Azure#39830, Azure#39793 (Azure#39838)

* Azure#39744
* fixing some syntax warnings Azure#39830
* Azure#39793

Author: achauhan-scc

sdk/ml/azure-ai-ml/CHANGELOG.md

@@ -8,6 +8,7 @@
 ### Bugs Fixed
   - #37464 - Allowing to update a component in register with anonymousEnvironment environment.
   - #39744 - Fixing a serialization issue in RecurrencePattern schedule.
+  - #39793 - Fixing bug in AML OBO to work with KV secret client.
   - Fix environment archiving and restore
 
 ### Other Changes

sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_10_01/models/_azure_machine_learning_services_enums.py

@@ -205,7 +205,7 @@ class ClassificationModels(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     #: The goal is to create a model that predicts the value of a target variable by learning simple
     #: decision rules inferred from the data features."""
     RANDOM_FOREST = "RandomForest"
-    """Random forest is a supervised learning algorithm.
+    r"""Random forest is a supervised learning algorithm.
     #: The "forest"\  it builds, is an ensemble of decision trees, usually trained with the “bagging”\
     #: method.
     #: The general idea of the bagging method is that a combination of learning models increases the
@@ -1324,7 +1324,7 @@ class RegressionModels(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     #: outputs.
     #: It's an inexact but powerful technique."""
     RANDOM_FOREST = "RandomForest"
-    """Random forest is a supervised learning algorithm.
+    r"""Random forest is a supervised learning algorithm.
     #: The "forest"\  it builds, is an ensemble of decision trees, usually trained with the “bagging”\
     #: method.
     #: The general idea of the bagging method is that a combination of learning models increases the

sdk/ml/azure-ai-ml/azure/ai/ml/_vendor/azure_resources/operations/_resources_operations.py

@@ -62,7 +62,7 @@ def list_by_resource_group(
         **kwargs  # type: Any
     ):
         # type: (...) -> Iterable["models.ResourceListResult"]
-        """Get all the resources for a resource group.
+        r"""Get all the resources for a resource group.
 
         :param resource_group_name: The resource group with the resources to get.
         :type resource_group_name: str
@@ -410,7 +410,7 @@ def list(
         **kwargs  # type: Any
     ):
         # type: (...) -> Iterable["models.ResourceListResult"]
-        """Get all the resources in a subscription.
+        r"""Get all the resources in a subscription.
 
         :param filter: The filter to apply on the operation.:code:`<br>`:code:`<br>`The properties you
          can use for eq (equals) or ne (not equals) are: location, resourceType, name, resourceGroup,

sdk/ml/azure-ai-ml/azure/ai/ml/identity/_internal/managed_identity_client.py

@@ -119,6 +119,11 @@ def request_token(self, *scopes: str, **kwargs: Any) -> AccessToken:
         resource = _scopes_to_resource(*scopes)
         request = self._request_factory(resource)
         request_time = int(time.time())
+        # https://github.com/Azure/azure-sdk-for-python/issues/39793
+        # Remove unsupported parameters
+        kwargs.pop("claims", None)
+        kwargs.pop("tenant_id", None)
+        kwargs.pop("enable_cae", None)
         response = self._pipeline.run(request, retry_on_methods=[request.method], **kwargs)
         token = self._process_response(response=response, request_time=request_time, resource=resource)
         return token