Only use p_tqdm is n_jobs>1

miplearn/components/component.py

@@ -198,7 +198,10 @@ class Component:
             instance.free()
             return pre_instance
 
-        pre = p_umap(_pre_sample_xy, instances, num_cpus=n_jobs)
+        if n_jobs == 1:
+            pre = [_pre_sample_xy(instance) for instance in instances]
+        else:
+            pre = p_umap(_pre_sample_xy, instances, num_cpus=n_jobs)
         pre_combined: Dict = {}
         for (cname, comp) in components.items():
             pre_combined[cname] = []
@@ -229,7 +232,10 @@ class Component:
             instance.free()
             return x_instance, y_instance
 
-        xy = p_umap(_sample_xy, instances)
+        if n_jobs == 1:
+            xy = [_sample_xy(instance) for instance in instances]
+        else:
+            xy = p_umap(_sample_xy, instances)
 
         for (cname, comp) in components.items():
             x_comp: Dict = {}

setup.py

@@ -9,7 +9,7 @@ with open("README.md", "r") as fh:
 
 setup(
     name="miplearn",
-    version="0.2.0.dev6",
+    version="0.2.0.dev7",
     author="Alinson S. Xavier",
     author_email="axavier@anl.gov",
     description="Extensible framework for Learning-Enhanced Mixed-Integer Optimization",