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test with Sophia #485

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4 changes: 0 additions & 4 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -20,9 +20,7 @@ MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
OrdinaryDiffEqDefault = "50262376-6c5a-4cf5-baba-aaf4f84d72d7"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
Expand All @@ -48,9 +46,7 @@ MLJBase = "1"
MLJModelInterface = "1"
MLUtils = "0.4"
NNlib = "0.9"
Optimisers = "0.4"
Optimization = "4"
OptimizationOptimisers = "0.3"
OrdinaryDiffEqDefault = "1"
Random = "1"
SciMLBase = "2"
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4 changes: 2 additions & 2 deletions examples/usage.jl
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Expand Up @@ -53,11 +53,11 @@ r = rand(data_dist, nvars, n)
r = convert.(Float32, r)

# Fit It
using DataFrames, MLJBase, Zygote, ADTypes, OptimizationOptimisers
using DataFrames, MLJBase, Zygote, ADTypes, Optimization
df = DataFrame(transpose(r), :auto)
model = ICNFModel(
icnf;
optimizers = (Lion(),),
optimizers = (Sophia(),),
n_epochs = 300,
adtype = AutoZygote(),
batch_size = 512,
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2 changes: 0 additions & 2 deletions src/ContinuousNormalizingFlows.jl
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Expand Up @@ -16,9 +16,7 @@ import ADTypes,
MLJModelInterface,
MLUtils,
NNlib,
Optimisers,
Optimization,
OptimizationOptimisers,
OrdinaryDiffEqDefault,
Random,
SciMLBase,
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2 changes: 1 addition & 1 deletion src/exts/mlj_ext/core_cond_icnf.jl
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Expand Up @@ -13,7 +13,7 @@ end
function CondICNFModel(
m::AbstractICNF,
loss::Function = loss;
optimizers::Tuple = (Optimisers.Lion(),),
optimizers::Tuple = (Optimization.Sophia(),),
n_epochs::Int = 300,
adtype::ADTypes.AbstractADType = ADTypes.AutoZygote(),
batch_size::Int = 32,
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2 changes: 1 addition & 1 deletion src/exts/mlj_ext/core_icnf.jl
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Expand Up @@ -13,7 +13,7 @@ end
function ICNFModel(
m::AbstractICNF,
loss::Function = loss;
optimizers::Tuple = (Optimisers.Lion(),),
optimizers::Tuple = (Optimization.Sophia(),),
n_epochs::Int = 300,
adtype::ADTypes.AbstractADType = ADTypes.AutoZygote(),
batch_size::Int = 32,
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