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Merge pull request #22 from LuxDL/fm/tc
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Type check for kwargs
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@avik-pal
avik-pal authored Mar 10, 2024
2 parents 63010b1 + ed1bddf commit b62af48
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Showing 4 changed files with 27 additions and 13 deletions.
2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "WeightInitializers"
uuid = "d49dbf32-c5c2-4618-8acc-27bb2598ef2d"
authors = ["Avik Pal <[email protected]> and contributors"]
version = "0.1.6"
version = "0.1.7"

[deps]
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
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6 changes: 3 additions & 3 deletions ext/WeightInitializersCUDAExt.jl
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Expand Up @@ -30,7 +30,7 @@ function sparse_init(rng::AbstractCuRNG, ::Type{T}, dims::Integer...;
rows, cols = dims
prop_zero = min(1.0, sparsity)
num_zeros = ceil(Integer, prop_zero * rows)
sparse_array = randn(rng, T, dims...) .* std
sparse_array = randn(rng, T, dims...) .* T(std)
sparse_array[1:num_zeros, :] .= CUDA.zero(T)

return CUDA.@allowscalar mapslices(shuffle, sparse_array, dims=1)
Expand All @@ -46,7 +46,7 @@ function identity_init(rng::AbstractCuRNG, ::Type{T}, dims::Integer...;
rows, cols = dims
mat = CUDA.zeros(T, rows, cols)
diag_indices = 1:min(rows, cols)
CUDA.fill!(view(mat, diag_indices, diag_indices), gain)
CUDA.fill!(view(mat, diag_indices, diag_indices), T(gain))
return CUDA.circshift(mat, shift)
else
# Convolution or more dimensions
Expand All @@ -56,7 +56,7 @@ function identity_init(rng::AbstractCuRNG, ::Type{T}, dims::Integer...;
#we should really find a better way to do this
CUDA.@allowscalar for i in 1:min(nin, nout)
index = (centers..., i, i)
weights[index...] = gain
weights[index...] = T(gain)
end
return CUDA.circshift(weights, (ntuple(d -> 0, length(dims) - 2)..., shift, shift))
end
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18 changes: 9 additions & 9 deletions src/initializers.jl
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Expand Up @@ -75,7 +75,7 @@ vision_. 2015.
"""
function kaiming_uniform(rng::AbstractRNG, ::Type{T}, dims::Integer...;
gain::Number=√T(2)) where {T <: Number}
bound = √T(3) * gain / sqrt(T(first(_nfan(dims...))))
bound = √T(3) * T(gain) / sqrt(T(first(_nfan(dims...))))
return (rand(rng, T, dims...) .- T(1 // 2)) .* 2 * bound
end

Expand All @@ -94,7 +94,7 @@ vision_. 2015.
"""
function kaiming_normal(rng::AbstractRNG, ::Type{T}, dims::Integer...;
gain::Number=√T(2)) where {T <: Number}
std = gain / sqrt(T(first(_nfan(dims...))))
std = T(gain) / sqrt(T(first(_nfan(dims...))))
return randn(rng, T, dims...) .* std
end

Expand All @@ -111,13 +111,13 @@ function truncated_normal(rng::AbstractRNG, ::Type{T}, dims::Integer...; mean=T(
if (mean < lo - 2 * std) || (mean > hi + 2 * std)
@warn "Mean is more than 2 std outside the limits in truncated_normal, so the distribution of values may be inaccurate."
end
l = _norm_cdf((lo - mean) / std)
u = _norm_cdf((hi - mean) / std)
l = _norm_cdf((T(lo) - T(mean)) / T(std))
u = _norm_cdf((T(hi) - T(mean)) / T(std))
xs = rand(rng, T, dims...)
broadcast!(xs, xs) do x
x = x * 2(u - l) + (2l - 1)
x = erfinv(x)
return clamp(x * std * √2 + mean, lo, hi)
return clamp(x * T(std) * √2 + T(mean), T(lo), T(hi))
end
return xs
end
Expand Down Expand Up @@ -162,7 +162,7 @@ function orthogonal(rng::AbstractRNG, ::Type{T}, dims::Integer...;
end

if rows < cols
return permutedims(orthogonal(rng, T, cols, rows; gain))
return permutedims(orthogonal(rng, T, cols, rows; gain=T(gain)))
end

mat = randn(rng, T, rows, cols)
Expand Down Expand Up @@ -236,7 +236,7 @@ function sparse_init(rng::AbstractRNG, ::Type{T}, dims::Integer...;
rows, cols = dims
prop_zero = min(1.0, sparsity)
num_zeros = ceil(Integer, prop_zero * rows)
sparse_array = randn(rng, T, dims...) .* std
sparse_array = randn(rng, T, dims...) .* T(std)
sparse_array[1:num_zeros, :] .= zero(T)
return mapslices(shuffle, sparse_array; dims=1)
end
Expand Down Expand Up @@ -313,7 +313,7 @@ function identity_init(rng::AbstractRNG, ::Type{T}, dims::Integer...;
rows, cols = dims
mat = zeros(T, rows, cols)
for i in 1:min(rows, cols)
mat[i, i] = gain
mat[i, i] = T(gain)
end
return circshift(mat, shift)
else
Expand All @@ -323,7 +323,7 @@ function identity_init(rng::AbstractRNG, ::Type{T}, dims::Integer...;
weights = zeros(T, dims...)
for i in 1:min(nin, nout)
index = (centers..., i, i)
weights[index...] = gain
weights[index...] = T(gain)
end
return circshift(weights, (ntuple(d -> 0, length(dims) - 2)..., shift, shift))
end
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14 changes: 14 additions & 0 deletions test/runtests.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -114,6 +114,20 @@ const GROUP = get(ENV, "GROUP", "All")
@test eltype(cl(rng, 4, 2)) == Float32
end

@testset "Kwargs types" for T in (
Float16, Float32, Float64, ComplexF16, ComplexF32, ComplexF64)
if (T <: Real)
@test eltype(truncated_normal(T, 2, 5; mean=0, std=1, lo=-2, hi=2)) == T
@test eltype(orthogonal(T, 2, 5; gain=1.0)) == T
end
@test eltype(glorot_uniform(T, 2, 5; gain=1.0)) == T
@test eltype(glorot_normal(T, 2, 5; gain=1.0)) == T
@test eltype(kaiming_uniform(T, 2, 5; gain=sqrt(2))) == T
@test eltype(kaiming_normal(T, 2, 5; gain=sqrt(2))) == T
@test eltype(identity_init(T, 2, 5; gain=1.0)) == T
@test eltype(sparse_init(T, 2, 5; sparsity=0.5, std=0.01)) == T
end

@testset "kaiming" begin
# kaiming_uniform should yield a kernel in range [-sqrt(6/n_out), sqrt(6/n_out)]
# and kaiming_normal should yield a kernel with stddev ~= sqrt(2/n_out)
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Registration pull request created: JuliaRegistries/General/102612

Tip: Release Notes

Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.

@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.1.7 -m "<description of version>" b62af481eb8dacb29e29e4d99f9ed0e8c7e06d77
git push origin v0.1.7

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