two version of R2R are here HEAD master

9 files changed, 9556 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/__init__.py
new file mode 100644
index 00000000..3e84a44a
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/__init__.py
@@ -0,0 +1,27 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from ._delete_operations import DeleteOperations
+from ._events_operations import EventsOperations
+from ._experiments_operations import ExperimentsOperations
+from ._metric_operations import MetricOperations
+from ._runs_operations import RunsOperations
+from ._run_artifacts_operations import RunArtifactsOperations
+from ._run_operations import RunOperations
+from ._spans_operations import SpansOperations
+
+__all__ = [
+    'DeleteOperations',
+    'EventsOperations',
+    'ExperimentsOperations',
+    'MetricOperations',
+    'RunsOperations',
+    'RunArtifactsOperations',
+    'RunOperations',
+    'SpansOperations',
+]
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_delete_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_delete_operations.py
new file mode 100644
index 00000000..9080611e
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_delete_operations.py
@@ -0,0 +1,248 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Optional, TypeVar
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_patch_configuration_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_configuration_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class DeleteOperations(object):
+    """DeleteOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def patch_configuration(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.DeleteConfiguration"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.DeleteConfiguration"
+        """patch_configuration.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: DeleteConfiguration, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.DeleteConfiguration"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteConfiguration')
+        else:
+            _json = None
+
+        request = build_patch_configuration_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.patch_configuration.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('DeleteConfiguration', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    patch_configuration.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration"}  # type: ignore
+
+
+    @distributed_trace
+    def get_configuration(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.DeleteConfiguration"
+        """get_configuration.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: DeleteConfiguration, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.DeleteConfiguration"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_configuration_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            template_url=self.get_configuration.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('DeleteConfiguration', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_configuration.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_events_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_events_operations.py
new file mode 100644
index 00000000..f87546d9
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_events_operations.py
@@ -0,0 +1,713 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Optional, TypeVar
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_batch_post_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_post_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_post_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batch/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_post_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_post_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_post_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/events")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class EventsOperations(object):
+    """EventsOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def batch_post_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.BatchEventCommand"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchEventCommandResult"
+        """batch_post_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchEventCommandResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchEventCommandResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchEventCommand')
+        else:
+            _json = None
+
+        request = build_batch_post_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_post_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchEventCommandResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_post_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/events"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_post_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.BatchEventCommand"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchEventCommandResult"
+        """batch_post_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchEventCommandResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchEventCommandResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchEventCommand')
+        else:
+            _json = None
+
+        request = build_batch_post_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_post_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchEventCommandResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_post_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/events"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_post(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.BatchEventCommand"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchEventCommandResult"
+        """batch_post.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchEventCommandResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchEventCommandResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchEventCommand')
+        else:
+            _json = None
+
+        request = build_batch_post_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_post.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchEventCommandResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_post.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batch/events"}  # type: ignore
+
+
+    @distributed_trace
+    def post_by_experiment_name(  # pylint: disable=inconsistent-return-statements
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.BaseEvent"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """post_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: None, or the result of cls(response)
+        :rtype: None
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[None]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BaseEvent')
+        else:
+            _json = None
+
+        request = build_post_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.post_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in []:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    post_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/events"}  # type: ignore
+
+
+    @distributed_trace
+    def post_by_experiment_id(  # pylint: disable=inconsistent-return-statements
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.BaseEvent"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """post_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: None, or the result of cls(response)
+        :rtype: None
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[None]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BaseEvent')
+        else:
+            _json = None
+
+        request = build_post_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.post_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in []:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    post_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/events"}  # type: ignore
+
+
+    @distributed_trace
+    def post(  # pylint: disable=inconsistent-return-statements
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.BaseEvent"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """post.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: None, or the result of cls(response)
+        :rtype: None
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[None]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BaseEvent')
+        else:
+            _json = None
+
+        request = build_post_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.post.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in []:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    post.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/events"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_experiments_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_experiments_operations.py
new file mode 100644
index 00000000..3b12b9c1
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_experiments_operations.py
@@ -0,0 +1,878 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, Optional, TypeVar, Union
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_get_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_create_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_update_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_request_initial(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_query_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+    url_safe_experiment_names_only = kwargs.pop('url_safe_experiment_names_only', True)  # type: Optional[bool]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments:query")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if url_safe_experiment_names_only is not None:
+        _query_parameters['urlSafeExperimentNamesOnly'] = _SERIALIZER.query("url_safe_experiment_names_only", url_safe_experiment_names_only, 'bool')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_tags_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/tags:delete")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class ExperimentsOperations(object):
+    """ExperimentsOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def get(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Experiment"
+        """Get details of an Experiment.
+
+        Get details of an Experiment with specific Experiment name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name: The experiment name.
+        :type experiment_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Experiment, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Experiment
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Experiment"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_name=experiment_name,
+            template_url=self.get.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Experiment', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}"}  # type: ignore
+
+
+    @distributed_trace
+    def create(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Experiment"
+        """Create an Experiment.
+
+        Create a new Experiment.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name: The experiment name.
+        :type experiment_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Experiment, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Experiment
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Experiment"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_create_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_name=experiment_name,
+            template_url=self.create.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Experiment', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    create.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Experiment"
+        """Get details of an Experiment.
+
+        Get details of an Experiment with specific Experiment Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id: The identifier of the experiment.
+        :type experiment_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Experiment, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Experiment
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Experiment"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_by_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            template_url=self.get_by_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Experiment', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"}  # type: ignore
+
+
+    @distributed_trace
+    def update(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.ModifyExperiment"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Experiment"
+        """Update details of an Experiment.
+
+        Update details of an Experiment with specific Experiment Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id: The identifier of the experiment.
+        :type experiment_id: str
+        :param body: Experiment details which needs to be updated.
+        :type body: ~azure.mgmt.machinelearningservices.models.ModifyExperiment
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Experiment, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Experiment
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Experiment"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'ModifyExperiment')
+        else:
+            _json = None
+
+        request = build_update_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.update.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Experiment', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    update.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"}  # type: ignore
+
+
+    def _delete_initial(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Any
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_delete_request_initial(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            template_url=self._delete_initial.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            raise HttpResponseError(response=response, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('object', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    _delete_initial.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"}  # type: ignore
+
+
+    @distributed_trace
+    def begin_delete(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> LROPoller[Any]
+        """Delete an Experiment.
+
+        Delete an existing Empty Experiment.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id: The identifier of the experiment.
+        :type experiment_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+        :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+         operation to not poll, or pass in your own initialized polling object for a personal polling
+         strategy.
+        :paramtype polling: bool or ~azure.core.polling.PollingMethod
+        :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+         Retry-After header is present.
+        :return: An instance of LROPoller that returns either any or the result of cls(response)
+        :rtype: ~azure.core.polling.LROPoller[any]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        polling = kwargs.pop('polling', True)  # type: Union[bool, PollingMethod]
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        lro_delay = kwargs.pop(
+            'polling_interval',
+            self._config.polling_interval
+        )
+        cont_token = kwargs.pop('continuation_token', None)  # type: Optional[str]
+        if cont_token is None:
+            raw_result = self._delete_initial(
+                subscription_id=subscription_id,
+                resource_group_name=resource_group_name,
+                workspace_name=workspace_name,
+                experiment_id=experiment_id,
+                cls=lambda x,y,z: x,
+                **kwargs
+            )
+        kwargs.pop('error_map', None)
+
+        def get_long_running_output(pipeline_response):
+            response = pipeline_response.http_response
+            deserialized = self._deserialize('object', pipeline_response)
+            if cls:
+                return cls(pipeline_response, deserialized, {})
+            return deserialized
+
+
+        if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
+        elif polling is False: polling_method = NoPolling()
+        else: polling_method = polling
+        if cont_token:
+            return LROPoller.from_continuation_token(
+                polling_method=polling_method,
+                continuation_token=cont_token,
+                client=self._client,
+                deserialization_callback=get_long_running_output
+            )
+        return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
+
+    begin_delete.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"}  # type: ignore
+
+    @distributed_trace
+    def get_by_query(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        url_safe_experiment_names_only=True,  # type: Optional[bool]
+        body=None,  # type: Optional["_models.ExperimentQueryParams"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedExperimentList"]
+        """Get all Experiments in a specific workspace.
+
+        Get all experiments in a specific workspace with the specified query filters.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param url_safe_experiment_names_only:
+        :type url_safe_experiment_names_only: bool
+        :param body: Query parameters for data sorting and filtering.
+        :type body: ~azure.mgmt.machinelearningservices.models.ExperimentQueryParams
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedExperimentList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedExperimentList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedExperimentList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ExperimentQueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    content_type=content_type,
+                    json=_json,
+                    url_safe_experiment_names_only=url_safe_experiment_names_only,
+                    template_url=self.get_by_query.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ExperimentQueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    content_type=content_type,
+                    json=_json,
+                    url_safe_experiment_names_only=url_safe_experiment_names_only,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedExperimentList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_by_query.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments:query"}  # type: ignore
+
+    @distributed_trace
+    def delete_tags(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.DeleteTagsCommand"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.DeleteExperimentTagsResult"
+        """Delete list of Tags in an Experiment.
+
+        Delete list of Tags from a specific Experiment Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id: The identifier of the experiment.
+        :type experiment_id: str
+        :param body: The requested tags list to be deleted.
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteTagsCommand
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: DeleteExperimentTagsResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.DeleteExperimentTagsResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.DeleteExperimentTagsResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteTagsCommand')
+        else:
+            _json = None
+
+        request = build_delete_tags_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_tags.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('DeleteExperimentTagsResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_tags.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/tags:delete"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_metric_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_metric_operations.py
new file mode 100644
index 00000000..f9184554
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_metric_operations.py
@@ -0,0 +1,1206 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, Optional, TypeVar, Union
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_get_full_fidelity_metric_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/full")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_metric_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/list")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_generic_resource_metrics_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/azuremonitor/list")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_sampled_metric_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/sample")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_post_run_metrics_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/batch")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_metrics_by_data_container_id_request_initial(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    data_container_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentId}/containers/{dataContainerId}/deleteMetrics")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+        "dataContainerId": _SERIALIZER.url("data_container_id", data_container_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_metrics_by_run_id_request_initial(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/deleteMetrics")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_metric_details_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    metric_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/metrics/{metricId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "metricId": _SERIALIZER.url("metric_id", metric_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_metric_details_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    metric_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/metrics/{metricId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "metricId": _SERIALIZER.url("metric_id", metric_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class MetricOperations(object):
+    """MetricOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def get_full_fidelity_metric(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.RetrieveFullFidelityMetricRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.MetricV2"
+        """API to retrieve the full-fidelity sequence associated with a particular run and metricName.
+
+        API to retrieve the full-fidelity sequence associated with a particular run and metricName.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.RetrieveFullFidelityMetricRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: MetricV2, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.MetricV2
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.MetricV2"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'RetrieveFullFidelityMetricRequest')
+        else:
+            _json = None
+
+        request = build_get_full_fidelity_metric_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.get_full_fidelity_metric.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('MetricV2', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_full_fidelity_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/full"}  # type: ignore
+
+
+    @distributed_trace
+    def list_metric(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.ListMetrics"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedMetricDefinitionList"]
+        """API to list metric for a particular datacontainer and metricName.
+
+        API to list metric for a particular datacontainer and metricName.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ListMetrics
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedMetricDefinitionList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedMetricDefinitionList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedMetricDefinitionList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ListMetrics')
+                else:
+                    _json = None
+                
+                request = build_list_metric_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=self.list_metric.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ListMetrics')
+                else:
+                    _json = None
+                
+                request = build_list_metric_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedMetricDefinitionList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/list"}  # type: ignore
+
+    @distributed_trace
+    def list_generic_resource_metrics(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.ListGenericResourceMetrics"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedMetricDefinitionList"]
+        """API to list workspace/subworkspace resource metrics for a particular ResourceId.
+
+        API to list workspace/subworkspace resource metrics for a particular ResourceId.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ListGenericResourceMetrics
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedMetricDefinitionList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedMetricDefinitionList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedMetricDefinitionList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ListGenericResourceMetrics')
+                else:
+                    _json = None
+                
+                request = build_list_generic_resource_metrics_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=self.list_generic_resource_metrics.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                if body is not None:
+                    _json = self._serialize.body(body, 'ListGenericResourceMetrics')
+                else:
+                    _json = None
+                
+                request = build_list_generic_resource_metrics_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedMetricDefinitionList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_generic_resource_metrics.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/azuremonitor/list"}  # type: ignore
+
+    @distributed_trace
+    def get_sampled_metric(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.GetSampledMetricRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.MetricSample"
+        """Stub for future action
+        API to retrieve samples for one or many runs to compare a given metricName
+        Throw if schemas don't match across metrics.
+
+        Stub for future action
+        API to retrieve samples for one or many runs to compare a given metricName
+        Throw if schemas don't match across metrics.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.GetSampledMetricRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: MetricSample, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.MetricSample
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.MetricSample"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'GetSampledMetricRequest')
+        else:
+            _json = None
+
+        request = build_get_sampled_metric_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.get_sampled_metric.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('MetricSample', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_sampled_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/sample"}  # type: ignore
+
+
+    @distributed_trace
+    def post_run_metrics(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.BatchIMetricV2"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.PostRunMetricsResult"
+        """Post Metrics to a Run.
+
+        Post Metrics to a specific Run Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchIMetricV2
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: PostRunMetricsResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.PostRunMetricsResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PostRunMetricsResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchIMetricV2')
+        else:
+            _json = None
+
+        request = build_post_run_metrics_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.post_run_metrics.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200, 207]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if response.status_code == 200:
+            deserialized = self._deserialize('PostRunMetricsResult', pipeline_response)
+
+        if response.status_code == 207:
+            deserialized = self._deserialize('PostRunMetricsResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    post_run_metrics.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/batch"}  # type: ignore
+
+
+    def _delete_metrics_by_data_container_id_initial(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        data_container_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Any
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_delete_metrics_by_data_container_id_request_initial(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            data_container_id=data_container_id,
+            template_url=self._delete_metrics_by_data_container_id_initial.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            raise HttpResponseError(response=response, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('object', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    _delete_metrics_by_data_container_id_initial.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentId}/containers/{dataContainerId}/deleteMetrics"}  # type: ignore
+
+
+    @distributed_trace
+    def begin_delete_metrics_by_data_container_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        data_container_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> LROPoller[Any]
+        """API to delete metrics by data container id.
+
+        API to delete metrics by data container id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param data_container_id:
+        :type data_container_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+        :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+         operation to not poll, or pass in your own initialized polling object for a personal polling
+         strategy.
+        :paramtype polling: bool or ~azure.core.polling.PollingMethod
+        :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+         Retry-After header is present.
+        :return: An instance of LROPoller that returns either any or the result of cls(response)
+        :rtype: ~azure.core.polling.LROPoller[any]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        polling = kwargs.pop('polling', True)  # type: Union[bool, PollingMethod]
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        lro_delay = kwargs.pop(
+            'polling_interval',
+            self._config.polling_interval
+        )
+        cont_token = kwargs.pop('continuation_token', None)  # type: Optional[str]
+        if cont_token is None:
+            raw_result = self._delete_metrics_by_data_container_id_initial(
+                subscription_id=subscription_id,
+                resource_group_name=resource_group_name,
+                workspace_name=workspace_name,
+                experiment_id=experiment_id,
+                data_container_id=data_container_id,
+                cls=lambda x,y,z: x,
+                **kwargs
+            )
+        kwargs.pop('error_map', None)
+
+        def get_long_running_output(pipeline_response):
+            response = pipeline_response.http_response
+            deserialized = self._deserialize('object', pipeline_response)
+            if cls:
+                return cls(pipeline_response, deserialized, {})
+            return deserialized
+
+
+        if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
+        elif polling is False: polling_method = NoPolling()
+        else: polling_method = polling
+        if cont_token:
+            return LROPoller.from_continuation_token(
+                polling_method=polling_method,
+                continuation_token=cont_token,
+                client=self._client,
+                deserialization_callback=get_long_running_output
+            )
+        return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
+
+    begin_delete_metrics_by_data_container_id.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentId}/containers/{dataContainerId}/deleteMetrics"}  # type: ignore
+
+    def _delete_metrics_by_run_id_initial(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Any
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_delete_metrics_by_run_id_request_initial(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            template_url=self._delete_metrics_by_run_id_initial.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            raise HttpResponseError(response=response, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('object', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    _delete_metrics_by_run_id_initial.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/deleteMetrics"}  # type: ignore
+
+
+    @distributed_trace
+    def begin_delete_metrics_by_run_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> LROPoller[Any]
+        """API to delete metrics by run id.
+
+        API to delete metrics by run id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+        :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+         operation to not poll, or pass in your own initialized polling object for a personal polling
+         strategy.
+        :paramtype polling: bool or ~azure.core.polling.PollingMethod
+        :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+         Retry-After header is present.
+        :return: An instance of LROPoller that returns either any or the result of cls(response)
+        :rtype: ~azure.core.polling.LROPoller[any]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        polling = kwargs.pop('polling', True)  # type: Union[bool, PollingMethod]
+        cls = kwargs.pop('cls', None)  # type: ClsType[Any]
+        lro_delay = kwargs.pop(
+            'polling_interval',
+            self._config.polling_interval
+        )
+        cont_token = kwargs.pop('continuation_token', None)  # type: Optional[str]
+        if cont_token is None:
+            raw_result = self._delete_metrics_by_run_id_initial(
+                subscription_id=subscription_id,
+                resource_group_name=resource_group_name,
+                workspace_name=workspace_name,
+                run_id=run_id,
+                cls=lambda x,y,z: x,
+                **kwargs
+            )
+        kwargs.pop('error_map', None)
+
+        def get_long_running_output(pipeline_response):
+            response = pipeline_response.http_response
+            deserialized = self._deserialize('object', pipeline_response)
+            if cls:
+                return cls(pipeline_response, deserialized, {})
+            return deserialized
+
+
+        if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
+        elif polling is False: polling_method = NoPolling()
+        else: polling_method = polling
+        if cont_token:
+            return LROPoller.from_continuation_token(
+                polling_method=polling_method,
+                continuation_token=cont_token,
+                client=self._client,
+                deserialization_callback=get_long_running_output
+            )
+        return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
+
+    begin_delete_metrics_by_run_id.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/deleteMetrics"}  # type: ignore
+
+    @distributed_trace
+    def get_metric_details_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        metric_id,  # type: str
+        experiment_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunMetric"
+        """Get Metric details.
+
+        Get Metric details for a specific Metric Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param metric_id: The identifier for a Metric.
+        :type metric_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunMetric, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunMetric
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunMetric"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_metric_details_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            metric_id=metric_id,
+            experiment_name=experiment_name,
+            template_url=self.get_metric_details_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunMetric', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_metric_details_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/metrics/{metricId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_metric_details_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        metric_id,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunMetric"
+        """Get Metric details.
+
+        Get Metric details for a specific Metric Id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param metric_id: The identifier for a Metric.
+        :type metric_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunMetric, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunMetric
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunMetric"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_metric_details_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            metric_id=metric_id,
+            experiment_id=experiment_id,
+            template_url=self.get_metric_details_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunMetric', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_metric_details_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/metrics/{metricId}"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_artifacts_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_artifacts_operations.py
new file mode 100644
index 00000000..c7dd5930
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_artifacts_operations.py
@@ -0,0 +1,1850 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, Optional, TypeVar
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_list_in_container_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_in_container_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_in_path_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/path")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_in_path_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/path")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_id_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/metadata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_id_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/metadata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_content_information_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/contentinfo")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_content_information_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/contentinfo")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_sas_uri_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/artifacturi")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_sas_uri_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/artifacturi")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_sas_by_prefix_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/prefix/contentinfo")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_sas_by_prefix_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    path = kwargs.pop('path', None)  # type: Optional[str]
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/prefix/contentinfo")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if path is not None:
+        _query_parameters['path'] = _SERIALIZER.query("path", path, 'str')
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_create_empty_artifacts_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/batch/metadata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_create_empty_artifacts_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/batch/metadata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class RunArtifactsOperations(object):
+    """RunArtifactsOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def list_in_container_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactList"]
+        """list_in_container_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_in_container_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_in_container_by_experiment_name.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_in_container_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_in_container_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts"}  # type: ignore
+
+    @distributed_trace
+    def list_in_container_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactList"]
+        """list_in_container_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_in_container_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_in_container_by_experiment_id.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_in_container_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_in_container_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts"}  # type: ignore
+
+    @distributed_trace
+    def list_in_path_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        path=None,  # type: Optional[str]
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactList"]
+        """list_in_path_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param path:
+        :type path: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_in_path_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_in_path_by_experiment_name.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_in_path_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_in_path_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/path"}  # type: ignore
+
+    @distributed_trace
+    def list_in_path_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        path=None,  # type: Optional[str]
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactList"]
+        """list_in_path_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param path:
+        :type path: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactList or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_in_path_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_in_path_by_experiment_id.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_in_path_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_in_path_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/path"}  # type: ignore
+
+    @distributed_trace
+    def get_by_id_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Artifact"
+        """get_by_id_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Artifact, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Artifact
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Artifact"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_by_id_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            path=path,
+            template_url=self.get_by_id_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Artifact', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_id_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/metadata"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_id_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Artifact"
+        """get_by_id_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Artifact, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Artifact
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Artifact"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_by_id_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            path=path,
+            template_url=self.get_by_id_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Artifact', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_id_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/metadata"}  # type: ignore
+
+
+    @distributed_trace
+    def get_content_information_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ArtifactContentInformation"
+        """get_content_information_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ArtifactContentInformation, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ArtifactContentInformation
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ArtifactContentInformation"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_content_information_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            path=path,
+            template_url=self.get_content_information_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('ArtifactContentInformation', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_content_information_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/contentinfo"}  # type: ignore
+
+
+    @distributed_trace
+    def get_content_information_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ArtifactContentInformation"
+        """get_content_information_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ArtifactContentInformation, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ArtifactContentInformation
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ArtifactContentInformation"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_content_information_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            path=path,
+            template_url=self.get_content_information_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('ArtifactContentInformation', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_content_information_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/contentinfo"}  # type: ignore
+
+
+    @distributed_trace
+    def get_sas_uri_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> str
+        """get_sas_uri_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: str, or the result of cls(response)
+        :rtype: str
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[str]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_sas_uri_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            path=path,
+            template_url=self.get_sas_uri_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('str', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_sas_uri_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/artifacturi"}  # type: ignore
+
+
+    @distributed_trace
+    def get_sas_uri_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        path=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> str
+        """get_sas_uri_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param path:
+        :type path: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: str, or the result of cls(response)
+        :rtype: str
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[str]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_sas_uri_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            path=path,
+            template_url=self.get_sas_uri_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('str', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_sas_uri_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/artifacturi"}  # type: ignore
+
+
+    @distributed_trace
+    def list_sas_by_prefix_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        path=None,  # type: Optional[str]
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactContentInformationList"]
+        """list_sas_by_prefix_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param path:
+        :type path: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactContentInformationList or the
+         result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactContentInformationList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactContentInformationList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_sas_by_prefix_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_sas_by_prefix_by_experiment_name.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_sas_by_prefix_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactContentInformationList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_sas_by_prefix_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/prefix/contentinfo"}  # type: ignore
+
+    @distributed_trace
+    def list_sas_by_prefix_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        path=None,  # type: Optional[str]
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedArtifactContentInformationList"]
+        """list_sas_by_prefix_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param path:
+        :type path: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedArtifactContentInformationList or the
+         result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactContentInformationList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedArtifactContentInformationList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_sas_by_prefix_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list_sas_by_prefix_by_experiment_id.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_sas_by_prefix_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    path=path,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedArtifactContentInformationList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_sas_by_prefix_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/prefix/contentinfo"}  # type: ignore
+
+    @distributed_trace
+    def batch_create_empty_artifacts_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.ArtifactPathList"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchArtifactContentInformationResult"
+        """batch_create_empty_artifacts_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ArtifactPathList
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchArtifactContentInformationResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchArtifactContentInformationResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchArtifactContentInformationResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'ArtifactPathList')
+        else:
+            _json = None
+
+        request = build_batch_create_empty_artifacts_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_create_empty_artifacts_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchArtifactContentInformationResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_create_empty_artifacts_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/batch/metadata"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_create_empty_artifacts_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.ArtifactPathList"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchArtifactContentInformationResult"
+        """batch_create_empty_artifacts_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ArtifactPathList
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchArtifactContentInformationResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchArtifactContentInformationResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchArtifactContentInformationResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'ArtifactPathList')
+        else:
+            _json = None
+
+        request = build_batch_create_empty_artifacts_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_create_empty_artifacts_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchArtifactContentInformationResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_create_empty_artifacts_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/batch/metadata"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_operations.py
new file mode 100644
index 00000000..c8591bff
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_run_operations.py
@@ -0,0 +1,233 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, List, Optional, TypeVar, Union
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_list_by_compute_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    compute_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    filter = kwargs.pop('filter', None)  # type: Optional[str]
+    continuationtoken = kwargs.pop('continuationtoken', None)  # type: Optional[str]
+    orderby = kwargs.pop('orderby', None)  # type: Optional[List[str]]
+    sortorder = kwargs.pop('sortorder', None)  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+    top = kwargs.pop('top', None)  # type: Optional[int]
+    count = kwargs.pop('count', None)  # type: Optional[bool]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/runs")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "computeName": _SERIALIZER.url("compute_name", compute_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if filter is not None:
+        _query_parameters['$filter'] = _SERIALIZER.query("filter", filter, 'str')
+    if continuationtoken is not None:
+        _query_parameters['$continuationtoken'] = _SERIALIZER.query("continuationtoken", continuationtoken, 'str')
+    if orderby is not None:
+        _query_parameters['$orderby'] = _SERIALIZER.query("orderby", orderby, '[str]')
+    if sortorder is not None:
+        _query_parameters['$sortorder'] = _SERIALIZER.query("sortorder", sortorder, 'str')
+    if top is not None:
+        _query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
+    if count is not None:
+        _query_parameters['$count'] = _SERIALIZER.query("count", count, 'bool')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class RunOperations(object):
+    """RunOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def list_by_compute(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        compute_name,  # type: str
+        filter=None,  # type: Optional[str]
+        continuationtoken=None,  # type: Optional[str]
+        orderby=None,  # type: Optional[List[str]]
+        sortorder=None,  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+        top=None,  # type: Optional[int]
+        count=None,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """list_by_compute.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param compute_name:
+        :type compute_name: str
+        :param filter: Allows for filtering the collection of resources.
+         The expression specified is evaluated for each resource in the collection, and only items
+         where the expression evaluates to true are included in the response.
+        :type filter: str
+        :param continuationtoken: The continuation token to use for getting the next set of resources.
+        :type continuationtoken: str
+        :param orderby: The list of resource properties to use for sorting the requested resources.
+        :type orderby: list[str]
+        :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after
+         each property name in the OrderBy parameter.
+        :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection
+        :param top: The maximum number of items in the resource collection to be included in the
+         result.
+         If not specified, all items are returned.
+        :type top: int
+        :param count: Whether to include a count of the matching resources along with the resources
+         returned in the response.
+        :type count: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_by_compute_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    compute_name=compute_name,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=self.list_by_compute.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_by_compute_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    compute_name=compute_name,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list_by_compute.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/runs"}  # type: ignore
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_runs_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_runs_operations.py
new file mode 100644
index 00000000..a95f5652
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_runs_operations.py
@@ -0,0 +1,3972 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, List, Optional, TypeVar, Union
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_get_child_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    filter = kwargs.pop('filter', None)  # type: Optional[str]
+    continuationtoken = kwargs.pop('continuationtoken', None)  # type: Optional[str]
+    orderby = kwargs.pop('orderby', None)  # type: Optional[List[str]]
+    sortorder = kwargs.pop('sortorder', None)  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+    top = kwargs.pop('top', None)  # type: Optional[int]
+    count = kwargs.pop('count', None)  # type: Optional[bool]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/children")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if filter is not None:
+        _query_parameters['$filter'] = _SERIALIZER.query("filter", filter, 'str')
+    if continuationtoken is not None:
+        _query_parameters['$continuationtoken'] = _SERIALIZER.query("continuationtoken", continuationtoken, 'str')
+    if orderby is not None:
+        _query_parameters['$orderby'] = _SERIALIZER.query("orderby", orderby, '[str]')
+    if sortorder is not None:
+        _query_parameters['$sortorder'] = _SERIALIZER.query("sortorder", sortorder, 'str')
+    if top is not None:
+        _query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
+    if count is not None:
+        _query_parameters['$count'] = _SERIALIZER.query("count", count, 'bool')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_child_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    filter = kwargs.pop('filter', None)  # type: Optional[str]
+    continuationtoken = kwargs.pop('continuationtoken', None)  # type: Optional[str]
+    orderby = kwargs.pop('orderby', None)  # type: Optional[List[str]]
+    sortorder = kwargs.pop('sortorder', None)  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+    top = kwargs.pop('top', None)  # type: Optional[int]
+    count = kwargs.pop('count', None)  # type: Optional[bool]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/children")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if filter is not None:
+        _query_parameters['$filter'] = _SERIALIZER.query("filter", filter, 'str')
+    if continuationtoken is not None:
+        _query_parameters['$continuationtoken'] = _SERIALIZER.query("continuationtoken", continuationtoken, 'str')
+    if orderby is not None:
+        _query_parameters['$orderby'] = _SERIALIZER.query("orderby", orderby, '[str]')
+    if sortorder is not None:
+        _query_parameters['$sortorder'] = _SERIALIZER.query("sortorder", sortorder, 'str')
+    if top is not None:
+        _query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
+    if count is not None:
+        _query_parameters['$count'] = _SERIALIZER.query("count", count, 'bool')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_child_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    filter = kwargs.pop('filter', None)  # type: Optional[str]
+    continuationtoken = kwargs.pop('continuationtoken', None)  # type: Optional[str]
+    orderby = kwargs.pop('orderby', None)  # type: Optional[List[str]]
+    sortorder = kwargs.pop('sortorder', None)  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+    top = kwargs.pop('top', None)  # type: Optional[int]
+    count = kwargs.pop('count', None)  # type: Optional[bool]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/children")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if filter is not None:
+        _query_parameters['$filter'] = _SERIALIZER.query("filter", filter, 'str')
+    if continuationtoken is not None:
+        _query_parameters['$continuationtoken'] = _SERIALIZER.query("continuationtoken", continuationtoken, 'str')
+    if orderby is not None:
+        _query_parameters['$orderby'] = _SERIALIZER.query("orderby", orderby, '[str]')
+    if sortorder is not None:
+        _query_parameters['$sortorder'] = _SERIALIZER.query("sortorder", sortorder, 'str')
+    if top is not None:
+        _query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
+    if count is not None:
+        _query_parameters['$count'] = _SERIALIZER.query("count", count, 'bool')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_details_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/details")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_details_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/details")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_details_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/details")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_run_data_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/rundata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_get_run_data_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchrundata")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_add_or_modify_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/runs")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_batch_add_or_modify_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/runs")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_add_or_modify_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str', pattern=r'^[a-zA-Z0-9][\w-]{0,255}$'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_add_or_modify_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str', pattern=r'^[a-zA-Z0-9][\w-]{0,255}$'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_add_or_modify_experiment_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str', pattern=r'^[a-zA-Z0-9][\w-]{0,255}$'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_add_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str', pattern=r'^[a-zA-Z0-9][\w-]{0,255}$'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_tags_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_modify_or_delete_tags_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_tags_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_modify_or_delete_tags_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_tags_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/tags")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_run_services_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/services")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_run_services_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/services")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_delete_run_services_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/services")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="DELETE",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_add_or_modify_run_service_instances_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    node_id,  # type: int
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "nodeId": _SERIALIZER.url("node_id", node_id, 'int'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="PATCH",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_run_service_instances_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    node_id,  # type: int
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "nodeId": _SERIALIZER.url("node_id", node_id, 'int'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_query_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs:query")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_query_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs:query")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_ids_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/runIds")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_by_ids_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/runIds")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_cancel_run_with_uri_by_experiment_id_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    cancelation_reason = kwargs.pop('cancelation_reason', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/cancel")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentId": _SERIALIZER.url("experiment_id", experiment_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if cancelation_reason is not None:
+        _query_parameters['CancelationReason'] = _SERIALIZER.query("cancelation_reason", cancelation_reason, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_cancel_run_with_uri_by_experiment_name_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    experiment_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    cancelation_reason = kwargs.pop('cancelation_reason', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/cancel")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+        "experimentName": _SERIALIZER.url("experiment_name", experiment_name, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if cancelation_reason is not None:
+        _query_parameters['CancelationReason'] = _SERIALIZER.query("cancelation_reason", cancelation_reason, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class RunsOperations(object):  # pylint: disable=too-many-public-methods
+    """RunsOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def get_child_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        filter=None,  # type: Optional[str]
+        continuationtoken=None,  # type: Optional[str]
+        orderby=None,  # type: Optional[List[str]]
+        sortorder=None,  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+        top=None,  # type: Optional[int]
+        count=None,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """get_child_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param filter: Allows for filtering the collection of resources.
+         The expression specified is evaluated for each resource in the collection, and only items
+         where the expression evaluates to true are included in the response.
+        :type filter: str
+        :param continuationtoken: The continuation token to use for getting the next set of resources.
+        :type continuationtoken: str
+        :param orderby: The list of resource properties to use for sorting the requested resources.
+        :type orderby: list[str]
+        :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after
+         each property name in the OrderBy parameter.
+        :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection
+        :param top: The maximum number of items in the resource collection to be included in the
+         result.
+         If not specified, all items are returned.
+        :type top: int
+        :param count: Whether to include a count of the matching resources along with the resources
+         returned in the response.
+        :type count: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_get_child_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=self.get_child_by_experiment_name.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_get_child_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_name=experiment_name,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_child_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/children"}  # type: ignore
+
+    @distributed_trace
+    def get_child_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        filter=None,  # type: Optional[str]
+        continuationtoken=None,  # type: Optional[str]
+        orderby=None,  # type: Optional[List[str]]
+        sortorder=None,  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+        top=None,  # type: Optional[int]
+        count=None,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """get_child_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param filter: Allows for filtering the collection of resources.
+         The expression specified is evaluated for each resource in the collection, and only items
+         where the expression evaluates to true are included in the response.
+        :type filter: str
+        :param continuationtoken: The continuation token to use for getting the next set of resources.
+        :type continuationtoken: str
+        :param orderby: The list of resource properties to use for sorting the requested resources.
+        :type orderby: list[str]
+        :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after
+         each property name in the OrderBy parameter.
+        :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection
+        :param top: The maximum number of items in the resource collection to be included in the
+         result.
+         If not specified, all items are returned.
+        :type top: int
+        :param count: Whether to include a count of the matching resources along with the resources
+         returned in the response.
+        :type count: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_get_child_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=self.get_child_by_experiment_id.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_get_child_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    experiment_id=experiment_id,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_child_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/children"}  # type: ignore
+
+    @distributed_trace
+    def get_child(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        filter=None,  # type: Optional[str]
+        continuationtoken=None,  # type: Optional[str]
+        orderby=None,  # type: Optional[List[str]]
+        sortorder=None,  # type: Optional[Union[str, "_models.SortOrderDirection"]]
+        top=None,  # type: Optional[int]
+        count=None,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """get_child.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param filter: Allows for filtering the collection of resources.
+         The expression specified is evaluated for each resource in the collection, and only items
+         where the expression evaluates to true are included in the response.
+        :type filter: str
+        :param continuationtoken: The continuation token to use for getting the next set of resources.
+        :type continuationtoken: str
+        :param orderby: The list of resource properties to use for sorting the requested resources.
+        :type orderby: list[str]
+        :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after
+         each property name in the OrderBy parameter.
+        :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection
+        :param top: The maximum number of items in the resource collection to be included in the
+         result.
+         If not specified, all items are returned.
+        :type top: int
+        :param count: Whether to include a count of the matching resources along with the resources
+         returned in the response.
+        :type count: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_get_child_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=self.get_child.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_get_child_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    filter=filter,
+                    continuationtoken=continuationtoken,
+                    orderby=orderby,
+                    sortorder=sortorder,
+                    top=top,
+                    count=count,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_child.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/children"}  # type: ignore
+
+    @distributed_trace
+    def get_details_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunDetails"
+        """get_details_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunDetails, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunDetails"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_details_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            template_url=self.get_details_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunDetails', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_details_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/details"}  # type: ignore
+
+
+    @distributed_trace
+    def get_details_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunDetails"
+        """get_details_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunDetails, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunDetails"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_details_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            template_url=self.get_details_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunDetails', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_details_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/details"}  # type: ignore
+
+
+    @distributed_trace
+    def get_details(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunDetails"
+        """get_details.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunDetails, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunDetails"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_details_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            template_url=self.get_details.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunDetails', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_details.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/details"}  # type: ignore
+
+
+    @distributed_trace
+    def get_run_data(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.GetRunDataRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.GetRunDataResult"
+        """get_run_data.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.GetRunDataRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: GetRunDataResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.GetRunDataResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.GetRunDataResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'GetRunDataRequest')
+        else:
+            _json = None
+
+        request = build_get_run_data_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.get_run_data.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('GetRunDataResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_run_data.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/rundata"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_get_run_data(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.BatchRequest1"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchResult1"
+        """batch_get_run_data.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchRequest1
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchResult1, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchResult1
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchResult1"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchRequest1')
+        else:
+            _json = None
+
+        request = build_batch_get_run_data_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_get_run_data.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200, 207]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if response.status_code == 200:
+            deserialized = self._deserialize('BatchResult1', pipeline_response)
+
+        if response.status_code == 207:
+            deserialized = self._deserialize('BatchResult1', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_get_run_data.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchrundata"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_add_or_modify_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.BatchAddOrModifyRunRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchRunResult"
+        """batch_add_or_modify_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchAddOrModifyRunRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchRunResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchRunResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchAddOrModifyRunRequest')
+        else:
+            _json = None
+
+        request = build_batch_add_or_modify_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_add_or_modify_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchRunResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_add_or_modify_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/runs"}  # type: ignore
+
+
+    @distributed_trace
+    def batch_add_or_modify_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.BatchAddOrModifyRunRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchRunResult"
+        """batch_add_or_modify_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchAddOrModifyRunRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchRunResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchRunResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'BatchAddOrModifyRunRequest')
+        else:
+            _json = None
+
+        request = build_batch_add_or_modify_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.batch_add_or_modify_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchRunResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_add_or_modify_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/runs"}  # type: ignore
+
+
+    @distributed_trace
+    def add_or_modify_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.CreateRun"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """add_or_modify_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateRun
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'CreateRun')
+        else:
+            _json = None
+
+        request = build_add_or_modify_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.add_or_modify_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    add_or_modify_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """get_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            template_url=self.get_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def add_or_modify_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.CreateRun"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """add_or_modify_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateRun
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'CreateRun')
+        else:
+            _json = None
+
+        request = build_add_or_modify_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.add_or_modify_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    add_or_modify_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """get_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            template_url=self.get_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def add_or_modify_experiment(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.CreateRun"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """add_or_modify_experiment.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateRun
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'CreateRun')
+        else:
+            _json = None
+
+        request = build_add_or_modify_experiment_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.add_or_modify_experiment.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    add_or_modify_experiment.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def add(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.CreateRun"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """add.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateRun
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'CreateRun')
+        else:
+            _json = None
+
+        request = build_add_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.add.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    add.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """get.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            template_url=self.get.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_tags_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional[List[str]]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_tags_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: list[str]
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, '[str]')
+        else:
+            _json = None
+
+        request = build_delete_tags_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_tags_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_tags_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags"}  # type: ignore
+
+
+    @distributed_trace
+    def modify_or_delete_tags_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.DeleteOrModifyTags"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """modify_or_delete_tags_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteOrModifyTags
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteOrModifyTags')
+        else:
+            _json = None
+
+        request = build_modify_or_delete_tags_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.modify_or_delete_tags_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    modify_or_delete_tags_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_tags_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional[List[str]]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_tags_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: list[str]
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, '[str]')
+        else:
+            _json = None
+
+        request = build_delete_tags_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_tags_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_tags_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags"}  # type: ignore
+
+
+    @distributed_trace
+    def modify_or_delete_tags_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.DeleteOrModifyTags"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """modify_or_delete_tags_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteOrModifyTags
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteOrModifyTags')
+        else:
+            _json = None
+
+        request = build_modify_or_delete_tags_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.modify_or_delete_tags_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    modify_or_delete_tags_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_tags(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional[List[str]]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_tags.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: list[str]
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, '[str]')
+        else:
+            _json = None
+
+        request = build_delete_tags_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_tags.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_tags.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/tags"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_run_services_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.DeleteRunServices"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_run_services_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteRunServices')
+        else:
+            _json = None
+
+        request = build_delete_run_services_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_run_services_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_run_services_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/services"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_run_services_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.DeleteRunServices"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_run_services_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteRunServices')
+        else:
+            _json = None
+
+        request = build_delete_run_services_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_run_services_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_run_services_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/services"}  # type: ignore
+
+
+    @distributed_trace
+    def delete_run_services(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.DeleteRunServices"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """delete_run_services.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'DeleteRunServices')
+        else:
+            _json = None
+
+        request = build_delete_run_services_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.delete_run_services.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    delete_run_services.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/services"}  # type: ignore
+
+
+    @distributed_trace
+    def add_or_modify_run_service_instances(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        node_id,  # type: int
+        body=None,  # type: Optional["_models.AddOrModifyRunServiceInstancesRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunServiceInstances"
+        """add_or_modify_run_service_instances.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param node_id:
+        :type node_id: int
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.AddOrModifyRunServiceInstancesRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunServiceInstances, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunServiceInstances
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunServiceInstances"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'AddOrModifyRunServiceInstancesRequest')
+        else:
+            _json = None
+
+        request = build_add_or_modify_run_service_instances_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            node_id=node_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.add_or_modify_run_service_instances.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunServiceInstances', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    add_or_modify_run_service_instances.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_run_service_instances(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        node_id,  # type: int
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.RunServiceInstances"
+        """get_run_service_instances.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param node_id:
+        :type node_id: int
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: RunServiceInstances, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.RunServiceInstances
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.RunServiceInstances"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_get_run_service_instances_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            node_id=node_id,
+            template_url=self.get_run_service_instances.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('RunServiceInstances', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_run_service_instances.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_query_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.QueryParams"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """get_by_query_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.QueryParams
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                if body is not None:
+                    _json = self._serialize.body(body, 'QueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    experiment_name=experiment_name,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=self.get_by_query_by_experiment_name.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                if body is not None:
+                    _json = self._serialize.body(body, 'QueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_by_experiment_name_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    experiment_name=experiment_name,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_by_query_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs:query"}  # type: ignore
+
+    @distributed_trace
+    def get_by_query_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.QueryParams"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedRunList"]
+        """get_by_query_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.QueryParams
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedRunList or the result of cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedRunList"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                if body is not None:
+                    _json = self._serialize.body(body, 'QueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    experiment_id=experiment_id,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=self.get_by_query_by_experiment_id.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                if body is not None:
+                    _json = self._serialize.body(body, 'QueryParams')
+                else:
+                    _json = None
+                
+                request = build_get_by_query_by_experiment_id_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    experiment_id=experiment_id,
+                    content_type=content_type,
+                    json=_json,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedRunList", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_by_query_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs:query"}  # type: ignore
+
+    @distributed_trace
+    def get_by_ids_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_id,  # type: str
+        body=None,  # type: Optional["_models.GetRunsByIds"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchRunResult"
+        """get_by_ids_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.GetRunsByIds
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchRunResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchRunResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'GetRunsByIds')
+        else:
+            _json = None
+
+        request = build_get_by_ids_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_id=experiment_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.get_by_ids_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchRunResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_ids_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/runIds"}  # type: ignore
+
+
+    @distributed_trace
+    def get_by_ids_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        experiment_name,  # type: str
+        body=None,  # type: Optional["_models.GetRunsByIds"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchRunResult"
+        """get_by_ids_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.GetRunsByIds
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchRunResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchRunResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'GetRunsByIds')
+        else:
+            _json = None
+
+        request = build_get_by_ids_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            experiment_name=experiment_name,
+            content_type=content_type,
+            json=_json,
+            template_url=self.get_by_ids_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('BatchRunResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    get_by_ids_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/runIds"}  # type: ignore
+
+
+    @distributed_trace
+    def cancel_run_with_uri_by_experiment_id(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_id,  # type: str
+        cancelation_reason=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """cancel_run_with_uri_by_experiment_id.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_id:
+        :type experiment_id: str
+        :param cancelation_reason:
+        :type cancelation_reason: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_cancel_run_with_uri_by_experiment_id_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_id=experiment_id,
+            cancelation_reason=cancelation_reason,
+            template_url=self.cancel_run_with_uri_by_experiment_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    cancel_run_with_uri_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/cancel"}  # type: ignore
+
+
+    @distributed_trace
+    def cancel_run_with_uri_by_experiment_name(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        experiment_name,  # type: str
+        cancelation_reason=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Run"
+        """cancel_run_with_uri_by_experiment_name.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param experiment_name:
+        :type experiment_name: str
+        :param cancelation_reason:
+        :type cancelation_reason: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Run, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Run
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Run"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_cancel_run_with_uri_by_experiment_name_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            experiment_name=experiment_name,
+            cancelation_reason=cancelation_reason,
+            template_url=self.cancel_run_with_uri_by_experiment_name.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        deserialized = self._deserialize('Run', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    cancel_run_with_uri_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/cancel"}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_spans_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_spans_operations.py
new file mode 100644
index 00000000..7245f5ed
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/operations/_spans_operations.py
@@ -0,0 +1,429 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import TYPE_CHECKING
+
+from msrest import Serializer
+
+from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.mgmt.core.exceptions import ARMErrorFormat
+
+from .. import models as _models
+from .._vendor import _convert_request, _format_url_section
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Iterable, Optional, TypeVar
+    T = TypeVar('T')
+    ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+# fmt: off
+
+def build_post_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    content_type = kwargs.pop('content_type', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    if content_type is not None:
+        _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=_url,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_list_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+
+def build_get_active_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    run_id,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    continuation_token_parameter = kwargs.pop('continuation_token_parameter', None)  # type: Optional[str]
+
+    accept = "application/json"
+    # Construct URL
+    _url = kwargs.pop("template_url", "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans/active")  # pylint: disable=line-too-long
+    path_format_arguments = {
+        "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
+        "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
+        "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
+        "runId": _SERIALIZER.url("run_id", run_id, 'str'),
+    }
+
+    _url = _format_url_section(_url, **path_format_arguments)
+
+    # Construct parameters
+    _query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if continuation_token_parameter is not None:
+        _query_parameters['continuationToken'] = _SERIALIZER.query("continuation_token_parameter", continuation_token_parameter, 'str')
+
+    # Construct headers
+    _header_parameters = kwargs.pop("headers", {})  # type: Dict[str, Any]
+    _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+    return HttpRequest(
+        method="GET",
+        url=_url,
+        params=_query_parameters,
+        headers=_header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class SpansOperations(object):
+    """SpansOperations operations.
+
+    You should not instantiate this class directly. Instead, you should create a Client instance that
+    instantiates it for you and attaches it as an attribute.
+
+    :ivar models: Alias to model classes used in this operation group.
+    :type models: ~azure.mgmt.machinelearningservices.models
+    :param client: Client for service requests.
+    :param config: Configuration of service client.
+    :param serializer: An object model serializer.
+    :param deserializer: An object model deserializer.
+    """
+
+    models = _models
+
+    def __init__(self, client, config, serializer, deserializer):
+        self._client = client
+        self._serialize = serializer
+        self._deserialize = deserializer
+        self._config = config
+
+    @distributed_trace
+    def post(  # pylint: disable=inconsistent-return-statements
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        body=None,  # type: Optional["_models.RunStatusSpans"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """post.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.RunStatusSpans
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: None, or the result of cls(response)
+        :rtype: None
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType[None]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json")  # type: Optional[str]
+
+        if body is not None:
+            _json = self._serialize.body(body, 'RunStatusSpans')
+        else:
+            _json = None
+
+        request = build_post_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            content_type=content_type,
+            json=_json,
+            template_url=self.post.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+            request,
+            stream=False,
+            **kwargs
+        )
+        response = pipeline_response.http_response
+
+        if response.status_code not in []:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+            raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    post.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans"}  # type: ignore
+
+
+    @distributed_trace
+    def list(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedSpanDefinition1List"]
+        """list.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedSpanDefinition1List or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedSpanDefinition1List]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedSpanDefinition1List"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_list_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.list.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_list_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedSpanDefinition1List", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    list.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans"}  # type: ignore
+
+    @distributed_trace
+    def get_active(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id,  # type: str
+        continuation_token_parameter=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> Iterable["_models.PaginatedSpanDefinition1List"]
+        """get_active.
+
+        :param subscription_id: The Azure Subscription ID.
+        :type subscription_id: str
+        :param resource_group_name: The Name of the resource group in which the workspace is located.
+        :type resource_group_name: str
+        :param workspace_name: The name of the workspace.
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param continuation_token_parameter:
+        :type continuation_token_parameter: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: An iterator like instance of either PaginatedSpanDefinition1List or the result of
+         cls(response)
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedSpanDefinition1List]
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.PaginatedSpanDefinition1List"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+        def prepare_request(next_link=None):
+            if not next_link:
+                
+                request = build_get_active_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=self.get_active.metadata['url'],
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+
+            else:
+                
+                request = build_get_active_request(
+                    subscription_id=subscription_id,
+                    resource_group_name=resource_group_name,
+                    workspace_name=workspace_name,
+                    run_id=run_id,
+                    continuation_token_parameter=continuation_token_parameter,
+                    template_url=next_link,
+                )
+                request = _convert_request(request)
+                request.url = self._client.format_url(request.url)
+                request.method = "GET"
+            return request
+
+        def extract_data(pipeline_response):
+            deserialized = self._deserialize("PaginatedSpanDefinition1List", pipeline_response)
+            list_of_elem = deserialized.value
+            if cls:
+                list_of_elem = cls(list_of_elem)
+            return deserialized.next_link or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            request = prepare_request(next_link)
+
+            pipeline_response = self._client._pipeline.run(  # pylint: disable=protected-access
+                request,
+                stream=False,
+                **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+                raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+            return pipeline_response
+
+
+        return ItemPaged(
+            get_next, extract_data
+        )
+    get_active.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans/active"}  # type: ignore