diff options
Diffstat (limited to '.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio')
9 files changed, 1700 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/__init__.py new file mode 100644 index 00000000..f67ccda9 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/__init__.py @@ -0,0 +1,15 @@ +# 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 ._azure_machine_learning_workspaces import AzureMachineLearningWorkspaces +__all__ = ['AzureMachineLearningWorkspaces'] + +# `._patch.py` is used for handwritten extensions to the generated code +# Example: https://github.com/Azure/azure-sdk-for-python/blob/main/doc/dev/customize_code/how-to-patch-sdk-code.md +from ._patch import patch_sdk +patch_sdk() diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_azure_machine_learning_workspaces.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_azure_machine_learning_workspaces.py new file mode 100644 index 00000000..96732b90 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_azure_machine_learning_workspaces.py @@ -0,0 +1,95 @@ +# 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 copy import deepcopy +from typing import Any, Awaitable, Optional, TYPE_CHECKING + +from azure.core.rest import AsyncHttpResponse, HttpRequest +from azure.mgmt.core import AsyncARMPipelineClient +from msrest import Deserializer, Serializer + +from .. import models +from ._configuration import AzureMachineLearningWorkspacesConfiguration +from .operations import AssetsOperations, ExtensiveModelOperations, MigrationOperations, ModelsOperations + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + +class AzureMachineLearningWorkspaces: + """AzureMachineLearningWorkspaces. + + :ivar assets: AssetsOperations operations + :vartype assets: azure.mgmt.machinelearningservices.aio.operations.AssetsOperations + :ivar extensive_model: ExtensiveModelOperations operations + :vartype extensive_model: + azure.mgmt.machinelearningservices.aio.operations.ExtensiveModelOperations + :ivar migration: MigrationOperations operations + :vartype migration: azure.mgmt.machinelearningservices.aio.operations.MigrationOperations + :ivar models: ModelsOperations operations + :vartype models: azure.mgmt.machinelearningservices.aio.operations.ModelsOperations + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + :param base_url: Service URL. Default value is ''. + :type base_url: str + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + base_url: str = "", + **kwargs: Any + ) -> None: + self._config = AzureMachineLearningWorkspacesConfiguration(credential=credential, **kwargs) + self._client = AsyncARMPipelineClient(base_url=base_url, config=self._config, **kwargs) + + client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} + self._serialize = Serializer(client_models) + self._deserialize = Deserializer(client_models) + self._serialize.client_side_validation = False + self.assets = AssetsOperations(self._client, self._config, self._serialize, self._deserialize) + self.extensive_model = ExtensiveModelOperations(self._client, self._config, self._serialize, self._deserialize) + self.migration = MigrationOperations(self._client, self._config, self._serialize, self._deserialize) + self.models = ModelsOperations(self._client, self._config, self._serialize, self._deserialize) + + + def _send_request( + self, + request: HttpRequest, + **kwargs: Any + ) -> Awaitable[AsyncHttpResponse]: + """Runs the network request through the client's chained policies. + + >>> from azure.core.rest import HttpRequest + >>> request = HttpRequest("GET", "https://www.example.org/") + <HttpRequest [GET], url: 'https://www.example.org/'> + >>> response = await client._send_request(request) + <AsyncHttpResponse: 200 OK> + + For more information on this code flow, see https://aka.ms/azsdk/python/protocol/quickstart + + :param request: The network request you want to make. Required. + :type request: ~azure.core.rest.HttpRequest + :keyword bool stream: Whether the response payload will be streamed. Defaults to False. + :return: The response of your network call. Does not do error handling on your response. + :rtype: ~azure.core.rest.AsyncHttpResponse + """ + + request_copy = deepcopy(request) + request_copy.url = self._client.format_url(request_copy.url) + return self._client.send_request(request_copy, **kwargs) + + async def close(self) -> None: + await self._client.close() + + async def __aenter__(self) -> "AzureMachineLearningWorkspaces": + await self._client.__aenter__() + return self + + async def __aexit__(self, *exc_details) -> None: + await self._client.__aexit__(*exc_details) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_configuration.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_configuration.py new file mode 100644 index 00000000..26def54e --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_configuration.py @@ -0,0 +1,60 @@ +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- + +from typing import Any, TYPE_CHECKING + +from azure.core.configuration import Configuration +from azure.core.pipeline import policies +from azure.mgmt.core.policies import ARMHttpLoggingPolicy, AsyncARMChallengeAuthenticationPolicy + +from .._version import VERSION + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + + +class AzureMachineLearningWorkspacesConfiguration(Configuration): + """Configuration for AzureMachineLearningWorkspaces. + + Note that all parameters used to create this instance are saved as instance + attributes. + + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + **kwargs: Any + ) -> None: + super(AzureMachineLearningWorkspacesConfiguration, self).__init__(**kwargs) + if credential is None: + raise ValueError("Parameter 'credential' must not be None.") + + self.credential = credential + self.credential_scopes = kwargs.pop('credential_scopes', ['https://management.azure.com/.default']) + kwargs.setdefault('sdk_moniker', 'mgmt-machinelearningservices/{}'.format(VERSION)) + self._configure(**kwargs) + + def _configure( + self, + **kwargs: Any + ) -> None: + self.user_agent_policy = kwargs.get('user_agent_policy') or policies.UserAgentPolicy(**kwargs) + self.headers_policy = kwargs.get('headers_policy') or policies.HeadersPolicy(**kwargs) + self.proxy_policy = kwargs.get('proxy_policy') or policies.ProxyPolicy(**kwargs) + self.logging_policy = kwargs.get('logging_policy') or policies.NetworkTraceLoggingPolicy(**kwargs) + self.http_logging_policy = kwargs.get('http_logging_policy') or ARMHttpLoggingPolicy(**kwargs) + self.retry_policy = kwargs.get('retry_policy') or policies.AsyncRetryPolicy(**kwargs) + self.custom_hook_policy = kwargs.get('custom_hook_policy') or policies.CustomHookPolicy(**kwargs) + self.redirect_policy = kwargs.get('redirect_policy') or policies.AsyncRedirectPolicy(**kwargs) + self.authentication_policy = kwargs.get('authentication_policy') + if self.credential and not self.authentication_policy: + self.authentication_policy = AsyncARMChallengeAuthenticationPolicy(self.credential, *self.credential_scopes, **kwargs) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_patch.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_patch.py new file mode 100644 index 00000000..74e48ecd --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/_patch.py @@ -0,0 +1,31 @@ +# coding=utf-8 +# -------------------------------------------------------------------------- +# +# Copyright (c) Microsoft Corporation. All rights reserved. +# +# The MIT License (MIT) +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the ""Software""), to +# deal in the Software without restriction, including without limitation the +# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or +# sell copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in +# all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS +# IN THE SOFTWARE. +# +# -------------------------------------------------------------------------- + +# This file is used for handwritten extensions to the generated code. Example: +# https://github.com/Azure/azure-sdk-for-python/blob/main/doc/dev/customize_code/how-to-patch-sdk-code.md +def patch_sdk(): + pass
\ No newline at end of file diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/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/aio/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/aio/operations/_assets_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_assets_operations.py new file mode 100644 index 00000000..20f7a4cb --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_assets_operations.py @@ -0,0 +1,403 @@ +# 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 Any, Callable, Dict, Generic, List, Optional, TypeVar, Union +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 AsyncHttpResponse +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._assets_operations import build_create_request, build_delete_request, build_list_request, build_patch_request, build_query_by_id_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class AssetsOperations: + """AssetsOperations async 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) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + @distributed_trace_async + async def create( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.Asset"] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def list( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: Optional[str] = None, + project_id: Optional[str] = None, + name: Optional[str] = None, + tag: Optional[str] = None, + count: Optional[int] = None, + skip_token: Optional[str] = None, + tags: Optional[str] = None, + properties: Optional[str] = None, + type: Optional[str] = None, + orderby: Optional[Union[str, "_models.OrderString"]] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def patch( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: List["_models.Operation"], + **kwargs: Any + ) -> "_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 = await 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_async + async def delete( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + **kwargs: Any + ) -> 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 = await 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_async + async def query_by_id( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + **kwargs: Any + ) -> "_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 = await 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/aio/operations/_extensive_model_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_extensive_model_operations.py new file mode 100644 index 00000000..6f821f49 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_extensive_model_operations.py @@ -0,0 +1,103 @@ +# 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 Any, Callable, Dict, Generic, Optional, TypeVar +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 AsyncHttpResponse +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._extensive_model_operations import build_query_by_id_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class ExtensiveModelOperations: + """ExtensiveModelOperations async 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) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + @distributed_trace_async + async def query_by_id( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + **kwargs: Any + ) -> "_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 = await 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/aio/operations/_migration_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_migration_operations.py new file mode 100644 index 00000000..b6c4b7e4 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_migration_operations.py @@ -0,0 +1,99 @@ +# 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 Any, Callable, Dict, Generic, Optional, TypeVar +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 AsyncHttpResponse +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._migration_operations import build_start_migration_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class MigrationOperations: + """MigrationOperations async 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) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + @distributed_trace_async + async def start_migration( + self, + migration: Optional[str] = None, + timeout: Optional[str] = "00:01:00", + collection_id: Optional[str] = None, + workspace_id: Optional[str] = None, + **kwargs: Any + ) -> 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 = await 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/aio/operations/_models_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_models_operations.py new file mode 100644 index 00000000..f666dcec --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/model_dataplane/aio/operations/_models_operations.py @@ -0,0 +1,875 @@ +# 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 Any, Callable, Dict, Generic, List, Optional, TypeVar, Union +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 AsyncHttpResponse +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._models_operations import build_batch_get_resolved_uris_request, build_batch_query_request, build_create_unregistered_input_model_request, build_create_unregistered_output_model_request, build_delete_request, build_deployment_settings_request, build_list_query_post_request, build_list_request, build_patch_request, build_query_by_id_request, build_register_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class ModelsOperations: + """ModelsOperations async 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) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + @distributed_trace_async + async def register( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: "_models.Model", + auto_version: Optional[bool] = True, + **kwargs: Any + ) -> "_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 = await 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_async + async def list( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + name: Optional[str] = None, + tag: Optional[str] = None, + version: Optional[str] = None, + framework: Optional[str] = None, + description: Optional[str] = None, + count: Optional[int] = None, + offset: Optional[int] = None, + skip_token: Optional[str] = None, + tags: Optional[str] = None, + properties: Optional[str] = None, + run_id: Optional[str] = None, + dataset_id: Optional[str] = None, + order_by: Optional[str] = None, + latest_version_only: Optional[bool] = False, + feed: Optional[str] = None, + list_view_type: Optional[Union[str, "_models.ListViewType"]] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def create_unregistered_input_model( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: "_models.CreateUnregisteredInputModelDto", + **kwargs: Any + ) -> "_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 = await 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_async + async def create_unregistered_output_model( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: "_models.CreateUnregisteredOutputModelDto", + **kwargs: Any + ) -> "_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 = await 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_async + async def batch_get_resolved_uris( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.BatchGetResolvedUrisDto"] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def query_by_id( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + include_deployment_settings: Optional[bool] = False, + **kwargs: Any + ) -> "_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 = await 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_async + async def delete( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + **kwargs: Any + ) -> 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 = await 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_async + async def patch( + self, + id: str, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: List["_models.Operation"], + **kwargs: Any + ) -> "_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 = await 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_async + async def list_query_post( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.ListModelsRequest"] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def batch_query( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.ModelBatchDto"] = None, + **kwargs: Any + ) -> "_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 = await 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_async + async def deployment_settings( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.ModelSettingsIdentifiers"] = None, + **kwargs: Any + ) -> 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 = await 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 + |