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[WIP] Add initializers from ReservoirComputing #23

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[WIP] Add initializers from ReservoirComputing #23

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f453b9b
adding reservoircomputing initializers
MartinuzziFrancesco Mar 10, 2024
0a0d7c1
some fixes
MartinuzziFrancesco Mar 10, 2024
c107eaf
restructure of tests
MartinuzziFrancesco Mar 13, 2024
0bcdfbf
fixing cuda ext and test errors
MartinuzziFrancesco Mar 13, 2024
70a7d34
removing Distributions and moving rc_inits to CUDAExt
MartinuzziFrancesco Mar 26, 2024
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6 changes: 5 additions & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@ version = "0.1.7"

[deps]
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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This is quite heavy, we should make it into an extension

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I don't think we even need that, I was using it for Uniform and now it's only needed for Bernoulli, so I'm sure we can avoid it all together. I just needed to get the tests running to catch the various CUDA errors

LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
PartialFunctions = "570af359-4316-4cb7-8c74-252c00c2016b"
PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
Expand All @@ -22,10 +23,12 @@ WeightInitializersCUDAExt = "CUDA"
Aqua = "0.8"
CUDA = "5"
ChainRulesCore = "1.21"
Distributions = "0.25"
LinearAlgebra = "1.9"
PartialFunctions = "1.2"
PrecompileTools = "1.2"
Random = "1.9"
SafeTestsets = "0.1"
SpecialFunctions = "2"
StableRNGs = "1"
Statistics = "1.9"
Expand All @@ -36,9 +39,10 @@ julia = "1.9"
Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["Aqua", "Test", "StableRNGs", "Random", "Statistics", "CUDA"]
test = ["Aqua", "Test", "StableRNGs", "Random", "Statistics", "CUDA", "SafeTestsets"]
36 changes: 34 additions & 2 deletions ext/WeightInitializersCUDAExt.jl
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Expand Up @@ -3,7 +3,7 @@ module WeightInitializersCUDAExt
using WeightInitializers, CUDA
using Random
import WeightInitializers: __partial_apply, NUM_TO_FPOINT, identity_init, sparse_init,
orthogonal
orthogonal, delay_line, delay_line_backward

const AbstractCuRNG = Union{CUDA.RNG, CURAND.RNG}

Expand Down Expand Up @@ -62,7 +62,39 @@ function identity_init(rng::AbstractCuRNG, ::Type{T}, dims::Integer...;
end
end

for initializer in (:sparse_init, :identity_init)
# rc initializers

function delay_line(rng::AbstractCuRNG,
::Type{T},
dims::Integer...;
weight = T(0.1)) where {T <: Number}
reservoir_matrix = CUDA.zeros(T, dims...)
@assert length(dims) == 2&&dims[1] == dims[2] "The dimensions must define a square matrix (e.g., (100, 100))"

for i in 1:(dims[1] - 1)
reservoir_matrix[i + 1, i] = T(weight)
end

return reservoir_matrix
end

function delay_line_backward(rng::AbstractCuRNG,
::Type{T},
dims::Integer...;
weight = T(0.1),
fb_weight = T(0.2)) where {T <: Number}
res_size = first(dims)
reservoir_matrix = CUDA.zeros(T, dims...)

for i in 1:(res_size - 1)
reservoir_matrix[i + 1, i] = T(weight)
reservoir_matrix[i, i + 1] = T(fb_weight)
end

return reservoir_matrix
end

for initializer in (:sparse_init, :identity_init, :delay_line, :delay_line_backward)
@eval function ($initializer)(rng::AbstractCuRNG, dims::Integer...; kwargs...)
return $initializer(rng, Float32, dims...; kwargs...)
end
Expand Down
42 changes: 40 additions & 2 deletions src/WeightInitializers.jl
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Expand Up @@ -4,11 +4,12 @@ import PrecompileTools: @recompile_invalidations

@recompile_invalidations begin
using ChainRulesCore, PartialFunctions, Random, SpecialFunctions, Statistics,
LinearAlgebra
LinearAlgebra, Distributions
end

include("utils.jl")
include("initializers.jl")
include("rc_initializers.jl")

# Mark the functions as non-differentiable
for f in [
Expand Down Expand Up @@ -43,11 +44,46 @@ for f in [
:truncated_normal,
:orthogonal,
:sparse_init,
:identity_init
:identity_init,
:rand_sparse,
:delay_line,
:delay_line_backward,
:cycle_jumps,
:simple_cycle,
:pseudo_svd,
:scaled_rand,
:weighted_init,
:informed_init,
:minimal_init
]
@eval @non_differentiable $(f)(::Any...)
end

for initializer in (:glorot_uniform, :glorot_normal, :kaiming_uniform, :kaiming_normal,
:truncated_normal, :orthogonal, :sparse_init, :identity_init, :rand_sparse, :delay_line,
:delay_line_backward, :cycle_jumps, :simple_cycle, :pseudo_svd, :scaled_rand,
:weighted_init, :informed_init, :minimal_init)
NType = ifelse(initializer === :truncated_normal, Real, Number)
@eval function ($initializer)(dims::Integer...; kwargs...)
return $initializer(_default_rng(), Float32, dims...; kwargs...)
end
@eval function ($initializer)(rng::AbstractRNG, dims::Integer...; kwargs...)
return $initializer(rng, Float32, dims...; kwargs...)
end
@eval function ($initializer)(::Type{T},
dims::Integer...; kwargs...) where {T <: $NType}
return $initializer(_default_rng(), T, dims...; kwargs...)
end
@eval function ($initializer)(rng::AbstractRNG; kwargs...)
return __partial_apply($initializer, (rng, (; kwargs...)))
end
@eval function ($initializer)(rng::AbstractRNG,
::Type{T}; kwargs...) where {T <: $NType}
return __partial_apply($initializer, ((rng, T), (; kwargs...)))
end
@eval ($initializer)(; kwargs...) = __partial_apply($initializer, (; kwargs...))
end

export zeros64, ones64, rand64, randn64, zeros32, ones32, rand32, randn32, zeros16, ones16,
rand16, randn16
export zerosC64, onesC64, randC64, randnC64, zerosC32, onesC32, randC32, randnC32, zerosC16,
Expand All @@ -58,5 +94,7 @@ export truncated_normal
export orthogonal
export sparse_init
export identity_init
export scaled_rand, weighted_init, informed_init, minimal_init
export rand_sparse, delay_line, delay_line_backward, cycle_jumps, simple_cycle, pseudo_svd

end
23 changes: 0 additions & 23 deletions src/initializers.jl
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Expand Up @@ -330,29 +330,6 @@ function identity_init(rng::AbstractRNG, ::Type{T}, dims::Integer...;
end

# Default Fallbacks for all functions
for initializer in (:glorot_uniform, :glorot_normal, :kaiming_uniform, :kaiming_normal,
:truncated_normal, :orthogonal, :sparse_init, :identity_init)
NType = ifelse(initializer === :truncated_normal, Real, Number)
@eval function ($initializer)(dims::Integer...; kwargs...)
return $initializer(_default_rng(), Float32, dims...; kwargs...)
end
@eval function ($initializer)(rng::AbstractRNG, dims::Integer...; kwargs...)
return $initializer(rng, Float32, dims...; kwargs...)
end
@eval function ($initializer)(::Type{T},
dims::Integer...; kwargs...) where {T <: $NType}
return $initializer(_default_rng(), T, dims...; kwargs...)
end
@eval function ($initializer)(rng::AbstractRNG; kwargs...)
return __partial_apply($initializer, (rng, (; kwargs...)))
end
@eval function ($initializer)(rng::AbstractRNG,
::Type{T}; kwargs...) where {T <: $NType}
return __partial_apply($initializer, ((rng, T), (; kwargs...)))
end
@eval ($initializer)(; kwargs...) = __partial_apply($initializer, (; kwargs...))
end

for tp in ("16", "32", "64", "C16", "C32", "C64"), func in (:zeros, :ones, :randn, :rand)
initializer = Symbol(func, tp)
@eval function ($initializer)(dims::Integer...; kwargs...)
Expand Down
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