modules(m)

Return an iterator over non-leaf objects that can be reached by recursing m over the children given by functor .

Useful for applying a function (e.g. a regularizer) over specific modules or subsets of the parameters (e.g. the weights but not the biases).

Examples

			julia> m1 = Chain(Dense(28^2, 64), BatchNorm(64, relu));

julia> m2 = Chain(m1, Dense(64, 10))
Chain(
  Chain(
    Dense(784 => 64),                   # 50_240 parameters
    BatchNorm(64, relu),                # 128 parameters, plus 128
  ),
  Dense(64 => 10),                      # 650 parameters
)         # Total: 6 trainable arrays, 51_018 parameters,
          # plus 2 non-trainable, 128 parameters, summarysize 200.312 KiB.

julia> Flux.modules(m2)
7-element Vector{Any}:
 Chain(Chain(Dense(784 => 64), BatchNorm(64, relu)), Dense(64 => 10))  # 51_018 parameters, plus 128 non-trainable
 (Chain(Dense(784 => 64), BatchNorm(64, relu)), Dense(64 => 10))
 Chain(Dense(784 => 64), BatchNorm(64, relu))  # 50_368 parameters, plus 128 non-trainable
 (Dense(784 => 64), BatchNorm(64, relu))
 Dense(784 => 64)    # 50_240 parameters
 BatchNorm(64, relu)  # 128 parameters, plus 128 non-trainable
 Dense(64 => 10)     # 650 parameters

julia> L2(m) = sum(sum(abs2, l.weight) for l in Flux.modules(m) if l isa Dense)
L2 (generic function with 1 method)

julia> L2(m2) isa Float32
true