Merge 363f928 into 17deadd

englhardt · Aug 31, 2020 · 37aefbd · 37aefbd
2 parents 17deadd + 363f928
commit 37aefbd
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Showing 11 changed files with 40,532 additions and 28,177 deletions.
diff --git a/Manifest.toml b/Manifest.toml
diff --git a/examples/svdd_parametrization.ipynb b/examples/svdd_parametrization.ipynb
diff --git a/examples/svdd_training.ipynb b/examples/svdd_training.ipynb
diff --git a/src/classifiers/classifier_ssad.jl b/src/classifiers/classifier_ssad.jl
@@ -107,7 +107,7 @@ function predict(model::SSAD, target::Array{T,2}) where T <: Real
     return model.ρ .- vec(mapslices(predict_observation, target, dims=1))
 end
 
-function fit!(model::SSAD, solver)
+function fit!(model::SSAD, solver::SOLVER_TYPE)
     debug(LOGGER, "[FIT] Fitting SSAD.")
     model.state == model_created && throw(ModelStateException(model.state, model_initialized))
 
@@ -132,7 +132,7 @@ function fit!(model::SSAD, solver)
 end
 
 # see also tilitools https://github.com/nicococo/tilitools/blob/master/tilitools/ssad_convex.py
-function solve!(model::SSAD, solver::JuMP.OptimizerFactory)
+function solve!(model::SSAD, solver::SOLVER_TYPE)
     debug(LOGGER, "[SOLVE] Setting up QP for SSAD with $(is_K_adjusted(model) ? "adjusted" : "non-adjusted") kernel matrix.")
     QP = Model(solver)
     K = is_K_adjusted(model) ? model.K_adjusted : model.K

diff --git a/src/classifiers/classifier_svdd_neg.jl b/src/classifiers/classifier_svdd_neg.jl
@@ -51,7 +51,7 @@ end
 
 set_C!(model::SVDDneg, C::Number) = set_C!(model, (C,C))
 
-function solve!(model::SVDDneg, solver::JuMP.OptimizerFactory)
+function solve!(model::SVDDneg, solver::SOLVER_TYPE)
     ULin = merge_pools(model.pools, :U, :Lin)
     length(ULin) > 0 || throw(ModelInvariantException("SVDDneg requires samples in pool :Lin or :U."))
 

diff --git a/src/classifiers/classifier_svdd_neg_eps.jl b/src/classifiers/classifier_svdd_neg_eps.jl
@@ -57,7 +57,7 @@ function set_eps!(model::SVDDnegEps, eps::Number)
     return nothing
 end
 
-function solve!(model::SVDDnegEps, solver::JuMP.OptimizerFactory)
+function solve!(model::SVDDnegEps, solver::SOLVER_TYPE)
     ULin = merge_pools(model.pools, :U, :Lin)
     length(ULin) > 0 || throw(ModelInvariantException("SVDDnegEps requires samples in pool :Lin or :U."))
 

diff --git a/src/classifiers/classifier_svdd_vanilla.jl b/src/classifiers/classifier_svdd_vanilla.jl
@@ -46,7 +46,7 @@ function set_C!(model::VanillaSVDD, C::Number)
     return nothing
 end
 
-function solve!(model::VanillaSVDD, solver::JuMP.OptimizerFactory)
+function solve!(model::VanillaSVDD, solver::SOLVER_TYPE)
     debug(LOGGER, "[SOLVE] Setting up QP for VanillaSVDD with $(is_K_adjusted(model) ? "adjusted" : "non-adjusted") kernel matrix.")
     QP = Model(solver)
     K = is_K_adjusted(model) ? model.K_adjusted : model.K

diff --git a/src/classifiers/sub/classifier_sub_svdd.jl b/src/classifiers/sub/classifier_sub_svdd.jl
@@ -73,7 +73,7 @@ function fit!(model::SubSVDD, solver)
     return status
 end
 
-function solve!(model::SubSVDD, solver::JuMP.OptimizerFactory)
+function solve!(model::SubSVDD, solver::SOLVER_TYPE)
     debug(LOGGER, "[SOLVE] Setting up QP for SubSVDD with $(is_K_adjusted(model) ? "adjusted" : "non-adjusted") kernel matrix.")
     QP = Model(solver)
     K = is_K_adjusted(model) ? model.K_adjusted : model.K

diff --git a/src/init_strategies/strategies_combined.jl b/src/init_strategies/strategies_combined.jl
@@ -50,7 +50,7 @@ end
     Determines C for WangGammaStrategy by using a provided C init strategy
 """
 struct WangCombinedInitializationStrategy <: InitializationStrategyCombined
-    solver::JuMP.OptimizerFactory
+    solver::SOLVER_TYPE
     gamma_search_range
     C_strategy::InitializationStrategyC
 end

diff --git a/src/svdd_base.jl b/src/svdd_base.jl
@@ -8,6 +8,7 @@ import MLBase
 const learning_pool_enc = LabelEnc.NativeLabels([:U, :Lin, :Lout])
 const class_label_enc = LabelEnc.NativeLabels([:inlier, :outlier])
 const OPT_PRECISION = 1e-7
+const SOLVER_TYPE = JuMP.MOI.OptimizerWithAttributes
 
 @enum ModelState model_created=1 model_initialized=2 model_fitted=3
 

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -5,7 +5,7 @@ using MLKernels, MLLabelUtils
 using Test
 using LinearAlgebra, Random, Statistics
 
-TEST_SOLVER =  with_optimizer(Ipopt.Optimizer, print_level=0)
+TEST_SOLVER =  optimizer_with_attributes(Ipopt.Optimizer, "print_level" => 0)
 
 include("test_utils.jl")