Fix simplification package related issues in image segmentation tasks (Azure#27254)

* uncomment the failing tests

* Fixed the failed schema

* removed the comments

* Use the pre-generated jsonls for IS

* Adding the jsonl conversions cript

Author: nvijayrania

sdk/ml/azure-ai-ml/dev_requirements.txt

@@ -14,6 +14,4 @@ pydash
 azure-mgmt-msi
 pywin32==304 ; sys_platform == 'win32'
 numpy;platform.python_implementation!="PyPy"
-scikit-image;platform.python_implementation!="PyPy"
-# comment this line as simplification is not supported in Python 3.11
-# simplification;platform.python_implementation!="PyPy"
+scikit-image;platform.python_implementation!="PyPy"

sdk/ml/azure-ai-ml/tests/automl_job/e2etests/test_automl_image_classification.py

@@ -135,7 +135,7 @@ def test_image_classification_multiclass_run(
         submitted_job_automode = client.jobs.create_or_update(image_classification_job_automode)
 
         # Assert completion of regular sweep job
-        assert_final_job_status(submitted_job_sweep, client, ImageClassificationJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_sweep, client, ImageClassificationJob, JobStatus.COMPLETED, deadline=3600)
 
         # Assert completion of Automode job
-        assert_final_job_status(submitted_job_automode, client, ImageClassificationJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_automode, client, ImageClassificationJob, JobStatus.COMPLETED, deadline=3600)

sdk/ml/azure-ai-ml/tests/automl_job/e2etests/test_automl_image_classification_multilabel.py

@@ -145,7 +145,7 @@ def test_image_classification_multilabel_run(
         submitted_job_automode = client.jobs.create_or_update(image_classification_multilabel_job_automode)
 
         # Assert completion of regular sweep job
-        assert_final_job_status(submitted_job_sweep, client, ImageClassificationMultilabelJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_sweep, client, ImageClassificationMultilabelJob, JobStatus.COMPLETED, deadline=3600)
 
         # Assert completion of Automode job
-        assert_final_job_status(submitted_job_automode, client, ImageClassificationMultilabelJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_automode, client, ImageClassificationMultilabelJob, JobStatus.COMPLETED, deadline=3600)

sdk/ml/azure-ai-ml/tests/automl_job/e2etests/test_automl_image_object_detection.py

@@ -169,7 +169,7 @@ def test_image_object_detection_run(
         submitted_job_automode = client.jobs.create_or_update(image_object_detection_job_automode)
 
         # Assert completion of regular sweep job
-        assert_final_job_status(submitted_job_sweep, client, ImageObjectDetectionJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_sweep, client, ImageObjectDetectionJob, JobStatus.COMPLETED, deadline=3600)
 
         # Assert completion of Automode job
-        assert_final_job_status(submitted_job_automode, client, ImageObjectDetectionJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_automode, client, ImageObjectDetectionJob, JobStatus.COMPLETED, deadline=3600)

sdk/ml/azure-ai-ml/tests/automl_job/e2etests/test_automl_image_segmentation.py

@@ -36,12 +36,32 @@ def _create_jsonl_segmentation(self, client, train_path, val_path):
         )
         data_path_uri = client.data.create_or_update(fridge_data)
 
-        data_path = "./odFridgeObjectsMask/"
+        import os
+        train_annotations_file = os.path.join(train_path, "train_annotations.jsonl")
+        validation_annotations_file = os.path.join(val_path, "validation_annotations.jsonl")
 
-        from automl_job.jsonl_converter import convert_mask_in_VOC_to_jsonl
+        self._update_jsonl_path(data_path_uri.path, train_annotations_file)
+        self._update_jsonl_path(data_path_uri.path, validation_annotations_file)
 
-        convert_mask_in_VOC_to_jsonl(data_path, data_path_uri.path, train_path, val_path)
+    def _update_jsonl_path(self, remote_path, file_path):
+        import json
 
+        jsonl_file = open(file_path, "r")
+        lines = jsonl_file.readlines()
+        jsonl_file.close()
+
+        data_path = "odFridgeObjectsMask/"
+
+        with open(file_path, "w") as jsonl_file_write:
+            for i in lines:
+                json_line = eval(i)
+                old_url = json_line["image_url"]
+                result = old_url.find(data_path)
+
+                # Update image url
+                json_line["image_url"] = remote_path + old_url[result + len(data_path) :]
+                jsonl_file_write.write(json.dumps(json_line) + "\n")
+    
     def test_image_segmentation_run(self, image_segmentation_dataset: Tuple[Input, Input], client: MLClient) -> None:
         # Note: this test launches two jobs in order to avoid calling the dataset fixture more than once. Ideally, it
         # would have sufficed to mark the fixture with session scope, but pytest-xdist breaks this functionality:
@@ -99,7 +119,7 @@ def test_image_segmentation_run(self, image_segmentation_dataset: Tuple[Input, I
         submitted_job_automode = client.jobs.create_or_update(image_instance_segmentation_job_automode)
 
         # Assert completion of regular sweep job
-        assert_final_job_status(submitted_job_sweep, client, ImageInstanceSegmentationJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_sweep, client, ImageInstanceSegmentationJob, JobStatus.COMPLETED, deadline=3600)
 
         # Assert completion of Automode job
-        assert_final_job_status(submitted_job_automode, client, ImageInstanceSegmentationJob, JobStatus.COMPLETED)
+        assert_final_job_status(submitted_job_automode, client, ImageInstanceSegmentationJob, JobStatus.COMPLETED, deadline=3600)