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Merged
merged 4 commits into from
Jul 26, 2021
Merged

use Flux.zeros32 #592

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893da46
use Flux.zeros32
DhairyaLGandhi Jul 20, 2021
5e9a0e6
typo
DhairyaLGandhi Jul 21, 2021
16be1e4
Fix Newton indexing
ChrisRackauckas Jul 26, 2021
b5cae13
cleaner
ChrisRackauckas Jul 26, 2021
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8 changes: 4 additions & 4 deletions src/fast_layers.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ initial_params(c::FastChain) = vcat(initial_params.(c.layers)...)

"""
FastDense(in,out,activation=identity;
bias = true ,initW = Flux.glorot_uniform, initb = Flux.zeros)
bias = true ,initW = Flux.glorot_uniform, initb = Flux.zeros32)

A Dense layer `activation.(W*x + b)` with input size `in` and output size `out`.
The `activation` function defaults to `identity`, meaning the layer is an affine
Expand All @@ -41,7 +41,7 @@ struct FastDense{F,F2} <: FastLayer
initial_params::F2
bias::Bool
function FastDense(in::Integer, out::Integer, σ = identity;
bias = true, initW = Flux.glorot_uniform, initb = Flux.zeros)
bias = true, initW = Flux.glorot_uniform, initb = Flux.zeros32)
temp = ((bias == false) ? vcat(vec(initW(out, in))) : vcat(vec(initW(out, in)),initb(out)))
initial_params() = temp
new{typeof(σ),typeof(initial_params)}(out,in,σ,initial_params,bias)
Expand Down Expand Up @@ -108,7 +108,7 @@ initial_params(f::FastDense) = f.initial_params()

"""
StaticDense(in,out,activation=identity;
initW = Flux.glorot_uniform, initb = Flux.zeros)
initW = Flux.glorot_uniform, initb = Flux.zeros32)

A Dense layer `activation.(W*x + b)` with input size `in` and output size `out`.
The `activation` function defaults to `identity`, meaning the layer is an affine
Expand All @@ -124,7 +124,7 @@ struct StaticDense{out,in,bias,F,F2} <: FastLayer
σ::F
initial_params::F2
function StaticDense(in::Integer, out::Integer, σ = identity;
bias::Bool = true, initW = Flux.glorot_uniform, initb = Flux.zeros)
bias::Bool = true, initW = Flux.glorot_uniform, initb = Flux.zeros32)
temp = ((bias == true ) ? vcat(vec(initW(out, in)),initb(out)) : vcat(vec(initW(out, in))) )
initial_params() = temp
new{out,in,bias,typeof(σ),typeof(initial_params)}(σ,initial_params)
Expand Down
4 changes: 2 additions & 2 deletions test/newton_neural_ode.jl
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Expand Up @@ -21,7 +21,7 @@ NN = Chain(Dense(n, 5n, tanh),
@info "ROCK4"
nODE = NeuralODE(NN, tspan, ROCK4(), reltol=1e-4, saveat=[tspan[end]])

loss_function(θ) = Flux.mse(y, nODE(x, θ))
loss_function(θ) = Flux.mse(y, nODE(x, θ)[end])
l1 = loss_function(nODE.p)

res = DiffEqFlux.sciml_train(loss_function, nODE.p, NewtonTrustRegion(), GalacticOptim.AutoZygote(), maxiters = 100, cb=cb)
Expand All @@ -35,7 +35,7 @@ NN = FastChain(FastDense(n, 5n, tanh),
@info "ROCK2"
nODE = NeuralODE(NN, tspan, ROCK2(), reltol=1e-4, saveat=[tspan[end]])

loss_function(θ) = Flux.mse(y, nODE(x, θ))
loss_function(θ) = Flux.mse(y, nODE(x, θ)[end])
l1 = loss_function(nODE.p)
optfunc = GalacticOptim.OptimizationFunction((x, p) -> loss_function(x), GalacticOptim.AutoZygote())
optprob = GalacticOptim.OptimizationProblem(optfunc, nODE.p,)
Expand Down