Remove _parent

src/loading.jl

@@ -14,9 +14,6 @@ function loadleaf!(dst::AbstractArray, src::AbstractArray, err)
   copyto!(dst, src)
 end
 
-_parent(x) = x
-_parent(x::AbstractArray) = parent(x)
-
 _tie_check(dst::Bool, src::AbstractArray) = iszero(dst) ||
   error("Encountered tied parameter with boolean source at some nodes and non-boolean sources at others.")
 _tie_check(dst::AbstractArray, src::Bool) = (iszero(dst) && iszero(src)) ||
@@ -79,7 +76,7 @@ function loadmodel!(dst, src; cache = Base.IdSet())
 
   err = DimensionMismatch("Tried to load $src into $dst but the parameter sizes do not match.")
   foreach(ldsts, lsrcs) do ldst, lsrc
-    if _parent(ldst) in cache # we already loaded this parameter before
+    if ldst in cache # we already loaded this parameter before
       _tie_check(ldst, lsrc) && return ldst
     elseif Functors.isleaf(ldst) # our first time loading this leaf
       push!(cache, ldst)

test/utils.jl

@@ -483,21 +483,16 @@ end
     @test chain2[2].bias != chain1[2].bias
 
     # test shared weights
-    encoder_dst = Chain(Dense(10 => 5), Dense(5 => 2))
-    decoder_dst = Chain(Dense(transpose(encoder_dst[2].weight)),
-                        Dense(permutedims(encoder_dst[1].weight)))
-    encoder_src = Chain(Dense(10 => 5), Dense(5 => 2))
-    decoder_src = Chain(Dense(transpose(encoder_src[2].weight)),
-                        Dense(5 => 10))
+    shared_dst = Dense(10 => 10)
+    shared_src = Dense(10 => 10)
     # matched weights are okay
-    m1 = Chain(encoder_dst, decoder_dst)
-    m2 = Chain(encoder_src, decoder_src)
+    m1 = Chain(shared_dst, Dense(shared_dst.weight))
+    m2 = Chain(shared_src, Dense(shared_src.weight))
     loadmodel!(m1, m2)
-    @test m1[1][2].weight === parent(m1[2][1].weight)
-    @test m1[1][1].weight == m2[1][1].weight
-    @test m1[1][1].weight != permutedims(m1[2][2].weight)
+    @test m1[1].weight === m1[2].weight
+    @test m1[1].weight == m2[2].weight
     # mismatched weights are an error
-    m2 = Chain(Chain(Dense(10 => 5), Dense(5 => 2)), Chain(Dense(2 => 5), Dense(5 => 10)))
+    m2 = Chain(Dense(10 => 10), Dense(10 => 10))
     @test_throws ErrorException loadmodel!(m1, m2)
     # loading into tied weights with absent parameter is okay when the dst == zero
     b = Flux.zeros32(5)