如何解決DimensionMismatch("Input channels must match! (3 vs. 1)")
1
epochs = 50
2
@epochs epochs Flux.train!(loss, params(model), train, ADAM(0.005), cb=throttle(evalcb, 10))
┌ Info: Epoch 1 └ @ Main C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\optimise\train.jl:121
DimensionMismatch("Input channels must match! (3 vs. 1)") Stacktrace: [1] DenseConvDims(::NTuple{4,Int64}, ::NTuple{4,Int64}; stride::Tuple{Int64,Int64}, padding::Tuple{Int64,Int64}, dilation::Tuple{Int64,Int64}, flipkernel::Bool) at C:\Users\Marc Juang\.julia\packages\NNlib\FAI3o\src\dim_helpers\DenseConvDims.jl:28 [2] #DenseConvDims#7 at C:\Users\Marc Juang\.julia\packages\NNlib\FAI3o\src\dim_helpers\DenseConvDims.jl:52 [inlined] [3] #adjoint#1816 at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\lib\nnlib.jl:17 [inlined] [4] _pullback at C:\Users\Marc Juang\.julia\packages\ZygoteRules\6nssF\src\adjoint.jl:53 [inlined] [5] Conv at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\layers\conv.jl:60 [inlined] [6] _pullback(::Zygote.Context, ::Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}}, ::Array{Float32,4}) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface2.jl:0 [7] applychain at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\layers\basic.jl:36 [inlined] [8] _pullback(::Zygote.Context, ::typeof(Flux.applychain), ::Tuple{Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},typeof(flatten),Dense{typeof(relu),CuArray{Float32,2,Nothing},CuArray{Float32,1,Nothing}},Dense{typeof(identity),CuArray{Float32,2,Nothing},CuArray{Float32,1,Nothing}},typeof(softmax)}, ::Array{Float32,4}) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface2.jl:0 [9] Chain at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\layers\basic.jl:38 [inlined] [10] _pullback(::Zygote.Context, ::Chain{Tuple{Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},Conv{2,2,typeof(relu),CuArray{Float32,4,Nothing},CuArray{Float32,1,Nothing}},MaxPool{2,4},typeof(flatten),Dense{typeof(relu),CuArray{Float32,2,Nothing},CuArray{Float32,1,Nothing}},Dense{typeof(identity),CuArray{Float32,2,Nothing},CuArray{Float32,1,Nothing}},typeof(softmax)}}, ::Array{Float32,4}) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface2.jl:0 [11] loss at .\In[7]:1 [inlined] [12] _pullback(::Zygote.Context, ::typeof(loss), ::Array{Float32,4}, ::Flux.OneHotMatrix{Array{Flux.OneHotVector,1}}) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface2.jl:0 [13] adjoint at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\lib\lib.jl:179 [inlined] [14] _pullback at C:\Users\Marc Juang\.julia\packages\ZygoteRules\6nssF\src\adjoint.jl:47 [inlined] [15] #17 at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\optimise\train.jl:89 [inlined] [16] _pullback(::Zygote.Context, ::Flux.Optimise.var"#17#25"{typeof(loss),Tuple{Array{Float32,4},Flux.OneHotMatrix{Array{Flux.OneHotVector,1}}}}) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface2.jl:0 [17] pullback(::Function, ::Zygote.Params) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface.jl:174 [18] gradient(::Function, ::Zygote.Params) at C:\Users\Marc Juang\.julia\packages\Zygote\YeCEW\src\compiler\interface.jl:54 [19] macro expansion at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\optimise\train.jl:88 [inlined] [20] macro expansion at C:\Users\Marc Juang\.julia\packages\Juno\f8hj2\src\progress.jl:134 [inlined] [21] train!(::typeof(loss), ::Zygote.Params, ::DataLoader, ::ADAM; cb::Flux.var"#throttled#20"{Flux.var"#throttled#16#21"{Bool,Bool,typeof(evalcb),Int64}}) at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\optimise\train.jl:81 [22] top-level scope at C:\Users\Marc Juang\.julia\packages\Flux\Fj3bt\src\optimise\train.jl:122 [23] top-level scope at C:\Users\Marc Juang\.julia\packages\Juno\f8hj2\src\progress.jl:134 [24] top-level scope at In[10]:2
回答列表
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2020/05/12 上午 09:10杜岳華贊同數：0不贊同數：0留言數：0
請注意 error message 的部分:
DimensionMismatch("Input channels must match! (3 vs. 1)")
輸入的維度不一致，請更改你的模型或是資料。