diff options
Diffstat (limited to '.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio')
13 files changed, 6772 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/__init__.py new file mode 100644 index 00000000..f67ccda9 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/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/runhistory/aio/_azure_machine_learning_workspaces.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/_azure_machine_learning_workspaces.py new file mode 100644 index 00000000..92b775fb --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/_azure_machine_learning_workspaces.py @@ -0,0 +1,110 @@ +# 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, TYPE_CHECKING + +from msrest import Deserializer, Serializer + +from azure.core.rest import AsyncHttpResponse, HttpRequest +from azure.mgmt.core import AsyncARMPipelineClient + +from .. import models +from ._configuration import AzureMachineLearningWorkspacesConfiguration +from .operations import DeleteOperations, EventsOperations, ExperimentsOperations, MetricOperations, RunArtifactsOperations, RunOperations, RunsOperations, SpansOperations + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + +class AzureMachineLearningWorkspaces: # pylint: disable=too-many-instance-attributes + """AzureMachineLearningWorkspaces. + + :ivar delete: DeleteOperations operations + :vartype delete: azure.mgmt.machinelearningservices.aio.operations.DeleteOperations + :ivar events: EventsOperations operations + :vartype events: azure.mgmt.machinelearningservices.aio.operations.EventsOperations + :ivar experiments: ExperimentsOperations operations + :vartype experiments: azure.mgmt.machinelearningservices.aio.operations.ExperimentsOperations + :ivar metric: MetricOperations operations + :vartype metric: azure.mgmt.machinelearningservices.aio.operations.MetricOperations + :ivar runs: RunsOperations operations + :vartype runs: azure.mgmt.machinelearningservices.aio.operations.RunsOperations + :ivar run_artifacts: RunArtifactsOperations operations + :vartype run_artifacts: + azure.mgmt.machinelearningservices.aio.operations.RunArtifactsOperations + :ivar run: RunOperations operations + :vartype run: azure.mgmt.machinelearningservices.aio.operations.RunOperations + :ivar spans: SpansOperations operations + :vartype spans: azure.mgmt.machinelearningservices.aio.operations.SpansOperations + :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 + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no + Retry-After header is present. + """ + + 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.delete = DeleteOperations(self._client, self._config, self._serialize, self._deserialize) + self.events = EventsOperations(self._client, self._config, self._serialize, self._deserialize) + self.experiments = ExperimentsOperations(self._client, self._config, self._serialize, self._deserialize) + self.metric = MetricOperations(self._client, self._config, self._serialize, self._deserialize) + self.runs = RunsOperations(self._client, self._config, self._serialize, self._deserialize) + self.run_artifacts = RunArtifactsOperations(self._client, self._config, self._serialize, self._deserialize) + self.run = RunOperations(self._client, self._config, self._serialize, self._deserialize) + self.spans = SpansOperations(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/runhistory/aio/_configuration.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/_configuration.py new file mode 100644 index 00000000..6d0b0e4d --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/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): # pylint: disable=too-many-instance-attributes + """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/runhistory/aio/_patch.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/_patch.py new file mode 100644 index 00000000..74e48ecd --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/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/runhistory/aio/operations/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/__init__.py new file mode 100644 index 00000000..3e84a44a --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/__init__.py @@ -0,0 +1,27 @@ +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- + +from ._delete_operations import DeleteOperations +from ._events_operations import EventsOperations +from ._experiments_operations import ExperimentsOperations +from ._metric_operations import MetricOperations +from ._runs_operations import RunsOperations +from ._run_artifacts_operations import RunArtifactsOperations +from ._run_operations import RunOperations +from ._spans_operations import SpansOperations + +__all__ = [ + 'DeleteOperations', + 'EventsOperations', + 'ExperimentsOperations', + 'MetricOperations', + 'RunsOperations', + 'RunArtifactsOperations', + 'RunOperations', + 'SpansOperations', +] diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_delete_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_delete_operations.py new file mode 100644 index 00000000..6841ffdc --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_delete_operations.py @@ -0,0 +1,173 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, Callable, Dict, Optional, TypeVar + +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._delete_operations import build_get_configuration_request, build_patch_configuration_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class DeleteOperations: + """DeleteOperations 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 patch_configuration( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.DeleteConfiguration"] = None, + **kwargs: Any + ) -> "_models.DeleteConfiguration": + """patch_configuration. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration + :keyword callable cls: A custom type or function that will be passed the direct response + :return: DeleteConfiguration, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.DeleteConfiguration"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteConfiguration') + else: + _json = None + + request = build_patch_configuration_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=self.patch_configuration.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('DeleteConfiguration', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + patch_configuration.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration"} # type: ignore + + + @distributed_trace_async + async def get_configuration( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + **kwargs: Any + ) -> "_models.DeleteConfiguration": + """get_configuration. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: DeleteConfiguration, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.DeleteConfiguration + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.DeleteConfiguration"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_configuration_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + template_url=self.get_configuration.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('DeleteConfiguration', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_configuration.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/deleteConfiguration"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_events_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_events_operations.py new file mode 100644 index 00000000..03dc9d42 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_events_operations.py @@ -0,0 +1,480 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, Callable, Dict, Optional, TypeVar + +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._events_operations import build_batch_post_by_experiment_id_request, build_batch_post_by_experiment_name_request, build_batch_post_request, build_post_by_experiment_id_request, build_post_by_experiment_name_request, build_post_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class EventsOperations: + """EventsOperations 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 batch_post_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + body: Optional["_models.BatchEventCommand"] = None, + **kwargs: Any + ) -> "_models.BatchEventCommandResult": + """batch_post_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchEventCommandResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchEventCommandResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchEventCommand') + else: + _json = None + + request = build_batch_post_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.batch_post_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchEventCommandResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_post_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/events"} # type: ignore + + + @distributed_trace_async + async def batch_post_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.BatchEventCommand"] = None, + **kwargs: Any + ) -> "_models.BatchEventCommandResult": + """batch_post_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchEventCommandResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchEventCommandResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchEventCommand') + else: + _json = None + + request = build_batch_post_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.batch_post_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchEventCommandResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_post_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/events"} # type: ignore + + + @distributed_trace_async + async def batch_post( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.BatchEventCommand"] = None, + **kwargs: Any + ) -> "_models.BatchEventCommandResult": + """batch_post. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchEventCommand + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchEventCommandResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchEventCommandResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchEventCommandResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchEventCommand') + else: + _json = None + + request = build_batch_post_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=self.batch_post.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchEventCommandResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_post.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batch/events"} # type: ignore + + + @distributed_trace_async + async def post_by_experiment_name( # pylint: disable=inconsistent-return-statements + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional["_models.BaseEvent"] = None, + **kwargs: Any + ) -> None: + """post_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BaseEvent') + else: + _json = None + + request = build_post_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.post_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in []: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + post_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/events"} # type: ignore + + + @distributed_trace_async + async def post_by_experiment_id( # pylint: disable=inconsistent-return-statements + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional["_models.BaseEvent"] = None, + **kwargs: Any + ) -> None: + """post_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BaseEvent') + else: + _json = None + + request = build_post_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.post_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in []: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + post_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/events"} # type: ignore + + + @distributed_trace_async + async def post( # pylint: disable=inconsistent-return-statements + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.BaseEvent"] = None, + **kwargs: Any + ) -> None: + """post. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BaseEvent + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BaseEvent') + else: + _json = None + + request = build_post_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.post.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in []: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + post.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/events"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_experiments_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_experiments_operations.py new file mode 100644 index 00000000..e1831c4c --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_experiments_operations.py @@ -0,0 +1,621 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar, Union + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator import distributed_trace +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._experiments_operations import build_create_request, build_delete_request_initial, build_delete_tags_request, build_get_by_id_request, build_get_by_query_request, build_get_request, build_update_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class ExperimentsOperations: + """ExperimentsOperations 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 get( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + **kwargs: Any + ) -> "_models.Experiment": + """Get details of an Experiment. + + Get details of an Experiment with specific Experiment name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: The experiment name. + :type experiment_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Experiment, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Experiment + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Experiment"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + template_url=self.get.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Experiment', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}"} # type: ignore + + + @distributed_trace_async + async def create( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + **kwargs: Any + ) -> "_models.Experiment": + """Create an Experiment. + + Create a new Experiment. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: The experiment name. + :type experiment_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Experiment, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Experiment + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Experiment"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_create_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + template_url=self.create.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Experiment', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + create.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}"} # type: ignore + + + @distributed_trace_async + async def get_by_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + **kwargs: Any + ) -> "_models.Experiment": + """Get details of an Experiment. + + Get details of an Experiment with specific Experiment Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: The identifier of the experiment. + :type experiment_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Experiment, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Experiment + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Experiment"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_by_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + template_url=self.get_by_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Experiment', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"} # type: ignore + + + @distributed_trace_async + async def update( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.ModifyExperiment"] = None, + **kwargs: Any + ) -> "_models.Experiment": + """Update details of an Experiment. + + Update details of an Experiment with specific Experiment Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: The identifier of the experiment. + :type experiment_id: str + :param body: Experiment details which needs to be updated. + :type body: ~azure.mgmt.machinelearningservices.models.ModifyExperiment + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Experiment, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Experiment + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Experiment"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'ModifyExperiment') + else: + _json = None + + request = build_update_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.update.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Experiment', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + update.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"} # type: ignore + + + async def _delete_initial( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + **kwargs: Any + ) -> Any: + cls = kwargs.pop('cls', None) # type: ClsType[Any] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_delete_request_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + template_url=self._delete_initial.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('object', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + _delete_initial.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"} # type: ignore + + + @distributed_trace_async + async def begin_delete( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + **kwargs: Any + ) -> AsyncLROPoller[Any]: + """Delete an Experiment. + + Delete an existing Empty Experiment. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: The identifier of the experiment. + :type experiment_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for + this operation to not poll, or pass in your own initialized polling object for a personal + polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no + Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either any or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[any] + :raises: ~azure.core.exceptions.HttpResponseError + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[Any] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + cls=lambda x,y,z: x, + **kwargs + ) + kwargs.pop('error_map', None) + + def get_long_running_output(pipeline_response): + response = pipeline_response.http_response + deserialized = self._deserialize('object', pipeline_response) + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + + if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + + begin_delete.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}"} # type: ignore + + @distributed_trace + def get_by_query( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + url_safe_experiment_names_only: Optional[bool] = True, + body: Optional["_models.ExperimentQueryParams"] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedExperimentList"]: + """Get all Experiments in a specific workspace. + + Get all experiments in a specific workspace with the specified query filters. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param url_safe_experiment_names_only: + :type url_safe_experiment_names_only: bool + :param body: Query parameters for data sorting and filtering. + :type body: ~azure.mgmt.machinelearningservices.models.ExperimentQueryParams + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedExperimentList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedExperimentList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedExperimentList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + if body is not None: + _json = self._serialize.body(body, 'ExperimentQueryParams') + else: + _json = None + + request = build_get_by_query_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + url_safe_experiment_names_only=url_safe_experiment_names_only, + template_url=self.get_by_query.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + if body is not None: + _json = self._serialize.body(body, 'ExperimentQueryParams') + else: + _json = None + + request = build_get_by_query_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + url_safe_experiment_names_only=url_safe_experiment_names_only, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedExperimentList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_by_query.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments:query"} # type: ignore + + @distributed_trace_async + async def delete_tags( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.DeleteTagsCommand"] = None, + **kwargs: Any + ) -> "_models.DeleteExperimentTagsResult": + """Delete list of Tags in an Experiment. + + Delete list of Tags from a specific Experiment Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: The identifier of the experiment. + :type experiment_id: str + :param body: The requested tags list to be deleted. + :type body: ~azure.mgmt.machinelearningservices.models.DeleteTagsCommand + :keyword callable cls: A custom type or function that will be passed the direct response + :return: DeleteExperimentTagsResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.DeleteExperimentTagsResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.DeleteExperimentTagsResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteTagsCommand') + else: + _json = None + + request = build_delete_tags_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.delete_tags.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('DeleteExperimentTagsResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_tags.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/tags:delete"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_metric_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_metric_operations.py new file mode 100644 index 00000000..0fed06c3 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_metric_operations.py @@ -0,0 +1,875 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar, Union + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.core.rest import HttpRequest +from azure.core.tracing.decorator import distributed_trace +from azure.core.tracing.decorator_async import distributed_trace_async +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._metric_operations import build_delete_metrics_by_data_container_id_request_initial, build_delete_metrics_by_run_id_request_initial, build_get_full_fidelity_metric_request, build_get_metric_details_by_experiment_id_request, build_get_metric_details_by_experiment_name_request, build_get_sampled_metric_request, build_list_generic_resource_metrics_request, build_list_metric_request, build_post_run_metrics_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class MetricOperations: + """MetricOperations 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 get_full_fidelity_metric( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.RetrieveFullFidelityMetricRequest"] = None, + **kwargs: Any + ) -> "_models.MetricV2": + """API to retrieve the full-fidelity sequence associated with a particular run and metricName. + + API to retrieve the full-fidelity sequence associated with a particular run and metricName. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.RetrieveFullFidelityMetricRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: MetricV2, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.MetricV2 + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.MetricV2"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'RetrieveFullFidelityMetricRequest') + else: + _json = None + + request = build_get_full_fidelity_metric_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.get_full_fidelity_metric.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('MetricV2', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_full_fidelity_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/full"} # type: ignore + + + @distributed_trace + def list_metric( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.ListMetrics"] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedMetricDefinitionList"]: + """API to list metric for a particular datacontainer and metricName. + + API to list metric for a particular datacontainer and metricName. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.ListMetrics + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedMetricDefinitionList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedMetricDefinitionList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedMetricDefinitionList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + if body is not None: + _json = self._serialize.body(body, 'ListMetrics') + else: + _json = None + + request = build_list_metric_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.list_metric.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + if body is not None: + _json = self._serialize.body(body, 'ListMetrics') + else: + _json = None + + request = build_list_metric_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedMetricDefinitionList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/list"} # type: ignore + + @distributed_trace + def list_generic_resource_metrics( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.ListGenericResourceMetrics"] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedMetricDefinitionList"]: + """API to list workspace/subworkspace resource metrics for a particular ResourceId. + + API to list workspace/subworkspace resource metrics for a particular ResourceId. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.ListGenericResourceMetrics + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedMetricDefinitionList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedMetricDefinitionList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedMetricDefinitionList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + if body is not None: + _json = self._serialize.body(body, 'ListGenericResourceMetrics') + else: + _json = None + + request = build_list_generic_resource_metrics_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=self.list_generic_resource_metrics.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + if body is not None: + _json = self._serialize.body(body, 'ListGenericResourceMetrics') + else: + _json = None + + request = build_list_generic_resource_metrics_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedMetricDefinitionList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_generic_resource_metrics.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/azuremonitor/list"} # type: ignore + + @distributed_trace_async + async def get_sampled_metric( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.GetSampledMetricRequest"] = None, + **kwargs: Any + ) -> "_models.MetricSample": + """Stub for future action + API to retrieve samples for one or many runs to compare a given metricName + Throw if schemas don't match across metrics. + + Stub for future action + API to retrieve samples for one or many runs to compare a given metricName + Throw if schemas don't match across metrics. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.GetSampledMetricRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: MetricSample, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.MetricSample + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.MetricSample"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'GetSampledMetricRequest') + else: + _json = None + + request = build_get_sampled_metric_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.get_sampled_metric.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('MetricSample', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_sampled_metric.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/sample"} # type: ignore + + + @distributed_trace_async + async def post_run_metrics( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.BatchIMetricV2"] = None, + **kwargs: Any + ) -> "_models.PostRunMetricsResult": + """Post Metrics to a Run. + + Post Metrics to a specific Run Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchIMetricV2 + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PostRunMetricsResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.PostRunMetricsResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PostRunMetricsResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchIMetricV2') + else: + _json = None + + request = build_post_run_metrics_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.post_run_metrics.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200, 207]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if response.status_code == 200: + deserialized = self._deserialize('PostRunMetricsResult', pipeline_response) + + if response.status_code == 207: + deserialized = self._deserialize('PostRunMetricsResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + post_run_metrics.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/batch"} # type: ignore + + + async def _delete_metrics_by_data_container_id_initial( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + data_container_id: str, + **kwargs: Any + ) -> Any: + cls = kwargs.pop('cls', None) # type: ClsType[Any] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_delete_metrics_by_data_container_id_request_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + data_container_id=data_container_id, + template_url=self._delete_metrics_by_data_container_id_initial.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('object', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + _delete_metrics_by_data_container_id_initial.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentId}/containers/{dataContainerId}/deleteMetrics"} # type: ignore + + + @distributed_trace_async + async def begin_delete_metrics_by_data_container_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + data_container_id: str, + **kwargs: Any + ) -> AsyncLROPoller[Any]: + """API to delete metrics by data container id. + + API to delete metrics by data container id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: + :type experiment_id: str + :param data_container_id: + :type data_container_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for + this operation to not poll, or pass in your own initialized polling object for a personal + polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no + Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either any or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[any] + :raises: ~azure.core.exceptions.HttpResponseError + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[Any] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_metrics_by_data_container_id_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + data_container_id=data_container_id, + cls=lambda x,y,z: x, + **kwargs + ) + kwargs.pop('error_map', None) + + def get_long_running_output(pipeline_response): + response = pipeline_response.http_response + deserialized = self._deserialize('object', pipeline_response) + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + + if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + + begin_delete_metrics_by_data_container_id.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentId}/containers/{dataContainerId}/deleteMetrics"} # type: ignore + + async def _delete_metrics_by_run_id_initial( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + **kwargs: Any + ) -> Any: + cls = kwargs.pop('cls', None) # type: ClsType[Any] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_delete_metrics_by_run_id_request_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + template_url=self._delete_metrics_by_run_id_initial.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('object', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + _delete_metrics_by_run_id_initial.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/deleteMetrics"} # type: ignore + + + @distributed_trace_async + async def begin_delete_metrics_by_run_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + **kwargs: Any + ) -> AsyncLROPoller[Any]: + """API to delete metrics by run id. + + API to delete metrics by run id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :keyword str continuation_token: A continuation token to restart a poller from a saved state. + :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for + this operation to not poll, or pass in your own initialized polling object for a personal + polling strategy. + :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no + Retry-After header is present. + :return: An instance of AsyncLROPoller that returns either any or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[any] + :raises: ~azure.core.exceptions.HttpResponseError + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[Any] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_metrics_by_run_id_initial( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + cls=lambda x,y,z: x, + **kwargs + ) + kwargs.pop('error_map', None) + + def get_long_running_output(pipeline_response): + response = pipeline_response.http_response + deserialized = self._deserialize('object', pipeline_response) + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + + if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs) + elif polling is False: polling_method = AsyncNoPolling() + else: polling_method = polling + if cont_token: + return AsyncLROPoller.from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output + ) + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + + begin_delete_metrics_by_run_id.metadata = {'url': "/metric/v2.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/deleteMetrics"} # type: ignore + + @distributed_trace_async + async def get_metric_details_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + metric_id: str, + experiment_name: str, + **kwargs: Any + ) -> "_models.RunMetric": + """Get Metric details. + + Get Metric details for a specific Metric Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param metric_id: The identifier for a Metric. + :type metric_id: str + :param experiment_name: + :type experiment_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunMetric, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunMetric + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunMetric"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_metric_details_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + metric_id=metric_id, + experiment_name=experiment_name, + template_url=self.get_metric_details_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunMetric', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_metric_details_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/metrics/{metricId}"} # type: ignore + + + @distributed_trace_async + async def get_metric_details_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + metric_id: str, + experiment_id: str, + **kwargs: Any + ) -> "_models.RunMetric": + """Get Metric details. + + Get Metric details for a specific Metric Id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param metric_id: The identifier for a Metric. + :type metric_id: str + :param experiment_id: + :type experiment_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunMetric, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunMetric + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunMetric"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_metric_details_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + metric_id=metric_id, + experiment_id=experiment_id, + template_url=self.get_metric_details_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunMetric', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_metric_details_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/metrics/{metricId}"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_artifacts_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_artifacts_operations.py new file mode 100644 index 00000000..3710e381 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_artifacts_operations.py @@ -0,0 +1,1236 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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 import distributed_trace +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._run_artifacts_operations import build_batch_create_empty_artifacts_by_experiment_id_request, build_batch_create_empty_artifacts_by_experiment_name_request, build_get_by_id_by_experiment_id_request, build_get_by_id_by_experiment_name_request, build_get_content_information_by_experiment_id_request, build_get_content_information_by_experiment_name_request, build_get_sas_uri_by_experiment_id_request, build_get_sas_uri_by_experiment_name_request, build_list_in_container_by_experiment_id_request, build_list_in_container_by_experiment_name_request, build_list_in_path_by_experiment_id_request, build_list_in_path_by_experiment_name_request, build_list_sas_by_prefix_by_experiment_id_request, build_list_sas_by_prefix_by_experiment_name_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class RunArtifactsOperations: + """RunArtifactsOperations 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 + def list_in_container_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactList"]: + """list_in_container_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_in_container_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_in_container_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_in_container_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_in_container_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts"} # type: ignore + + @distributed_trace + def list_in_container_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactList"]: + """list_in_container_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_in_container_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_in_container_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_in_container_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_in_container_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts"} # type: ignore + + @distributed_trace + def list_in_path_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + path: Optional[str] = None, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactList"]: + """list_in_path_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param path: + :type path: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_in_path_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_in_path_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_in_path_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_in_path_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/path"} # type: ignore + + @distributed_trace + def list_in_path_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + path: Optional[str] = None, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactList"]: + """list_in_path_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param path: + :type path: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactList or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_in_path_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_in_path_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_in_path_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_in_path_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/path"} # type: ignore + + @distributed_trace_async + async def get_by_id_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + path: Optional[str] = None, + **kwargs: Any + ) -> "_models.Artifact": + """get_by_id_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Artifact, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Artifact + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Artifact"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_by_id_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + template_url=self.get_by_id_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Artifact', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_id_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/metadata"} # type: ignore + + + @distributed_trace_async + async def get_by_id_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + path: Optional[str] = None, + **kwargs: Any + ) -> "_models.Artifact": + """get_by_id_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Artifact, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Artifact + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Artifact"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_by_id_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + template_url=self.get_by_id_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Artifact', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_id_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/metadata"} # type: ignore + + + @distributed_trace_async + async def get_content_information_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + path: Optional[str] = None, + **kwargs: Any + ) -> "_models.ArtifactContentInformation": + """get_content_information_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ArtifactContentInformation, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.ArtifactContentInformation + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.ArtifactContentInformation"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_content_information_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + template_url=self.get_content_information_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ArtifactContentInformation', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_content_information_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/contentinfo"} # type: ignore + + + @distributed_trace_async + async def get_content_information_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + path: Optional[str] = None, + **kwargs: Any + ) -> "_models.ArtifactContentInformation": + """get_content_information_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ArtifactContentInformation, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.ArtifactContentInformation + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.ArtifactContentInformation"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_content_information_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + template_url=self.get_content_information_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ArtifactContentInformation', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_content_information_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/contentinfo"} # type: ignore + + + @distributed_trace_async + async def get_sas_uri_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + path: Optional[str] = None, + **kwargs: Any + ) -> str: + """get_sas_uri_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: str, or the result of cls(response) + :rtype: str + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[str] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_sas_uri_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + template_url=self.get_sas_uri_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('str', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_sas_uri_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/artifacturi"} # type: ignore + + + @distributed_trace_async + async def get_sas_uri_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + path: Optional[str] = None, + **kwargs: Any + ) -> str: + """get_sas_uri_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param path: + :type path: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: str, or the result of cls(response) + :rtype: str + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[str] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_sas_uri_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + template_url=self.get_sas_uri_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('str', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_sas_uri_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/artifacturi"} # type: ignore + + + @distributed_trace + def list_sas_by_prefix_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + path: Optional[str] = None, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactContentInformationList"]: + """list_sas_by_prefix_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param path: + :type path: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactContentInformationList or the + result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactContentInformationList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactContentInformationList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_sas_by_prefix_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_sas_by_prefix_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_sas_by_prefix_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactContentInformationList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_sas_by_prefix_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/prefix/contentinfo"} # type: ignore + + @distributed_trace + def list_sas_by_prefix_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + path: Optional[str] = None, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedArtifactContentInformationList"]: + """list_sas_by_prefix_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param path: + :type path: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedArtifactContentInformationList or the + result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedArtifactContentInformationList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedArtifactContentInformationList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_sas_by_prefix_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list_sas_by_prefix_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_sas_by_prefix_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + path=path, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedArtifactContentInformationList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_sas_by_prefix_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/prefix/contentinfo"} # type: ignore + + @distributed_trace_async + async def batch_create_empty_artifacts_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional["_models.ArtifactPathList"] = None, + **kwargs: Any + ) -> "_models.BatchArtifactContentInformationResult": + """batch_create_empty_artifacts_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.ArtifactPathList + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchArtifactContentInformationResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchArtifactContentInformationResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchArtifactContentInformationResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'ArtifactPathList') + else: + _json = None + + request = build_batch_create_empty_artifacts_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.batch_create_empty_artifacts_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchArtifactContentInformationResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_create_empty_artifacts_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/artifacts/batch/metadata"} # type: ignore + + + @distributed_trace_async + async def batch_create_empty_artifacts_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional["_models.ArtifactPathList"] = None, + **kwargs: Any + ) -> "_models.BatchArtifactContentInformationResult": + """batch_create_empty_artifacts_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.ArtifactPathList + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchArtifactContentInformationResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchArtifactContentInformationResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchArtifactContentInformationResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'ArtifactPathList') + else: + _json = None + + request = build_batch_create_empty_artifacts_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.batch_create_empty_artifacts_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchArtifactContentInformationResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_create_empty_artifacts_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/artifacts/batch/metadata"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_operations.py new file mode 100644 index 00000000..64cbc7dd --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_run_operations.py @@ -0,0 +1,168 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, List, Optional, TypeVar, Union + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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 import distributed_trace +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models as _models +from ..._vendor import _convert_request +from ...operations._run_operations import build_list_by_compute_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class RunOperations: + """RunOperations 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 + def list_by_compute( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + compute_name: str, + filter: Optional[str] = None, + continuationtoken: Optional[str] = None, + orderby: Optional[List[str]] = None, + sortorder: Optional[Union[str, "_models.SortOrderDirection"]] = None, + top: Optional[int] = None, + count: Optional[bool] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """list_by_compute. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param compute_name: + :type compute_name: str + :param filter: Allows for filtering the collection of resources. + The expression specified is evaluated for each resource in the collection, and only items + where the expression evaluates to true are included in the response. + :type filter: str + :param continuationtoken: The continuation token to use for getting the next set of resources. + :type continuationtoken: str + :param orderby: The list of resource properties to use for sorting the requested resources. + :type orderby: list[str] + :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after + each property name in the OrderBy parameter. + :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection + :param top: The maximum number of items in the resource collection to be included in the + result. + If not specified, all items are returned. + :type top: int + :param count: Whether to include a count of the matching resources along with the resources + returned in the response. + :type count: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_by_compute_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=self.list_by_compute.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_by_compute_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list_by_compute.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/runs"} # type: ignore diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_runs_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_runs_operations.py new file mode 100644 index 00000000..b42721dc --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_runs_operations.py @@ -0,0 +1,2674 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, List, Optional, TypeVar, Union + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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 import distributed_trace +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._runs_operations import build_add_or_modify_by_experiment_id_request, build_add_or_modify_by_experiment_name_request, build_add_or_modify_experiment_request, build_add_or_modify_run_service_instances_request, build_add_request, build_batch_add_or_modify_by_experiment_id_request, build_batch_add_or_modify_by_experiment_name_request, build_batch_get_run_data_request, build_cancel_run_with_uri_by_experiment_id_request, build_cancel_run_with_uri_by_experiment_name_request, build_delete_run_services_by_experiment_id_request, build_delete_run_services_by_experiment_name_request, build_delete_run_services_request, build_delete_tags_by_experiment_id_request, build_delete_tags_by_experiment_name_request, build_delete_tags_request, build_get_by_experiment_id_request, build_get_by_experiment_name_request, build_get_by_ids_by_experiment_id_request, build_get_by_ids_by_experiment_name_request, build_get_by_query_by_experiment_id_request, build_get_by_query_by_experiment_name_request, build_get_child_by_experiment_id_request, build_get_child_by_experiment_name_request, build_get_child_request, build_get_details_by_experiment_id_request, build_get_details_by_experiment_name_request, build_get_details_request, build_get_request, build_get_run_data_request, build_get_run_service_instances_request, build_modify_or_delete_tags_by_experiment_id_request, build_modify_or_delete_tags_by_experiment_name_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class RunsOperations: # pylint: disable=too-many-public-methods + """RunsOperations 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 + def get_child_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + filter: Optional[str] = None, + continuationtoken: Optional[str] = None, + orderby: Optional[List[str]] = None, + sortorder: Optional[Union[str, "_models.SortOrderDirection"]] = None, + top: Optional[int] = None, + count: Optional[bool] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """get_child_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param filter: Allows for filtering the collection of resources. + The expression specified is evaluated for each resource in the collection, and only items + where the expression evaluates to true are included in the response. + :type filter: str + :param continuationtoken: The continuation token to use for getting the next set of resources. + :type continuationtoken: str + :param orderby: The list of resource properties to use for sorting the requested resources. + :type orderby: list[str] + :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after + each property name in the OrderBy parameter. + :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection + :param top: The maximum number of items in the resource collection to be included in the + result. + If not specified, all items are returned. + :type top: int + :param count: Whether to include a count of the matching resources along with the resources + returned in the response. + :type count: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_get_child_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=self.get_child_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_get_child_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_child_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/children"} # type: ignore + + @distributed_trace + def get_child_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + filter: Optional[str] = None, + continuationtoken: Optional[str] = None, + orderby: Optional[List[str]] = None, + sortorder: Optional[Union[str, "_models.SortOrderDirection"]] = None, + top: Optional[int] = None, + count: Optional[bool] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """get_child_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param filter: Allows for filtering the collection of resources. + The expression specified is evaluated for each resource in the collection, and only items + where the expression evaluates to true are included in the response. + :type filter: str + :param continuationtoken: The continuation token to use for getting the next set of resources. + :type continuationtoken: str + :param orderby: The list of resource properties to use for sorting the requested resources. + :type orderby: list[str] + :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after + each property name in the OrderBy parameter. + :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection + :param top: The maximum number of items in the resource collection to be included in the + result. + If not specified, all items are returned. + :type top: int + :param count: Whether to include a count of the matching resources along with the resources + returned in the response. + :type count: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_get_child_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=self.get_child_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_get_child_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_child_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/children"} # type: ignore + + @distributed_trace + def get_child( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + filter: Optional[str] = None, + continuationtoken: Optional[str] = None, + orderby: Optional[List[str]] = None, + sortorder: Optional[Union[str, "_models.SortOrderDirection"]] = None, + top: Optional[int] = None, + count: Optional[bool] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """get_child. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param filter: Allows for filtering the collection of resources. + The expression specified is evaluated for each resource in the collection, and only items + where the expression evaluates to true are included in the response. + :type filter: str + :param continuationtoken: The continuation token to use for getting the next set of resources. + :type continuationtoken: str + :param orderby: The list of resource properties to use for sorting the requested resources. + :type orderby: list[str] + :param sortorder: The sort order of the returned resources. Not used, specify asc or desc after + each property name in the OrderBy parameter. + :type sortorder: str or ~azure.mgmt.machinelearningservices.models.SortOrderDirection + :param top: The maximum number of items in the resource collection to be included in the + result. + If not specified, all items are returned. + :type top: int + :param count: Whether to include a count of the matching resources along with the resources + returned in the response. + :type count: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_get_child_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=self.get_child.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_get_child_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + filter=filter, + continuationtoken=continuationtoken, + orderby=orderby, + sortorder=sortorder, + top=top, + count=count, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_child.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/children"} # type: ignore + + @distributed_trace_async + async def get_details_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + **kwargs: Any + ) -> "_models.RunDetails": + """get_details_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunDetails, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunDetails"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_details_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + template_url=self.get_details_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunDetails', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_details_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/details"} # type: ignore + + + @distributed_trace_async + async def get_details_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + **kwargs: Any + ) -> "_models.RunDetails": + """get_details_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunDetails, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunDetails"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_details_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + template_url=self.get_details_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunDetails', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_details_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/details"} # type: ignore + + + @distributed_trace_async + async def get_details( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + **kwargs: Any + ) -> "_models.RunDetails": + """get_details. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunDetails, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunDetails + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunDetails"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_details_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + template_url=self.get_details.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunDetails', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_details.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/details"} # type: ignore + + + @distributed_trace_async + async def get_run_data( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.GetRunDataRequest"] = None, + **kwargs: Any + ) -> "_models.GetRunDataResult": + """get_run_data. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.GetRunDataRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: GetRunDataResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.GetRunDataResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.GetRunDataResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'GetRunDataRequest') + else: + _json = None + + request = build_get_run_data_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=self.get_run_data.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('GetRunDataResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_run_data.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/rundata"} # type: ignore + + + @distributed_trace_async + async def batch_get_run_data( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + body: Optional["_models.BatchRequest1"] = None, + **kwargs: Any + ) -> "_models.BatchResult1": + """batch_get_run_data. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchRequest1 + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchResult1, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchResult1 + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchResult1"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchRequest1') + else: + _json = None + + request = build_batch_get_run_data_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + content_type=content_type, + json=_json, + template_url=self.batch_get_run_data.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200, 207]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if response.status_code == 200: + deserialized = self._deserialize('BatchResult1', pipeline_response) + + if response.status_code == 207: + deserialized = self._deserialize('BatchResult1', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_get_run_data.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchrundata"} # type: ignore + + + @distributed_trace_async + async def batch_add_or_modify_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.BatchAddOrModifyRunRequest"] = None, + **kwargs: Any + ) -> "_models.BatchRunResult": + """batch_add_or_modify_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchAddOrModifyRunRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchRunResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchRunResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchAddOrModifyRunRequest') + else: + _json = None + + request = build_batch_add_or_modify_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.batch_add_or_modify_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchRunResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_add_or_modify_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/batch/runs"} # type: ignore + + + @distributed_trace_async + async def batch_add_or_modify_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + body: Optional["_models.BatchAddOrModifyRunRequest"] = None, + **kwargs: Any + ) -> "_models.BatchRunResult": + """batch_add_or_modify_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.BatchAddOrModifyRunRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchRunResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchRunResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'BatchAddOrModifyRunRequest') + else: + _json = None + + request = build_batch_add_or_modify_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.batch_add_or_modify_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchRunResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + batch_add_or_modify_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/batch/runs"} # type: ignore + + + @distributed_trace_async + async def add_or_modify_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional["_models.CreateRun"] = None, + **kwargs: Any + ) -> "_models.Run": + """add_or_modify_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.CreateRun + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'CreateRun') + else: + _json = None + + request = build_add_or_modify_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.add_or_modify_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + add_or_modify_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def get_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + **kwargs: Any + ) -> "_models.Run": + """get_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + template_url=self.get_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def add_or_modify_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional["_models.CreateRun"] = None, + **kwargs: Any + ) -> "_models.Run": + """add_or_modify_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.CreateRun + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'CreateRun') + else: + _json = None + + request = build_add_or_modify_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.add_or_modify_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + add_or_modify_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def get_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + **kwargs: Any + ) -> "_models.Run": + """get_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + template_url=self.get_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def add_or_modify_experiment( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.CreateRun"] = None, + **kwargs: Any + ) -> "_models.Run": + """add_or_modify_experiment. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.CreateRun + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'CreateRun') + else: + _json = None + + request = build_add_or_modify_experiment_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.add_or_modify_experiment.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + add_or_modify_experiment.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def add( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.CreateRun"] = None, + **kwargs: Any + ) -> "_models.Run": + """add. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.CreateRun + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'CreateRun') + else: + _json = None + + request = build_add_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.add.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + add.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def get( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + **kwargs: Any + ) -> "_models.Run": + """get. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + template_url=self.get.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}"} # type: ignore + + + @distributed_trace_async + async def delete_tags_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional[List[str]] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_tags_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: list[str] + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, '[str]') + else: + _json = None + + request = build_delete_tags_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.delete_tags_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_tags_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags"} # type: ignore + + + @distributed_trace_async + async def modify_or_delete_tags_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional["_models.DeleteOrModifyTags"] = None, + **kwargs: Any + ) -> "_models.Run": + """modify_or_delete_tags_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteOrModifyTags + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteOrModifyTags') + else: + _json = None + + request = build_modify_or_delete_tags_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.modify_or_delete_tags_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + modify_or_delete_tags_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/tags"} # type: ignore + + + @distributed_trace_async + async def delete_tags_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional[List[str]] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_tags_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: list[str] + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, '[str]') + else: + _json = None + + request = build_delete_tags_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.delete_tags_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_tags_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags"} # type: ignore + + + @distributed_trace_async + async def modify_or_delete_tags_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional["_models.DeleteOrModifyTags"] = None, + **kwargs: Any + ) -> "_models.Run": + """modify_or_delete_tags_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteOrModifyTags + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteOrModifyTags') + else: + _json = None + + request = build_modify_or_delete_tags_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.modify_or_delete_tags_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + modify_or_delete_tags_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/tags"} # type: ignore + + + @distributed_trace_async + async def delete_tags( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional[List[str]] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_tags. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: list[str] + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, '[str]') + else: + _json = None + + request = build_delete_tags_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.delete_tags.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_tags.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/tags"} # type: ignore + + + @distributed_trace_async + async def delete_run_services_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + body: Optional["_models.DeleteRunServices"] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_run_services_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteRunServices') + else: + _json = None + + request = build_delete_run_services_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.delete_run_services_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_run_services_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/services"} # type: ignore + + + @distributed_trace_async + async def delete_run_services_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + body: Optional["_models.DeleteRunServices"] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_run_services_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteRunServices') + else: + _json = None + + request = build_delete_run_services_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.delete_run_services_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_run_services_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/services"} # type: ignore + + + @distributed_trace_async + async def delete_run_services( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.DeleteRunServices"] = None, + **kwargs: Any + ) -> "_models.Run": + """delete_run_services. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.DeleteRunServices + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'DeleteRunServices') + else: + _json = None + + request = build_delete_run_services_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.delete_run_services.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + delete_run_services.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/services"} # type: ignore + + + @distributed_trace_async + async def add_or_modify_run_service_instances( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + node_id: int, + body: Optional["_models.AddOrModifyRunServiceInstancesRequest"] = None, + **kwargs: Any + ) -> "_models.RunServiceInstances": + """add_or_modify_run_service_instances. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param node_id: + :type node_id: int + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.AddOrModifyRunServiceInstancesRequest + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunServiceInstances, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunServiceInstances + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunServiceInstances"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'AddOrModifyRunServiceInstancesRequest') + else: + _json = None + + request = build_add_or_modify_run_service_instances_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + node_id=node_id, + content_type=content_type, + json=_json, + template_url=self.add_or_modify_run_service_instances.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunServiceInstances', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + add_or_modify_run_service_instances.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}"} # type: ignore + + + @distributed_trace_async + async def get_run_service_instances( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + node_id: int, + **kwargs: Any + ) -> "_models.RunServiceInstances": + """get_run_service_instances. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param node_id: + :type node_id: int + :keyword callable cls: A custom type or function that will be passed the direct response + :return: RunServiceInstances, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.RunServiceInstances + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.RunServiceInstances"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_get_run_service_instances_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + node_id=node_id, + template_url=self.get_run_service_instances.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('RunServiceInstances', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_run_service_instances.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/serviceinstances/{nodeId}"} # type: ignore + + + @distributed_trace + def get_by_query_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + body: Optional["_models.QueryParams"] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """get_by_query_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.QueryParams + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + if body is not None: + _json = self._serialize.body(body, 'QueryParams') + else: + _json = None + + request = build_get_by_query_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.get_by_query_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + if body is not None: + _json = self._serialize.body(body, 'QueryParams') + else: + _json = None + + request = build_get_by_query_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_by_query_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs:query"} # type: ignore + + @distributed_trace + def get_by_query_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.QueryParams"] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedRunList"]: + """get_by_query_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.QueryParams + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedRunList or the result of cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedRunList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedRunList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + if body is not None: + _json = self._serialize.body(body, 'QueryParams') + else: + _json = None + + request = build_get_by_query_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.get_by_query_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + if body is not None: + _json = self._serialize.body(body, 'QueryParams') + else: + _json = None + + request = build_get_by_query_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedRunList", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_by_query_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs:query"} # type: ignore + + @distributed_trace_async + async def get_by_ids_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_id: str, + body: Optional["_models.GetRunsByIds"] = None, + **kwargs: Any + ) -> "_models.BatchRunResult": + """get_by_ids_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_id: + :type experiment_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.GetRunsByIds + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchRunResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchRunResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'GetRunsByIds') + else: + _json = None + + request = build_get_by_ids_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_id=experiment_id, + content_type=content_type, + json=_json, + template_url=self.get_by_ids_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchRunResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_ids_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/runIds"} # type: ignore + + + @distributed_trace_async + async def get_by_ids_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + experiment_name: str, + body: Optional["_models.GetRunsByIds"] = None, + **kwargs: Any + ) -> "_models.BatchRunResult": + """get_by_ids_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param experiment_name: + :type experiment_name: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.GetRunsByIds + :keyword callable cls: A custom type or function that will be passed the direct response + :return: BatchRunResult, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.BatchRunResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.BatchRunResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'GetRunsByIds') + else: + _json = None + + request = build_get_by_ids_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + experiment_name=experiment_name, + content_type=content_type, + json=_json, + template_url=self.get_by_ids_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('BatchRunResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + get_by_ids_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/runIds"} # type: ignore + + + @distributed_trace_async + async def cancel_run_with_uri_by_experiment_id( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_id: str, + cancelation_reason: Optional[str] = None, + **kwargs: Any + ) -> "_models.Run": + """cancel_run_with_uri_by_experiment_id. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_id: + :type experiment_id: str + :param cancelation_reason: + :type cancelation_reason: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_cancel_run_with_uri_by_experiment_id_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_id=experiment_id, + cancelation_reason=cancelation_reason, + template_url=self.cancel_run_with_uri_by_experiment_id.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + cancel_run_with_uri_by_experiment_id.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experimentids/{experimentId}/runs/{runId}/cancel"} # type: ignore + + + @distributed_trace_async + async def cancel_run_with_uri_by_experiment_name( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + experiment_name: str, + cancelation_reason: Optional[str] = None, + **kwargs: Any + ) -> "_models.Run": + """cancel_run_with_uri_by_experiment_name. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param experiment_name: + :type experiment_name: str + :param cancelation_reason: + :type cancelation_reason: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Run, or the result of cls(response) + :rtype: ~azure.mgmt.machinelearningservices.models.Run + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.Run"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + + request = build_cancel_run_with_uri_by_experiment_name_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + experiment_name=experiment_name, + cancelation_reason=cancelation_reason, + template_url=self.cancel_run_with_uri_by_experiment_name.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Run', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + + cancel_run_with_uri_by_experiment_name.metadata = {'url': "/history/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/experiments/{experimentName}/runs/{runId}/cancel"} # type: ignore + diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_spans_operations.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_spans_operations.py new file mode 100644 index 00000000..92894166 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/_restclient/runhistory/aio/operations/_spans_operations.py @@ -0,0 +1,302 @@ +# pylint: disable=too-many-lines +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) AutoRest Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar + +from azure.core.async_paging import AsyncItemPaged, AsyncList +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 import distributed_trace +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._spans_operations import build_get_active_request, build_list_request, build_post_request +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class SpansOperations: + """SpansOperations 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 post( # pylint: disable=inconsistent-return-statements + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + body: Optional["_models.RunStatusSpans"] = None, + **kwargs: Any + ) -> None: + """post. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param body: + :type body: ~azure.mgmt.machinelearningservices.models.RunStatusSpans + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + + content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] + + if body is not None: + _json = self._serialize.body(body, 'RunStatusSpans') + else: + _json = None + + request = build_post_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + content_type=content_type, + json=_json, + template_url=self.post.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in []: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + post.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans"} # type: ignore + + + @distributed_trace + def list( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedSpanDefinition1List"]: + """list. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedSpanDefinition1List or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedSpanDefinition1List] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedSpanDefinition1List"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_list_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + continuation_token_parameter=continuation_token_parameter, + template_url=self.list.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_list_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedSpanDefinition1List", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + list.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans"} # type: ignore + + @distributed_trace + def get_active( + self, + subscription_id: str, + resource_group_name: str, + workspace_name: str, + run_id: str, + continuation_token_parameter: Optional[str] = None, + **kwargs: Any + ) -> AsyncIterable["_models.PaginatedSpanDefinition1List"]: + """get_active. + + :param subscription_id: The Azure Subscription ID. + :type subscription_id: str + :param resource_group_name: The Name of the resource group in which the workspace is located. + :type resource_group_name: str + :param workspace_name: The name of the workspace. + :type workspace_name: str + :param run_id: + :type run_id: str + :param continuation_token_parameter: + :type continuation_token_parameter: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedSpanDefinition1List or the result of + cls(response) + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.PaginatedSpanDefinition1List] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["_models.PaginatedSpanDefinition1List"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + def prepare_request(next_link=None): + if not next_link: + + request = build_get_active_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + continuation_token_parameter=continuation_token_parameter, + template_url=self.get_active.metadata['url'], + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + + else: + + request = build_get_active_request( + subscription_id=subscription_id, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + run_id=run_id, + continuation_token_parameter=continuation_token_parameter, + template_url=next_link, + ) + request = _convert_request(request) + request.url = self._client.format_url(request.url) + request.method = "GET" + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize("PaginatedSpanDefinition1List", pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access + request, + stream=False, + **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + + return AsyncItemPaged( + get_next, extract_data + ) + get_active.metadata = {'url': "/history/v1.0/private/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/runs/{runId}/spans/active"} # type: ignore |