TST speedup tests

formasaurus/fieldtype_model.py

@@ -55,6 +55,8 @@
 def train(annotations,
           use_precise_form_types=True,
           optimize_hyperparameters_iters=0,
+          optimize_hyperparameters_folds=5,
+          optimize_hyperparameters_jobs=-1,
           full_form_type_names=False,
           full_field_type_names=True,
           verbose=True):
@@ -106,9 +108,9 @@ def log(msg):
         }
 
         rs = RandomizedSearchCV(crf, params_space,
-            cv=get_annotation_folds(annotations, 5),
+            cv=get_annotation_folds(annotations, optimize_hyperparameters_folds),
             verbose=verbose,
-            n_jobs=-1,
+            n_jobs=optimize_hyperparameters_jobs,
             n_iter=optimize_hyperparameters_iters,
             iid=False,
             scoring=scorer

tests/test_cmdline.py

@@ -23,7 +23,7 @@ def test_check_data():
 
 
 def test_evaluate():
-    out = subprocess.check_output('formasaurus evaluate all --cv 3', shell=True)
+    out = subprocess.check_output('formasaurus evaluate all --cv 2', shell=True)
     m = re.search(b"(\d+.\d+)% forms are classified correctly", out)
     assert m
     assert float(m.group(1)) > 80

tests/test_fieldtype_model.py

@@ -1,5 +1,6 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import, division
+import itertools
 
 import numpy as np
 from sklearn_crfsuite.metrics import flat_accuracy_score
@@ -13,16 +14,18 @@
 
 
 def test_training(storage, capsys):
-
-    annotations = list(a for a in storage.iter_annotations(
+    annotations = (a for a in storage.iter_annotations(
         simplify_form_types=True,
         simplify_field_types=True,
-    ) if a.fields_annotated)[:300]
+    ) if a.fields_annotated)
+    annotations = list(itertools.islice(annotations, 0, 300))
 
     crf = train(
         annotations=annotations,
         use_precise_form_types=False,
-        optimize_hyperparameters_iters=10,
+        optimize_hyperparameters_iters=2,
+        optimize_hyperparameters_folds=2,
+        optimize_hyperparameters_jobs=-1,
         full_form_type_names=False,
         full_field_type_names=False
     )

tests/test_formtype_model.py

@@ -1,16 +1,16 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import, division
+import itertools
 
 from sklearn.metrics import accuracy_score
 
 from formasaurus.formtype_model import get_realistic_form_labels
 
 
 def test_get_realistic_formtypes(storage):
-    annotations = list(storage.iter_annotations())
+    annotations = list(itertools.islice(storage.iter_annotations(), 0, 300))
     y_true = [a.type_full for a in annotations]
-    y_pred = get_realistic_form_labels(annotations, n_folds=5)
+    y_pred = get_realistic_form_labels(annotations, n_folds=3)
     score = accuracy_score(y_true, y_pred)
     assert 0.7 < score < 0.98
 
-