add namedparams

docs/src/models/regularisation.md

@@ -65,6 +65,14 @@ julia> sum(norm, ans)
 2.1166067f0
 ```
 
+One can also add regularisation only for weights by filtering out biases using `namedparams`.
+
+```
+ps = [p for (p, name) in Flux.namedparams(m) if !occursin(r"^b", name)]
+loss(x, y) = crossentropy(m(x), y) + sum(norm, p)
+```
+
 ```@docs
 Flux.activations
+Flux.namedparams
 ```

src/functor.jl

@@ -87,6 +87,39 @@ function params(m...)
   return ps
 end
 
+namedparams!(p, x::AbstractArray{<:Number}, name = :nothing, seen = IdSet()) = p[x] = name
+
+function namedparams!(p, x, name = :nothing, seen = IdSet())
+  x in seen && return
+  push!(seen, x)
+  for (name, child) in pairs(trainable(x))
+    name = name isa Symbol ? string(name) : ""
+    namedparams!(p, child, name, seen)
+  end
+end
+
+"""
+    namedparams(m...)
+
+Gate named parameters of the model
+
+# Examples
+```julia
+julia> Flux.namedparams(Chain(LSTM(1, 1)))
+IdDict{Any,String} with 5 entries:
+  Float32[0.0415536; 0.334981; 0.49804; 0.258496]    => "Wi"
+  Float32[0.0]                                       => ""
+  Float32[0.336735; -0.167129; -0.695561; -0.743882] => "Wh"
+  Float32[-0.979939, 1.0, 1.06309, -0.0981269]       => "b"
+  Float32[0.0]                                       => ""
+```
+"""
+function namedparams(m...)
+  ps = IdDict{Any, String}()
+  namedparams!(ps, m, :nothing)
+  return ps
+end
+
 # Deprecated stuff
 macro treelike(args...)
   functorm(args...)

test/utils.jl

@@ -95,6 +95,15 @@ end
   @test size.(params(r)) == [(5, 10), (5, 5), (5,), (5,)]
 end
 
+@testset "namedparams" begin
+  m = Dense(10, 5)
+  @test Flux.namedparams(m) == Base.IdDict(m.W => "W", m.b => "b")
+  m = RNN(10, 5)
+  @test Flux.namedparams(m) == Base.IdDict(m.cell.Wi => "Wi", m.cell.Wh => "Wh", m.init => "init", m.cell.b => "b")
+  c = Chain(m, m)
+  @test Flux.namedparams(c) == Base.IdDict(m.cell.Wi => "Wi", m.cell.Wh => "Wh", m.init => "init", m.cell.b => "b")
+end
+
 @testset "Basic Stacking" begin
   x = randn(3,3)
   stacked = stack([x, x], 2)