just saving meta data directly

experiments/experiment.jl

@@ -65,6 +65,8 @@ function run_experiment(exp::Experiment; save_output::Bool=true)
     # Save data:
     if save_output
         Serialization.serialize(joinpath(exp.output_path, "$(exp.save_name)_outcome.jls"), outcome)
+        Serialization.serialize(joinpath(exp.output_path, "$(exp.save_name)_bmk.jls"), bmk)
+        meta(outcome::ExperimentOutcome; save_output::Bool=true)
     end
 
     return outcome

src/generator.jl

 using CounterfactualExplanations.Objectives
 using CounterfactualExplanations.Generators: GradientBasedGenerator
 
-"Constructor for `CCEGenerator`."
-function CCEGenerator(; 
-    λ::Union{AbstractFloat,Vector{<:AbstractFloat}}=[0.1, 1.0], 
-    κ::Real=1.0, 
-    temp::Real=0.1, 
-    kwargs...
-)
-    function _set_size_penalty(ce::AbstractCounterfactualExplanation)
-        return ECCCo.set_size_penalty(ce; κ=κ, temp=temp)
-    end
-    _penalties = [Objectives.distance_l2, _set_size_penalty]
-    λ = λ isa AbstractFloat ? [0.0, λ] : λ
-    return GradientBasedGenerator(; penalty=_penalties, λ=λ, kwargs...)
-end
-
 "Constructor for `ECECCCoGenerator`: Energy Constrained Conformal Counterfactual Explanation Generator."
 function ECCCoGenerator(; 
     λ::Union{AbstractFloat,Vector{<:AbstractFloat}}=[0.2,0.4,0.4], 
@@ -45,11 +30,11 @@ function ECCCoGenerator(;
     _set_size_penalty = (ce::AbstractCounterfactualExplanation) -> ECCCo.set_size_penalty(ce; κ=κ, temp=temp)
 
     # Energy penalty
-    _energy_penalty = function (ce::AbstractCounterfactualExplanation)
+    _energy_penalty = function(ce::AbstractCounterfactualExplanation)
         if use_energy_delta
-            return ECCCo.energy_delta(ce; n=nsamples, nmin=nmin, kwargs...)
+            return ECCCo.energy_delta(ce; n=nsamples, nmin=nmin) 
         else
-            return ECCCo.distance_from_energy(ce; n=nsamples, nmin=nmin, kwargs...)
+            return ECCCo.distance_from_energy(ce; n=nsamples, nmin=nmin)
         end
     end
 
@@ -58,18 +43,4 @@ function ECCCoGenerator(;
 
     # Generator
     return GradientBasedGenerator(; loss=loss_fun, penalty=_penalties, λ=λ, opt=opt, kwargs...)
-end
-
-"Constructor for `EnergyDrivenGenerator`."
-function EnergyDrivenGenerator(; λ::Union{AbstractFloat,Vector{<:AbstractFloat}}=[0.1, 1.0], kwargs...)
-    _penalties = [Objectives.distance_l2, ECCCo.distance_from_energy]
-    λ = λ isa AbstractFloat ? [0.0, λ] : λ
-    return GradientBasedGenerator(; penalty=_penalties, λ=λ, kwargs...)
-end
-
-"Constructor for `TargetDrivenGenerator`."
-function TargetDrivenGenerator(; λ::Union{AbstractFloat,Vector{<:AbstractFloat}}=[0.1, 1.0], kwargs...)
-    _penalties = [Objectives.distance_l2, ECCCo.distance_from_targets]
-    λ = λ isa AbstractFloat ? [0.0, λ] : λ
-    return GradientBasedGenerator(; penalty=_penalties, λ=λ, kwargs...)
 end
\ No newline at end of file