[ml] Make copy of featureset obj during create_update (#32367)

* Make copy of featureset obj during create

* update dump

* update test

* update dump to work with py37

Author: bastrik

sdk/ml/azure-ai-ml/azure/ai/ml/__init__.py

@@ -24,6 +24,9 @@
     load_data,
     load_datastore,
     load_environment,
+    load_feature_set,
+    load_feature_store,
+    load_feature_store_entity,
     load_job,
     load_model,
     load_model_package,
@@ -58,6 +61,9 @@
     "load_compute",
     "load_data",
     "load_datastore",
+    "load_feature_set",
+    "load_feature_store",
+    "load_feature_store_entity",
     "load_model",
     "load_environment",
     "load_job",

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_assets/_artifacts/feature_set.py

@@ -206,9 +206,13 @@ def dump(self, dest: Union[str, PathLike, IO[AnyStr]], **kwargs) -> None:
 
         origin_spec_path = self.specification.path
         if isinstance(dest, (PathLike, str)) and not is_url(self.specification.path):
+            if os.path.exists(dest):
+                raise FileExistsError(f"File {dest} already exists.")
             relative_path = os.path.basename(self.specification.path)
             src_spec_path = str(Path(self._base_path, self.specification.path))
             dest_spec_path = str(Path(os.path.dirname(dest), relative_path))
+            if os.path.exists(dest_spec_path):
+                shutil.rmtree(dest_spec_path)
             shutil.copytree(src=src_spec_path, dst=dest_spec_path)
             self.specification.path = str(Path("./", relative_path))
         super().dump(dest=dest, **kwargs)

sdk/ml/azure-ai-ml/azure/ai/ml/operations/_feature_set_operations.py

@@ -6,9 +6,10 @@
 
 import json
 import os
+from copy import deepcopy
 from datetime import datetime
 from pathlib import Path
-from typing import Dict, Optional, Union, List
+from typing import Dict, List, Optional, Union
 
 from marshmallow.exceptions import ValidationError as SchemaValidationError
 
@@ -151,23 +152,24 @@ def begin_create_or_update(self, featureset: FeatureSet, **kwargs: Dict) -> LROP
         :return: An instance of LROPoller that returns a FeatureSet.
         :rtype: ~azure.core.polling.LROPoller[~azure.ai.ml.entities.FeatureSet]
         """
+        featureset_copy = deepcopy(featureset)
 
-        featureset_spec = self._validate_and_get_feature_set_spec(featureset)
-        featureset.properties["featuresetPropertiesVersion"] = "1"
-        featureset.properties["featuresetProperties"] = json.dumps(featureset_spec._to_dict())
+        featureset_spec = self._validate_and_get_feature_set_spec(featureset_copy)
+        featureset_copy.properties["featuresetPropertiesVersion"] = "1"
+        featureset_copy.properties["featuresetProperties"] = json.dumps(featureset_spec._to_dict())
 
         sas_uri = None
-        featureset, _ = _check_and_upload_path(
-            artifact=featureset, asset_operations=self, sas_uri=sas_uri, artifact_type=ErrorTarget.FEATURE_SET
+        featureset_copy, _ = _check_and_upload_path(
+            artifact=featureset_copy, asset_operations=self, sas_uri=sas_uri, artifact_type=ErrorTarget.FEATURE_SET
         )
 
-        featureset_resource = FeatureSet._to_rest_object(featureset)
+        featureset_resource = FeatureSet._to_rest_object(featureset_copy)
 
         return self._operation.begin_create_or_update(
             resource_group_name=self._resource_group_name,
             workspace_name=self._workspace_name,
-            name=featureset.name,
-            version=featureset.version,
+            name=featureset_copy.name,
+            version=featureset_copy.version,
             body=featureset_resource,
             **kwargs,
             cls=lambda response, deserialized, headers: FeatureSet._from_rest_object(deserialized),