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Approximate equality test #11

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Aug 16, 2023
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Approximate equality test #11

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19 changes: 19 additions & 0 deletions src/Architecture/DenseLayerOp.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,25 @@ function Base.:(==)(L1::DenseLayerOp, L2::DenseLayerOp)
L1.activation == L2.activation
end

function Base.:isapprox(L1::DenseLayerOp, L2::DenseLayerOp; atol::Real=0,
rtol=nothing)
if dim_in(L1) != dim_in(L2) || dim_out(L1) != dim_out(L2)
return false
end
if isnothing(rtol)
if iszero(atol)
N = promote_type(eltype(L1.weights), eltype(L2.weights),
eltype(L1.bias), eltype(L2.bias))
rtol = Base.rtoldefault(N)
else
rtol = zero(atol)
end
end
return isapprox(L1.weights, L2.weights; atol=atol, rtol=rtol) &&
isapprox(L1.bias, L2.bias; atol=atol, rtol=rtol) &&
L1.activation == L2.activation
end

dim_in(L::DenseLayerOp) = size(L.weights, 2)

dim_out(L::DenseLayerOp) = length(L.bias)
8 changes: 8 additions & 0 deletions src/Architecture/FeedforwardNetwork.jl
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Expand Up @@ -44,6 +44,14 @@ function Base.:(==)(N1::FeedforwardNetwork, N2::FeedforwardNetwork)
return N1.layers == N2.layers
end

function Base.:isapprox(N1::FeedforwardNetwork, N2::FeedforwardNetwork;
atol::Real=0, rtol=nothing)
if length(N1.layers) != length(N2.layers)
return false
end
return all(isapprox.(N1.layers, N2.layers; atol=atol, rtol=rtol))
end

dim_in(N::FeedforwardNetwork) = dim_in(first(N.layers))

dim_out(N::FeedforwardNetwork) = dim_out(last(N.layers))
14 changes: 14 additions & 0 deletions test/Architecture/DenseLayerOp.jl
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Expand Up @@ -23,6 +23,20 @@ L = DenseLayerOp(W, b, Id())
@test L != DenseLayerOp(W .+ 1, b, Id()) &&
L != DenseLayerOp(W, b .+ 1, Id()) &&
L != DenseLayerOp(W, b, ReLU())
@test L != DenseLayerOp(hcat(1), [1], Id())

# approximate equality
@test L ≈ DenseLayerOp(W, b, Id())
@test L ≈ DenseLayerOp(W .+ 1e-10, b, Id()) &&
L ≈ DenseLayerOp(W, b .+ 1e-10, Id()) &&
!≈(L, DenseLayerOp(W .+ 1e-10, b, Id()); rtol=1e-12) &&
!≈(L, DenseLayerOp(W, b .+ 1e-10, Id()); rtol=1e-12) &&
≈(L, DenseLayerOp(W .+ 1e-1, b, Id()); atol=1) &&
≈(L, DenseLayerOp(W, b .+ 1e-1, Id()); atol=1) &&
!(L ≈ DenseLayerOp(W .+ 1, b, Id())) &&
!(L ≈ DenseLayerOp(W, b .+ 1, Id())) &&
!(L ≈ DenseLayerOp(W, b, ReLU()))
@test !(L ≈ DenseLayerOp(hcat(1), [1], Id()))

# dimensions
@test dim_in(L) == 2
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5 changes: 5 additions & 0 deletions test/Architecture/FeedforwardNetwork.jl
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Expand Up @@ -32,6 +32,11 @@ N2 = FeedforwardNetwork([L1, L2])
@test N1 == FeedforwardNetwork([L1])
@test N1 != FeedforwardNetwork([L2])

# approximate equality
@test N1 ≈ FeedforwardNetwork([L1])
@test N1 ≈ FeedforwardNetwork([DenseLayerOp(W1 .+ 1e-10, b1, ReLU())])
@test !(N1 ≈ FeedforwardNetwork([L2]))

# dimensions
@test dim_in(N1) == 2 && dim_in(N2) == 2
@test dim_out(N1) == 3 && dim_out(N2) == 2
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