Partial implementation of parallel_solve

src/MIPLearn.jl

@@ -6,20 +6,16 @@ __precompile__(false)
 module MIPLearn
 
 using PyCall
-
-export JuMPInstance
-export LearningSolver
-export @feature
-export @category
-
-miplearn = pyimport("miplearn")
+global miplearn = pyimport("miplearn")
+global traceback = pyimport("traceback")
 
 include("utils/log.jl")
 include("utils/exceptions.jl")
+include("instance/abstract.jl")
+include("instance/jump.jl")
+include("instance/file.jl")
 include("solvers/jump.jl")
 include("solvers/learning.jl")
 include("solvers/macros.jl")
-include("instance/jump.jl")
-include("instance/file.jl")
 
 end # module

src/instance/abstract.jl

@@ -0,0 +1,8 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+abstract type Instance
+end
+
+

src/instance/file.jl

@@ -55,12 +55,16 @@ end
 
 struct FileInstance <: Instance
     py::PyCall.PyObject
+    filename::AbstractString
 end
 
 
 function FileInstance(filename)::FileInstance
     filename isa AbstractString || error("filename should be a string. Found $(typeof(filename)) instead.")
-    return FileInstance(PyFileInstance(filename))
+    return FileInstance(
+        PyFileInstance(filename),
+        filename,
+    )
 end
 
 

src/solvers/learning.jl

@@ -2,18 +2,21 @@
 #  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
+using Distributed
+
+
 struct LearningSolver
     py::PyCall.PyObject
-end
-
-
-abstract type Instance
+    optimizer_factory
 end
 
 
 function LearningSolver(optimizer_factory)::LearningSolver
     py = miplearn.LearningSolver(solver=JuMPSolver(optimizer_factory))
-    return LearningSolver(py)
+    return LearningSolver(
+        py,
+        optimizer_factory,
+    )
 end
 
 
@@ -31,7 +34,19 @@ function fit!(solver::LearningSolver, instances::Vector{<:Instance})
 end
 
 
+function parallel_solve!(solver::LearningSolver, instances::Vector{FileInstance})
+    filenames = [instance.filename for instance in instances]
+    optimizer_factory = solver.optimizer_factory
+    @sync @distributed for filename in filenames
+        s = LearningSolver(optimizer_factory)
+        solve!(s, FileInstance(filename))
+        nothing
+    end
+end
+
+
 export Instance,
        LearningSolver,
        solve!,
-       fit!
+       fit!,
+       parallel_solve!

src/solvers/macros.jl

@@ -62,3 +62,7 @@ macro category(obj, category)
         set_category!($(esc(obj)), $(esc(category)))
     end
 end
+
+
+export @feature,
+       @category

src/utils/exceptions.jl

@@ -3,7 +3,6 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 using PyCall
-traceback = pyimport("traceback")
 
 
 macro python_call(expr)