 3), 512 => 512, pad=1, bias=false), BatchNorm(512, relu), Conv((1, 1), 512 => 2048, bias=false), BatchNorm(2048, relu)), identity), AdaptiveMeanPool((1, 1))), Chain(PixelShuffle(2), Chain(Conv((3, 3), 512 => 1024, pad=1), BatchNorm(1024, relu)))), #32), index 6 in Chain, gave an error with input of size (16, 16, 1024, 1)
└ @ Flux C:\Users\xxxxxxxxxxx\.julia\packages\Flux\Zz9RI\src\outputsize.jl:107
ERROR: LoadError: DimensionMismatch("mismatch in dimension 1 (expected 2 got 16)")
Stacktrace:
[1] _cs
@ .\abstractarray.jl:1626 [inlined]
[2] _cshp
@ .\abstractarray.jl:1622 [inlined]
[3] _cat_size_shape
@ .\abstractarray.jl:1602 [inlined]
[4] cat_size_shape(dims::Tuple{Bool, Bool, Bool}, X::Array{Flux.NilNumber.Nil, 4}, tail::Array{Flux.NilNumber.Nil, 4})
@ Base .\abstractarray.jl:1600
[5] _cat_t(::Int64, ::Type{Flux.NilNumber.Nil}, ::Array{Flux.NilNumber.Nil, 4}, ::Vararg{Array{Flux.NilNumber.Nil, 4}, N} where N)
@ Base .\abstractarray.jl:1646
[6] cat_t(::Type{Flux.NilNumber.Nil}, ::Array{Flux.NilNumber.Nil, 4}, ::Vararg{Array{Flux.NilNumber.Nil, 4}, N} where N;
dims::Int64)
@ Base .\abstractarray.jl:1643
[7] _cat
@ .\abstractarray.jl:1782 [inlined]
[8] #cat#129
@ .\abstractarray.jl:1781 [inlined]
[9] (::FastAI.Models.var"#32#34"{NTuple{4, Int64}})(mx::Array{Flux.NilNumber.Nil, 4}, x::Array{Flux.NilNumber.Nil, 4})
@ FastAI.Models C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:54
[10] (::SkipConnection{Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}}, Chain{Tuple{PixelShuffle, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}}}, FastAI.Models.var"#32#34"{NTuple{4, Int64}}})(input::Array{Flux.NilNumber.Nil, 4})
@ Flux C:\Users\xxxxxxxxxxx\.julia\packages\Flux\Zz9RI\src\layers\basic.jl:279
[11] outputsize(m::Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2,
4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}},
typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, SkipConnection{Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}}, Chain{Tuple{PixelShuffle, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}}}, FastAI.Models.var"#32#34"{NTuple{4, Int64}}}}}, inputsizes::NTuple{4, Int64}; padbatch::Bool)
@ Flux C:\Users\xxxxxxxxxxx\.julia\packages\Flux\Zz9RI\src\outputsize.jl:104
[12] outputsize(m::Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2,
4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}},
typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, SkipConnection{Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Chain{Tuple{Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}}, Chain{Tuple{PixelShuffle, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}}}, FastAI.Models.var"#32#34"{NTuple{4, Int64}}}}}, inputsizes::NTuple{4, Int64})
@ Flux C:\Users\xxxxxxxxxxx\.julia\packages\Flux\Zz9RI\src\outputsize.jl:101
[13] unet_from_layers(backbonelayers::Vector{Any}, insz::NTuple{4, Int64}; fdownscale::Int64, upsample::typeof(FastAI.Models.upsample_block_small), agg::Function, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ FastAI.Models C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:70
[14] unet_from_layers(backbonelayers::Vector{Any}, insz::NTuple{4, Int64}; fdownscale::Int64, upsample::typeof(FastAI.Models.upsample_block_small), agg::Function, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
(repeats 3 times)
@ FastAI.Models C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:64
[15] unet_from_layers(backbonelayers::Vector{Any}, insz::NTuple{4, Int64})
@ FastAI.Models C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:56
[16] UNetDynamic(backbone::Chain{Tuple{Conv{2, 2, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, MaxPool{2, 2}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity),
Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32,
Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros},
BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}}, inputsize::NTuple{4, Int64}, final::FastAI.Models.var"#29#30"{Int64}; kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ FastAI.Models C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:38
[17] UNetDynamic
@ C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:37 [inlined]
[18] #UNetDynamic#28
@ C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:45 [inlined]
[19] UNetDynamic
@ C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\models\unet.jl:44 [inlined]
[20] blockmodel(inblock::FastAI.ImageTensor{2}, outblock::FastAI.OneHotTensor{2, String}, backbone::Chain{Tuple{Conv{2, 2, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, MaxPool{2, 2}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32,
4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4,
typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32},
Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4},
Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32,
Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}}; kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ FastAI C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\datablock\models.jl:41
[21] blockmodel
@ C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\datablock\models.jl:41 [inlined]
[22] methodmodel(method::BlockMethod{Tuple{Image{2}, Mask{2, String}}, Tuple{ProjectiveTransforms{2}, ImagePreprocessing{FixedPointNumbers.N0f8, 3, ColorTypes.RGB{FixedPointNumbers.N0f8}, Float32}, OneHot{DataType}}, FastAI.OneHotTensor{2, String}}, backbone::Chain{Tuple{Conv{2, 2, typeof(identity), Array{Float32, 4}, Vector{Float32}}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, MaxPool{2, 2}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}},
Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu),
Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu),
Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4,
typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity),
Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, Parallel{typeof(+), Tuple{Chain{Tuple{Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}, Conv{2, 4, typeof(identity), Array{Float32, 4}, Flux.Zeros}, BatchNorm{typeof(relu), Vector{Float32}, Float32, Vector{Float32}}}}, typeof(identity)}}, AdaptiveMeanPool{4, 2}}})
@ FastAI C:\Users\xxxxxxxxxxx\.julia\packages\FastAI\4mXj2\src\datablock\method.jl:50
[23] top-level scope
@ c:\Users\xxxxxxxxxxx\yyyyyyyyyyy\imgsegm.jl:47
in expression starting at c:\Users\xxxxxxxxxxx\yyyyyyyyyyy\imgsegm.jl:47
I can also post the display of the ResNet50.
from fastai.jl.
DhairyaLGandhi
commented on May 22, 2024
We can definitely improve the error by not showing the layer in there, and just reference to it
from fastai.jl.
darsnack
commented on May 22, 2024
I agree, we should use a compact representation of the layer instead of the full thing. Probably some \n characters in there too cause there are three separate pieces of info being delivered in a single line.
@cdsousa The quick fix for user code should be
backbone = Metalhead.ResNet50(pretrain=true).layers[1][1:(end - 1)]The real issue is that the AdaptiveMeanPool should not be part of the backbone. The actual fix will be to Metalhead.jl to change these lines to be
return Chain(Chain(layers...),
Chain(AdaptiveMeanPool((1, 1)), flatten, Dense(inplanes, nclasses)))If you would like to make a PR, then we'd appreciate the help!
from fastai.jl.
cdsousa
commented on May 22, 2024
Thanks @lorenzoh for doing the fix. I didn't proceed doing the PR because I was not able to check if everything fully worked as my laptop has only 4GB of VRAM which was not enough to run the training.
from fastai.jl.
Related Issues (20)
- Log to TensorBoard link in TOC
- Log to TensorBoard link in TOC HOT 2
- Faster image pipelines
- Benchmark image pipelines against ffcv
- Docs aren't working correctly. HOT 2
- Windows CI failure HOT 4
- Make a subpackage for Makie support HOT 1
- Deprecate implicit parameters
- Model registry
- Support batch-level transformations in `Encoding`s HOT 9
- `TaskDataset` does not sub-type `MLUtils.AbstractDataContainer` HOT 3
- `Quickstart` tutorial no longer works (`loaddataset` doesn't exist) HOT 6
- Collaborative filtering example HOT 2
- the dataset is deleted right after download in Windows10 HOT 2
- loading datasets fails under proxy, but Base.download works HOT 1
- Broken links on Readme page HOT 1
- unresponsive docs HOT 1
- Dead links in documentation HOT 1
- Use PrecompileTools.jl HOT 9
- Custom learning tasks tutorial gives error
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