Don't use at-eval

Author: tkf

src/multivariate/optimize/interface.jl

@@ -53,91 +53,95 @@ promote_objtype(method::ZerothOrderOptimizer, x, autodiff::Symbol, inplace::Bool
 promote_objtype(method::FirstOrderOptimizer,  x, autodiff::Symbol, inplace::Bool, td::TwiceDifferentiable) = td
 promote_objtype(method::SecondOrderOptimizer, x, autodiff::Symbol, inplace::Bool, td::TwiceDifferentiable) = td
 
-for optimize in [:optimize, :optimizing]
-@eval begin
-
 # if no method or options are present
-function $optimize(f,         initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
+function optimizing(f,         initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
     method = fallback_method(f)
     checked_kwargs, method = check_kwargs(kwargs, method)
     d = promote_objtype(method, initial_x, autodiff, inplace, f)
     add_default_opts!(checked_kwargs, method)
 
     options = Options(; checked_kwargs...)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
+function optimizing(f, g, initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
 
     method = fallback_method(f, g)
     checked_kwargs, method = check_kwargs(kwargs, method)
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g)
     add_default_opts!(checked_kwargs, method)
 
     options = Options(; checked_kwargs...)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, h, initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
+function optimizing(f, g, h, initial_x::AbstractArray; inplace = true, autodiff = :finite, kwargs...)
 
     method = fallback_method(f, g, h)
     checked_kwargs, method = check_kwargs(kwargs, method)
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g, h)
     add_default_opts!(checked_kwargs, method)
 
     options = Options(; checked_kwargs...)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
 
 # no method supplied with objective
-function $optimize(d::T, initial_x::AbstractArray, options::Options) where T<:AbstractObjective
-    $optimize(d, initial_x, fallback_method(d), options)
+function optimizing(d::T, initial_x::AbstractArray, options::Options) where T<:AbstractObjective
+    optimizing(d, initial_x, fallback_method(d), options)
 end
 # no method supplied with inplace and autodiff keywords becauase objective is not supplied
-function $optimize(f, initial_x::AbstractArray, options::Options; inplace = true, autodiff = :finite)
+function optimizing(f, initial_x::AbstractArray, options::Options; inplace = true, autodiff = :finite)
     method = fallback_method(f)
     d = promote_objtype(method, initial_x, autodiff, inplace, f)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, initial_x::AbstractArray, options::Options; inplace = true, autodiff = :finite)
+function optimizing(f, g, initial_x::AbstractArray, options::Options; inplace = true, autodiff = :finite)
 
     method = fallback_method(f, g)
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, h, initial_x::AbstractArray{T}, options::Options; inplace = true, autodiff = :finite) where {T}
+function optimizing(f, g, h, initial_x::AbstractArray{T}, options::Options; inplace = true, autodiff = :finite) where {T}
 
     method = fallback_method(f, g, h)
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g, h)
 
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
 
 # potentially everything is supplied (besides caches)
-function $optimize(f, initial_x::AbstractArray, method::AbstractOptimizer,
+function optimizing(f, initial_x::AbstractArray, method::AbstractOptimizer,
                      options::Options = Options(;default_options(method)...); inplace = true, autodiff = :finite)
 
     d = promote_objtype(method, initial_x, autodiff, inplace, f)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, initial_x::AbstractArray, method::AbstractOptimizer,
+function optimizing(f, g, initial_x::AbstractArray, method::AbstractOptimizer,
          options::Options = Options(;default_options(method)...); inplace = true, autodiff = :finite)
 
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g)
 
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
-function $optimize(f, g, h, initial_x::AbstractArray{T}, method::AbstractOptimizer,
+function optimizing(f, g, h, initial_x::AbstractArray{T}, method::AbstractOptimizer,
          options::Options = Options(;default_options(method)...); inplace = true, autodiff = :finite) where T
 
     d = promote_objtype(method, initial_x, autodiff, inplace, f, g, h)
 
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
 
-function $optimize(d::D, initial_x::AbstractArray, method::SecondOrderOptimizer,
+function optimizing(d::D, initial_x::AbstractArray, method::SecondOrderOptimizer,
                   options::Options = Options(;default_options(method)...); autodiff = :finite, inplace = true) where {D <: Union{NonDifferentiable, OnceDifferentiable}}
     d = promote_objtype(method, initial_x, autodiff, inplace, d)
-    $optimize(d, initial_x, method, options)
+    optimizing(d, initial_x, method, options)
 end
 
-end  # eval
-end  # for
+function optimize(args...; kwargs...)
+    local istate
+    for istate′ in optimizing(args...; kwargs...)
+        istate = istate′
+    end
+    # We can safely assume that `istate` is defined at this point.  That is to say,
+    # `OptimIterator` guarantees that `iterate(::OptimIterator) !== nothing`.
+    return OptimizationResults(istate)
+end

src/multivariate/optimize/optimize.jl

@@ -83,6 +83,9 @@ function Base.iterate(iter::OptimIterator, istate = nothing)
         options.show_trace && print_header(method)
         trace!(tr, d, state, iteration, method, options, time()-t0)
         ls_success::Bool = true
+
+        # Note: `optimize` depends on that first iteration always yields something
+        # (i.e., `iterate` does _not_ return a `nothing` when `istate === nothing`).
     else
         @unpack_IteratorState istate
 
@@ -197,13 +200,3 @@ function optimizing(d::D, initial_x::Tx, method::M,
     end
     return OptimIterator(d, initial_x, method, options, state)
 end
-
-function optimize(d::D, initial_x::Tx, method::M,
-                  options::Options = Options(;default_options(method)...),
-                  state = initial_state(method, options, d, initial_x)) where {D<:AbstractObjective, M<:AbstractOptimizer, Tx <: AbstractArray}
-    local istate
-    for istate′ in optimizing(d, initial_x, method, options, state)
-        istate = istate′
-    end
-    return OptimizationResults(istate)
-end