Unit tests clean up temp files (#3010)

Author: TobyRoseman

src/python/turicreate/test/test_activity_classifier.py

@@ -476,7 +476,7 @@ def test_export_coreml(self):
         import coremltools
 
         # Save the model as a CoreML model file
-        filename = tempfile.mkstemp("ActivityClassifier.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename)
 
         # Load the model back from the CoreML model file
@@ -521,7 +521,7 @@ def test_create_single_input_column(self):
                 session_id=self.session_id,
                 prediction_window=self.prediction_window,
         )
-        filename = tempfile.mkstemp("ActivityClassifier.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         model.export_coreml(filename)
 
         # Load the model back from the CoreML model file
@@ -748,7 +748,7 @@ def test_gpu_save_load_export(self):
                     model.save(filename)
                     model = tc.load_model(filename)
 
-                filename = tempfile.mkstemp("ActivityClassifier.mlmodel")[1]
+                filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
                 model.export_coreml(filename)
 
         tc.config.set_num_gpus(old_num_gpus)

src/python/turicreate/test/test_drawing_classifier.py

@@ -12,7 +12,7 @@
 import turicreate.toolkits.libtctensorflow
 from turicreate.toolkits._main import ToolkitError as _ToolkitError
 import numpy as _np
-from tempfile import mkstemp as _mkstemp
+import tempfile
 import coremltools as _coremltools
 from copy import copy as _copy
 from array import array as _array
@@ -350,7 +350,7 @@ def test_export_coreml(self):
         max_iters_ans = [str(self.max_iterations), "1"]
         warm_start_ans = "" if self.warm_start is None else self.warm_start
         for i, model in enumerate(self.models):
-            filename = _mkstemp("bingo.mlmodel")[1]
+            filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
             model.export_coreml(filename)
 
             # Load the model back from the CoreML model file
@@ -384,7 +384,7 @@ def test_export_coreml_with_predict(self):
                 prefix = "pretrained" + str(test_number)
             else:
                 prefix = "scratch" + str(test_number)
-            filename = _mkstemp(prefix + ".mlmodel")[1]
+            filename = tempfile.NamedTemporaryFile(prefix=prefix, suffix=".mlmodel").name
             model.export_coreml(filename)
             mlmodel = _coremltools.models.MLModel(filename)
             tc_preds = model.predict(sf)

src/python/turicreate/test/test_image_classifier.py

@@ -212,7 +212,7 @@ def test_export_coreml(self):
                 "Expected failure until "
                 + "https://github.com/apple/turicreate/issues/2744 is fixed"
             )
-        filename = tempfile.mkstemp("bingo.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename)
 
         coreml_model = coremltools.models.MLModel(filename)
@@ -234,7 +234,7 @@ def test_export_coreml(self):
 
     @unittest.skipIf(sys.platform != "darwin", "Core ML only supported on Mac")
     def test_export_coreml_predict(self):
-        filename = tempfile.mkstemp("bingo.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename)
 
         coreml_model = coremltools.models.MLModel(filename)

src/python/turicreate/test/test_image_similarity.py

@@ -227,7 +227,7 @@ def get_psnr(x, y):
             )
 
         # Save the model as a CoreML model file
-        filename = tempfile.mkstemp("ImageSimilarity.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename)
 
         # Load the model back from the CoreML model file

src/python/turicreate/test/test_object_detector.py

@@ -449,7 +449,7 @@ def test_export_coreml(self):
         import coremltools
         import platform
 
-        filename = tempfile.mkstemp("bingo.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename, include_non_maximum_suppression=False)
 
         coreml_model = coremltools.models.MLModel(filename)
@@ -486,7 +486,7 @@ def test_export_coreml(self):
             # not that meaningful unless the model has converged
 
         # Also check if we can train a second model and export it.
-        filename2 = tempfile.mkstemp("bingo2.mlmodel")[1]
+        filename2 = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         # We also test at the same time if we can export a model with a single
         # class
         sf = tc.SFrame(
@@ -505,7 +505,7 @@ def test_export_coreml(self):
     def test_export_coreml_with_non_maximum_suppression(self):
         from PIL import Image
 
-        filename = tempfile.mkstemp("bingo.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename, include_non_maximum_suppression=True)
 
         coreml_model = coremltools.models.MLModel(filename)
@@ -521,7 +521,7 @@ def test_export_coreml_with_non_maximum_suppression(self):
             # not that meaningful unless the model has converged
 
         # Also check if we can train a second model and export it.
-        filename2 = tempfile.mkstemp("bingo2.mlmodel")[1]
+        filename2 = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         # We also test at the same time if we can export a model with a single
         # class
         sf = tc.SFrame(

src/python/turicreate/test/test_one_shot_object_detector.py

@@ -215,7 +215,7 @@ def test_export_coreml(self):
         import coremltools
         import platform
 
-        filename = tempfile.mkstemp("bingo.mlmodel")[1]
+        filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename, include_non_maximum_suppression=False)
 
         ## Test metadata
@@ -254,7 +254,7 @@ def test_export_coreml(self):
             self.assertEqual(ret["coordinates"].shape[0], ret["confidence"].shape[0])
 
         # Test export without non max supression
-        filename2 = tempfile.mkstemp("bingo2.mlmodel")[1]
+        filename2 = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
         self.model.export_coreml(filename2, include_non_maximum_suppression=True)
         coreml_model = coremltools.models.MLModel(filename)
         self.assertTrue(

src/python/turicreate/test/test_recommender.py

@@ -36,7 +36,7 @@
 import array
 from turicreate.util import _assert_sframe_equal as assert_sframe_equal
 from turicreate.toolkits._internal_utils import _mac_ver
-from tempfile import mkstemp as _mkstemp
+import tempfile
 from copy import copy
 from subprocess import Popen as _Popen
 from subprocess import PIPE as _PIPE
@@ -75,7 +75,7 @@ def _coreml_to_tc(preds):
 
 class RecommenderTestBase(unittest.TestCase):
     def _test_coreml_export(self, m, item_ids, ratings=None):
-        temp_file_path = _mkstemp()[1]
+        temp_file_path = tempfile.NamedTemporaryFile().name
         if m.target and ratings:
             obs_data_sf = tc.SFrame(
                 {m.item_id: tc.SArray(item_ids), m.target: tc.SArray(ratings)}
@@ -3053,8 +3053,8 @@ def test_export_model_size(self):
         self.assertEqual(m1.num_users, 10)
         self.assertEqual(m2.num_users, 20 * 10)
 
-        temp_file_path_1 = _mkstemp()[1]
-        temp_file_path_2 = _mkstemp()[1]
+        temp_file_path_1 = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
+        temp_file_path_2 = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
 
         m1.export_coreml(temp_file_path_1)
         m2.export_coreml(temp_file_path_2)

src/python/turicreate/test/test_sarray.py

@@ -2306,9 +2306,11 @@ def test_save_sarray(self):
         data = SArray(range(1000))
         data = data[data > 50]
         # lazy and good
-        tmp_dir = tempfile.mkdtemp()
-        data.save(tmp_dir)
-        shutil.rmtree(tmp_dir)
+        try:
+            tmp_dir = tempfile.mkdtemp()
+            data.save(tmp_dir)
+        finally:
+            shutil.rmtree(tmp_dir)
         print(data)
 
     def test_to_numpy(self):

src/python/turicreate/test/test_sframe.py

@@ -4128,9 +4128,11 @@ def test_save_sframe(self):
         data["x"] = range(100)
         data["x"] = data["x"] > 50
         # lazy and good
-        tmp_dir = tempfile.mkdtemp()
-        data.save(tmp_dir)
-        shutil.rmtree(tmp_dir)
+        try:
+            tmp_dir = tempfile.mkdtemp()
+            data.save(tmp_dir)
+        finally:
+            shutil.rmtree(tmp_dir)
         print(data)
 
     def test_empty_argmax_does_not_fail(self):

src/python/turicreate/test/test_style_transfer.py

@@ -308,7 +308,7 @@ def test_export_coreml(self):
 
         model = self.model
         for flexible_shape_on in [True, False]:
-            filename = tempfile.mkstemp("my_style_transfer.mlmodel")[1]
+            filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
             model.export_coreml(filename, include_flexible_shape=flexible_shape_on)
 
             ## Metadata test