fix: enable local mode tests that were skipped (#2273)

Author: ahsan-z-khan

tests/integ/test_huggingface.py

@@ -24,7 +24,8 @@
 
 @pytest.mark.release
 @pytest.mark.skipif(
-    integ.test_region() in integ.TRAINING_NO_P2_REGIONS, reason="no ml.p2 instances in this region"
+    integ.test_region() in integ.TRAINING_NO_P2_REGIONS,
+    reason="no ml.p2 instances in this region",
 )
 def test_huggingface_training(
     sagemaker_session,
@@ -62,7 +63,8 @@ def test_huggingface_training(
         )
 
         train_input = hf.sagemaker_session.upload_data(
-            path=os.path.join(data_path, "train"), key_prefix="integ-test-data/huggingface/train"
+            path=os.path.join(data_path, "train"),
+            key_prefix="integ-test-data/huggingface/train",
         )
 
         hf.fit(train_input)

tests/integ/test_tfs.py

@@ -90,7 +90,10 @@ def tfs_predictor_with_model_and_entry_point_and_dependencies(
         tests.integ.DATA_DIR, "tfs/tfs-test-entrypoint-and-dependencies/inference.py"
     )
     dependencies = [
-        os.path.join(tests.integ.DATA_DIR, "tfs/tfs-test-entrypoint-and-dependencies/dependency.py")
+        os.path.join(
+            tests.integ.DATA_DIR,
+            "tfs/tfs-test-entrypoint-and-dependencies/dependency.py",
+        )
     ]
 
     model_data = "file://" + os.path.join(
@@ -133,7 +136,10 @@ def tfs_predictor_with_accelerator(
             name=endpoint_name,
         )
         predictor = model.deploy(
-            1, cpu_instance_type, endpoint_name=endpoint_name, accelerator_type="ml.eia1.medium"
+            1,
+            cpu_instance_type,
+            endpoint_name=endpoint_name,
+            accelerator_type="ml.eia1.medium",
         )
         yield predictor
 
@@ -161,9 +167,6 @@ def test_predict_with_accelerator(tfs_predictor_with_accelerator):
 
 
 @pytest.mark.local_mode
-@pytest.mark.skip(
-    reason="This test is broken due to a regression." "This test should be reenabled later."
-)
 def test_predict_with_entry_point(tfs_predictor_with_model_and_entry_point_same_tar):
     input_data = {"instances": [1.0, 2.0, 5.0]}
     expected_result = {"predictions": [4.0, 4.5, 6.0]}
@@ -173,9 +176,6 @@ def test_predict_with_entry_point(tfs_predictor_with_model_and_entry_point_same_
 
 
 @pytest.mark.local_mode
-@pytest.mark.skip(
-    reason="This test is broken due to a regression." "This test should be reenabled later."
-)
 def test_predict_with_model_and_entry_point_and_dependencies_separated(
     tfs_predictor_with_model_and_entry_point_and_dependencies,
 ):