two version of R2R are hereHEADmaster

5 files changed, 2233 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/__init__.py
new file mode 100644
index 00000000..261577d5
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/__init__.py
@@ -0,0 +1,19 @@
+# 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 ._assets_operations import AssetsOperations
+from ._extensive_model_operations import ExtensiveModelOperations
+from ._migration_operations import MigrationOperations
+from ._models_operations import ModelsOperations
+
+__all__ = [
+    'AssetsOperations',
+    'ExtensiveModelOperations',
+    'MigrationOperations',
+    'ModelsOperations',
+]
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_assets_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_assets_operations.py
new file mode 100644
index 00000000..65afa16f
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_assets_operations.py
@@ -0,0 +1,609 @@
+# 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.
+# --------------------------------------------------------------------------
+import functools
+from typing import TYPE_CHECKING
+import warnings
+
+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 msrest import Serializer
+
+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, Generic, 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_create_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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets')
+    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_list_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    run_id = kwargs.pop('run_id', None)  # type: Optional[str]
+    project_id = kwargs.pop('project_id', None)  # type: Optional[str]
+    name = kwargs.pop('name', None)  # type: Optional[str]
+    tag = kwargs.pop('tag', None)  # type: Optional[str]
+    count = kwargs.pop('count', None)  # type: Optional[int]
+    skip_token = kwargs.pop('skip_token', None)  # type: Optional[str]
+    tags = kwargs.pop('tags', None)  # type: Optional[str]
+    properties = kwargs.pop('properties', None)  # type: Optional[str]
+    type = kwargs.pop('type', None)  # type: Optional[str]
+    orderby = kwargs.pop('orderby', None)  # type: Optional[Union[str, "_models.OrderString"]]
+
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets')
+    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 run_id is not None:
+        query_parameters['runId'] = _SERIALIZER.query("run_id", run_id, 'str')
+    if project_id is not None:
+        query_parameters['projectId'] = _SERIALIZER.query("project_id", project_id, 'str')
+    if name is not None:
+        query_parameters['name'] = _SERIALIZER.query("name", name, 'str')
+    if tag is not None:
+        query_parameters['tag'] = _SERIALIZER.query("tag", tag, 'str')
+    if count is not None:
+        query_parameters['count'] = _SERIALIZER.query("count", count, 'int')
+    if skip_token is not None:
+        query_parameters['$skipToken'] = _SERIALIZER.query("skip_token", skip_token, 'str')
+    if tags is not None:
+        query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
+    if properties is not None:
+        query_parameters['properties'] = _SERIALIZER.query("properties", properties, 'str')
+    if type is not None:
+        query_parameters['type'] = _SERIALIZER.query("type", type, 'str')
+    if orderby is not None:
+        query_parameters['orderby'] = _SERIALIZER.query("orderby", orderby, '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_patch_request(
+    id,  # type: str
+    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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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_delete_request(
+    id,  # type: str
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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)
+
+    return HttpRequest(
+        method="DELETE",
+        url=url,
+        **kwargs
+    )
+
+
+def build_query_by_id_request(
+    id,  # type: str
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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 AssetsOperations(object):
+    """AssetsOperations 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 create(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.Asset"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Asset"
+        """create.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.Asset
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Asset, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Asset
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Asset"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'Asset')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'Asset')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_create_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.create.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Asset', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    create.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets'}  # type: ignore
+
+
+    @distributed_trace
+    def list(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        run_id=None,  # type: Optional[str]
+        project_id=None,  # type: Optional[str]
+        name=None,  # type: Optional[str]
+        tag=None,  # type: Optional[str]
+        count=None,  # type: Optional[int]
+        skip_token=None,  # type: Optional[str]
+        tags=None,  # type: Optional[str]
+        properties=None,  # type: Optional[str]
+        type=None,  # type: Optional[str]
+        orderby=None,  # type: Optional[Union[str, "_models.OrderString"]]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.AssetPaginatedResult"
+        """list.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param run_id:
+        :type run_id: str
+        :param project_id:
+        :type project_id: str
+        :param name:
+        :type name: str
+        :param tag:
+        :type tag: str
+        :param count:
+        :type count: int
+        :param skip_token:
+        :type skip_token: str
+        :param tags:
+        :type tags: str
+        :param properties:
+        :type properties: str
+        :param type:
+        :type type: str
+        :param orderby:
+        :type orderby: str or ~azure.mgmt.machinelearningservices.models.OrderString
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: AssetPaginatedResult, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.AssetPaginatedResult
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.AssetPaginatedResult"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_list_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            run_id=run_id,
+            project_id=project_id,
+            name=name,
+            tag=tag,
+            count=count,
+            skip_token=skip_token,
+            tags=tags,
+            properties=properties,
+            type=type,
+            orderby=orderby,
+            template_url=self.list.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('AssetPaginatedResult', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    list.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets'}  # type: ignore
+
+
+    @distributed_trace
+    def patch(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body,  # type: List["_models.Operation"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Asset"
+        """patch.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: list[~azure.mgmt.machinelearningservices.models.Operation]
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Asset, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Asset
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Asset"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            _json = self._serialize.body(body, '[Operation]')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            _json = self._serialize.body(body, '[Operation]')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_patch_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.patch.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Asset', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    patch.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}'}  # type: ignore
+
+
+    @distributed_trace
+    def delete(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """delete.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :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', {}))
+
+        
+        request = build_delete_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            template_url=self.delete.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200, 204]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            raise HttpResponseError(response=response, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    delete.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}'}  # type: ignore
+
+
+    @distributed_trace
+    def query_by_id(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Asset"
+        """query_by_id.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Asset, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Asset
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Asset"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_query_by_id_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            template_url=self.query_by_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Asset', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    query_by_id.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/assets/{id}'}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_extensive_model_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_extensive_model_operations.py
new file mode 100644
index 00000000..cd7703c6
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_extensive_model_operations.py
@@ -0,0 +1,144 @@
+# 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.
+# --------------------------------------------------------------------------
+import functools
+from typing import TYPE_CHECKING
+import warnings
+
+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 msrest import Serializer
+
+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, Generic, 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_query_by_id_request(
+    id,  # type: str
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/extensiveModels/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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 ExtensiveModelOperations(object):
+    """ExtensiveModelOperations 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 query_by_id(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ExtensiveModel"
+        """query_by_id.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ExtensiveModel, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ExtensiveModel
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ExtensiveModel"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_query_by_id_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            template_url=self.query_by_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('ExtensiveModel', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    query_by_id.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/extensiveModels/{id}'}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_migration_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_migration_operations.py
new file mode 100644
index 00000000..e8a39933
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_migration_operations.py
@@ -0,0 +1,139 @@
+# 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.
+# --------------------------------------------------------------------------
+import functools
+from typing import TYPE_CHECKING
+import warnings
+
+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 msrest import Serializer
+
+from .. import models as _models
+from .._vendor import _convert_request
+
+if TYPE_CHECKING:
+    # pylint: disable=unused-import,ungrouped-imports
+    from typing import Any, Callable, Dict, Generic, 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_start_migration_request(
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    migration = kwargs.pop('migration', None)  # type: Optional[str]
+    timeout = kwargs.pop('timeout', "00:01:00")  # type: Optional[str]
+    collection_id = kwargs.pop('collection_id', None)  # type: Optional[str]
+    workspace_id = kwargs.pop('workspace_id', None)  # type: Optional[str]
+
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/meta/migration')
+
+    # Construct parameters
+    query_parameters = kwargs.pop("params", {})  # type: Dict[str, Any]
+    if migration is not None:
+        query_parameters['migration'] = _SERIALIZER.query("migration", migration, 'str')
+    if timeout is not None:
+        query_parameters['timeout'] = _SERIALIZER.query("timeout", timeout, 'str')
+    if collection_id is not None:
+        query_parameters['collectionId'] = _SERIALIZER.query("collection_id", collection_id, 'str')
+    if workspace_id is not None:
+        query_parameters['workspaceId'] = _SERIALIZER.query("workspace_id", workspace_id, 'str')
+
+    return HttpRequest(
+        method="POST",
+        url=url,
+        params=query_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class MigrationOperations(object):
+    """MigrationOperations 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 start_migration(
+        self,
+        migration=None,  # type: Optional[str]
+        timeout="00:01:00",  # type: Optional[str]
+        collection_id=None,  # type: Optional[str]
+        workspace_id=None,  # type: Optional[str]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """start_migration.
+
+        :param migration:
+        :type migration: str
+        :param timeout:
+        :type timeout: str
+        :param collection_id:
+        :type collection_id: str
+        :param workspace_id:
+        :type workspace_id: str
+        :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', {}))
+
+        
+        request = build_start_migration_request(
+            migration=migration,
+            timeout=timeout,
+            collection_id=collection_id,
+            workspace_id=workspace_id,
+            template_url=self.start_migration.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    start_migration.metadata = {'url': '/modelregistry/v1.0/meta/migration'}  # type: ignore
+
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_models_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_models_operations.py
new file mode 100644
index 00000000..e65f830d
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations/_models_operations.py
@@ -0,0 +1,1322 @@
+# 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.
+# --------------------------------------------------------------------------
+import functools
+from typing import TYPE_CHECKING
+import warnings
+
+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 msrest import Serializer
+
+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, Generic, 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_register_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]
+    auto_version = kwargs.pop('auto_version', True)  # type: Optional[bool]
+
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models')
+    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 auto_version is not None:
+        query_parameters['autoVersion'] = _SERIALIZER.query("auto_version", auto_version, '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_list_request(
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    name = kwargs.pop('name', None)  # type: Optional[str]
+    tag = kwargs.pop('tag', None)  # type: Optional[str]
+    version = kwargs.pop('version', None)  # type: Optional[str]
+    framework = kwargs.pop('framework', None)  # type: Optional[str]
+    description = kwargs.pop('description', None)  # type: Optional[str]
+    count = kwargs.pop('count', None)  # type: Optional[int]
+    offset = kwargs.pop('offset', None)  # type: Optional[int]
+    skip_token = kwargs.pop('skip_token', None)  # type: Optional[str]
+    tags = kwargs.pop('tags', None)  # type: Optional[str]
+    properties = kwargs.pop('properties', None)  # type: Optional[str]
+    run_id = kwargs.pop('run_id', None)  # type: Optional[str]
+    dataset_id = kwargs.pop('dataset_id', None)  # type: Optional[str]
+    order_by = kwargs.pop('order_by', None)  # type: Optional[str]
+    latest_version_only = kwargs.pop('latest_version_only', False)  # type: Optional[bool]
+    feed = kwargs.pop('feed', None)  # type: Optional[str]
+    list_view_type = kwargs.pop('list_view_type', None)  # type: Optional[Union[str, "_models.ListViewType"]]
+
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models')
+    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 name is not None:
+        query_parameters['name'] = _SERIALIZER.query("name", name, 'str')
+    if tag is not None:
+        query_parameters['tag'] = _SERIALIZER.query("tag", tag, 'str')
+    if version is not None:
+        query_parameters['version'] = _SERIALIZER.query("version", version, 'str')
+    if framework is not None:
+        query_parameters['framework'] = _SERIALIZER.query("framework", framework, 'str')
+    if description is not None:
+        query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
+    if count is not None:
+        query_parameters['count'] = _SERIALIZER.query("count", count, 'int')
+    if offset is not None:
+        query_parameters['offset'] = _SERIALIZER.query("offset", offset, 'int')
+    if skip_token is not None:
+        query_parameters['$skipToken'] = _SERIALIZER.query("skip_token", skip_token, 'str')
+    if tags is not None:
+        query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
+    if properties is not None:
+        query_parameters['properties'] = _SERIALIZER.query("properties", properties, 'str')
+    if run_id is not None:
+        query_parameters['runId'] = _SERIALIZER.query("run_id", run_id, 'str')
+    if dataset_id is not None:
+        query_parameters['datasetId'] = _SERIALIZER.query("dataset_id", dataset_id, 'str')
+    if order_by is not None:
+        query_parameters['orderBy'] = _SERIALIZER.query("order_by", order_by, 'str')
+    if latest_version_only is not None:
+        query_parameters['latestVersionOnly'] = _SERIALIZER.query("latest_version_only", latest_version_only, 'bool')
+    if feed is not None:
+        query_parameters['feed'] = _SERIALIZER.query("feed", feed, 'str')
+    if list_view_type is not None:
+        query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, '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_create_unregistered_input_model_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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/createUnregisteredInput')
+    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_create_unregistered_output_model_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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/createUnregisteredOutput')
+    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_resolved_uris_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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/batchGetResolvedUris')
+    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_query_by_id_request(
+    id,  # type: str
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    include_deployment_settings = kwargs.pop('include_deployment_settings', False)  # type: Optional[bool]
+
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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 include_deployment_settings is not None:
+        query_parameters['includeDeploymentSettings'] = _SERIALIZER.query("include_deployment_settings", include_deployment_settings, '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_delete_request(
+    id,  # type: str
+    subscription_id,  # type: str
+    resource_group_name,  # type: str
+    workspace_name,  # type: str
+    **kwargs  # type: Any
+):
+    # type: (...) -> HttpRequest
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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)
+
+    return HttpRequest(
+        method="DELETE",
+        url=url,
+        **kwargs
+    )
+
+
+def build_patch_request(
+    id,  # type: str
+    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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}')
+    path_format_arguments = {
+        "id": _SERIALIZER.url("id", id, 'str'),
+        "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_list_query_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, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/list')
+    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_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]
+
+    accept = "application/json, text/json"
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/querybatch')
+    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_deployment_settings_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]
+
+    # Construct URL
+    url = kwargs.pop("template_url", '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/deploymentSettings')
+    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')
+
+    return HttpRequest(
+        method="POST",
+        url=url,
+        headers=header_parameters,
+        **kwargs
+    )
+
+# fmt: on
+class ModelsOperations(object):
+    """ModelsOperations 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 register(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body,  # type: "_models.Model"
+        auto_version=True,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Model"
+        """register.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.Model
+        :param auto_version:
+        :type auto_version: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Model, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Model
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Model"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            _json = self._serialize.body(body, 'Model')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            _json = self._serialize.body(body, 'Model')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_register_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            auto_version=auto_version,
+            template_url=self.register.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Model', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    register.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models'}  # type: ignore
+
+
+    @distributed_trace
+    def list(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        name=None,  # type: Optional[str]
+        tag=None,  # type: Optional[str]
+        version=None,  # type: Optional[str]
+        framework=None,  # type: Optional[str]
+        description=None,  # type: Optional[str]
+        count=None,  # type: Optional[int]
+        offset=None,  # type: Optional[int]
+        skip_token=None,  # type: Optional[str]
+        tags=None,  # type: Optional[str]
+        properties=None,  # type: Optional[str]
+        run_id=None,  # type: Optional[str]
+        dataset_id=None,  # type: Optional[str]
+        order_by=None,  # type: Optional[str]
+        latest_version_only=False,  # type: Optional[bool]
+        feed=None,  # type: Optional[str]
+        list_view_type=None,  # type: Optional[Union[str, "_models.ListViewType"]]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ModelPagedResponse"
+        """list.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param name:
+        :type name: str
+        :param tag:
+        :type tag: str
+        :param version:
+        :type version: str
+        :param framework:
+        :type framework: str
+        :param description:
+        :type description: str
+        :param count:
+        :type count: int
+        :param offset:
+        :type offset: int
+        :param skip_token:
+        :type skip_token: str
+        :param tags:
+        :type tags: str
+        :param properties:
+        :type properties: str
+        :param run_id:
+        :type run_id: str
+        :param dataset_id:
+        :type dataset_id: str
+        :param order_by:
+        :type order_by: str
+        :param latest_version_only:
+        :type latest_version_only: bool
+        :param feed:
+        :type feed: str
+        :param list_view_type:
+        :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ModelPagedResponse, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ModelPagedResponse
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ModelPagedResponse"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_list_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            name=name,
+            tag=tag,
+            version=version,
+            framework=framework,
+            description=description,
+            count=count,
+            offset=offset,
+            skip_token=skip_token,
+            tags=tags,
+            properties=properties,
+            run_id=run_id,
+            dataset_id=dataset_id,
+            order_by=order_by,
+            latest_version_only=latest_version_only,
+            feed=feed,
+            list_view_type=list_view_type,
+            template_url=self.list.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('ModelPagedResponse', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    list.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models'}  # type: ignore
+
+
+    @distributed_trace
+    def create_unregistered_input_model(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body,  # type: "_models.CreateUnregisteredInputModelDto"
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Model"
+        """create_unregistered_input_model.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateUnregisteredInputModelDto
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Model, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Model
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Model"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            _json = self._serialize.body(body, 'CreateUnregisteredInputModelDto')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            _json = self._serialize.body(body, 'CreateUnregisteredInputModelDto')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_create_unregistered_input_model_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.create_unregistered_input_model.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Model', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    create_unregistered_input_model.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/createUnregisteredInput'}  # type: ignore
+
+
+    @distributed_trace
+    def create_unregistered_output_model(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body,  # type: "_models.CreateUnregisteredOutputModelDto"
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Model"
+        """create_unregistered_output_model.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.CreateUnregisteredOutputModelDto
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Model, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Model
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Model"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            _json = self._serialize.body(body, 'CreateUnregisteredOutputModelDto')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            _json = self._serialize.body(body, 'CreateUnregisteredOutputModelDto')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_create_unregistered_output_model_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.create_unregistered_output_model.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Model', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    create_unregistered_output_model.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/createUnregisteredOutput'}  # type: ignore
+
+
+    @distributed_trace
+    def batch_get_resolved_uris(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.BatchGetResolvedUrisDto"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.BatchModelPathResponseDto"
+        """batch_get_resolved_uris.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.BatchGetResolvedUrisDto
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: BatchModelPathResponseDto, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.BatchModelPathResponseDto
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.BatchModelPathResponseDto"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'BatchGetResolvedUrisDto')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'BatchGetResolvedUrisDto')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_batch_get_resolved_uris_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.batch_get_resolved_uris.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('BatchModelPathResponseDto', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_get_resolved_uris.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/batchGetResolvedUris'}  # type: ignore
+
+
+    @distributed_trace
+    def query_by_id(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        include_deployment_settings=False,  # type: Optional[bool]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Model"
+        """query_by_id.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param include_deployment_settings:
+        :type include_deployment_settings: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Model, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Model
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Model"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        
+        request = build_query_by_id_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            include_deployment_settings=include_deployment_settings,
+            template_url=self.query_by_id.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Model', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    query_by_id.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}'}  # type: ignore
+
+
+    @distributed_trace
+    def delete(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """delete.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :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', {}))
+
+        
+        request = build_delete_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            template_url=self.delete.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200, 204]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            raise HttpResponseError(response=response, error_format=ARMErrorFormat)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    delete.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}'}  # type: ignore
+
+
+    @distributed_trace
+    def patch(
+        self,
+        id,  # type: str
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body,  # type: List["_models.Operation"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.Model"
+        """patch.
+
+        :param id:
+        :type id: str
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: list[~azure.mgmt.machinelearningservices.models.Operation]
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: Model, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.Model
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.Model"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            _json = self._serialize.body(body, '[Operation]')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            _json = self._serialize.body(body, '[Operation]')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_patch_request(
+            id=id,
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.patch.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('Model', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    patch.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{id}'}  # type: ignore
+
+
+    @distributed_trace
+    def list_query_post(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.ListModelsRequest"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ModelListModelsRequestPagedResponse"
+        """list_query_post.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ListModelsRequest
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ModelListModelsRequestPagedResponse, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ModelListModelsRequestPagedResponse
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ModelListModelsRequestPagedResponse"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ListModelsRequest')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ListModelsRequest')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_list_query_post_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.list_query_post.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('ModelListModelsRequestPagedResponse', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    list_query_post.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/list'}  # type: ignore
+
+
+    @distributed_trace
+    def batch_query(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.ModelBatchDto"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> "_models.ModelBatchResponseDto"
+        """batch_query.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ModelBatchDto
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: ModelBatchResponseDto, or the result of cls(response)
+        :rtype: ~azure.mgmt.machinelearningservices.models.ModelBatchResponseDto
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        cls = kwargs.pop('cls', None)  # type: ClsType["_models.ModelBatchResponseDto"]
+        error_map = {
+            401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+        }
+        error_map.update(kwargs.pop('error_map', {}))
+
+        content_type = kwargs.pop('content_type', "application/json-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ModelBatchDto')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ModelBatchDto')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_batch_query_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.batch_query.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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('ModelBatchResponseDto', pipeline_response)
+
+        if cls:
+            return cls(pipeline_response, deserialized, {})
+
+        return deserialized
+
+    batch_query.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/querybatch'}  # type: ignore
+
+
+    @distributed_trace
+    def deployment_settings(
+        self,
+        subscription_id,  # type: str
+        resource_group_name,  # type: str
+        workspace_name,  # type: str
+        body=None,  # type: Optional["_models.ModelSettingsIdentifiers"]
+        **kwargs  # type: Any
+    ):
+        # type: (...) -> None
+        """deployment_settings.
+
+        :param subscription_id:
+        :type subscription_id: str
+        :param resource_group_name:
+        :type resource_group_name: str
+        :param workspace_name:
+        :type workspace_name: str
+        :param body:
+        :type body: ~azure.mgmt.machinelearningservices.models.ModelSettingsIdentifiers
+        :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-patch+json")  # type: Optional[str]
+
+        _json = None
+        _content = None
+        if content_type.split(";")[0] in ['application/json', 'text/json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ModelSettingsIdentifiers')
+        elif content_type.split(";")[0] in ['application/json-patch+json', 'application/*+json']:
+            if body is not None:
+                _json = self._serialize.body(body, 'ModelSettingsIdentifiers')
+        else:
+            raise ValueError(
+                "The content_type '{}' is not one of the allowed values: "
+                "['application/json-patch+json', 'application/json', 'text/json', 'application/*+json']".format(content_type)
+            )
+
+        request = build_deployment_settings_request(
+            subscription_id=subscription_id,
+            resource_group_name=resource_group_name,
+            workspace_name=workspace_name,
+            content_type=content_type,
+            json=_json,
+            content=_content,
+            template_url=self.deployment_settings.metadata['url'],
+        )
+        request = _convert_request(request)
+        request.url = self._client.format_url(request.url)
+
+        pipeline_response = self._client._pipeline.run(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)
+
+        if cls:
+            return cls(pipeline_response, None, {})
+
+    deployment_settings.metadata = {'url': '/modelregistry/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/deploymentSettings'}  # type: ignore
+