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Here it concludes that there are non-trainable arrays, but in fact the same weights appear in two layers, which throws off the counting:
julia> using Flux julia> let d = Dense(10 => 10) Chain(Embedding(10=>10), d, d) end Chain( Embedding(10 => 10), # 100 parameters Dense(10 => 10), # 110 parameters Dense(10 => 10), # 110 parameters ) # Total: 3 trainable arrays, 210 parameters, # plus 2 non-trainable, 110 parameters, summarysize 1.055 KiB. julia> Flux.destructure(ans) # length 210, correct (Float32[1.7007293, 0.66258854, -0.040887665, -1.2084905, -0.53106576 … 0.0, 0.0, 0.0, 0.0, 0.0], Restructure(Chain, ..., 210))
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Here it concludes that there are non-trainable arrays, but in fact the same weights appear in two layers, which throws off the counting:
The text was updated successfully, but these errors were encountered: