diff options
Diffstat (limited to '.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/operations')
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 + |