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Added test that compares symbolic pullback to zygote pullback.
Flipped order of functions.
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using SymbolicNeuralNetworks | ||
using SymbolicNeuralNetworks: _get_params, _get_contents | ||
using AbstractNeuralNetworks | ||
using Symbolics | ||
using GeometricMachineLearning: ZygotePullback | ||
using Test | ||
import Random | ||
Random.seed!(123) | ||
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compare_values(arr1::Array, arr2::Array) = @test arr1 ≈ arr2 | ||
function compare_values(nt1::NamedTuple, nt2::NamedTuple) | ||
@assert keys(nt1) == keys(nt2) | ||
NamedTuple{keys(nt1)}((compare_values(arr1, arr2) for (arr1, arr2) in zip(values(nt1), values(nt2)))) | ||
end | ||
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function compare_symbolic_pullback_to_zygote_pullback(input_dim::Integer, output_dim::Integer, second_dim::Integer=1) | ||
c = Chain(Dense(input_dim, output_dim, tanh)) | ||
nn = NeuralNetwork(c) | ||
snn = SymbolicNeuralNetwork(nn) | ||
loss = FeedForwardLoss() | ||
spb = SymbolicPullback(snn, loss) | ||
input_output = (rand(input_dim, second_dim), rand(output_dim, second_dim)) | ||
loss_and_pullback = spb(nn.params, nn.model, input_output) | ||
# note that we apply the second argument to another input `1` | ||
pb_values = loss_and_pullback[2](1) | ||
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zpb = ZygotePullback(loss) | ||
loss_and_pullback_zygote = zpb(nn.params, nn.model, input_output) | ||
pb_values_zygote = loss_and_pullback_zygote[2](1) |> _get_contents |> _get_params | ||
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compare_values(pb_values, pb_values_zygote) | ||
end | ||
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for input_dim ∈ (2, 3) | ||
for output_dim ∈ (1, 2) | ||
compare_symbolic_pullback_to_zygote_pullback(input_dim, output_dim) | ||
end | ||
end |
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