"""Generated client library for hypercomputecluster version v1alpha."""
# NOTE: This file is autogenerated and should not be edited by hand.

from apitools.base.py import base_api
from googlecloudsdk.generated_clients.apis.hypercomputecluster.v1alpha import hypercomputecluster_v1alpha_messages as messages


class HypercomputeclusterV1alpha(base_api.BaseApiClient):
  """Generated client library for service hypercomputecluster version v1alpha."""

  MESSAGES_MODULE = messages
  BASE_URL = 'https://hypercomputecluster.googleapis.com/'
  MTLS_BASE_URL = 'https://hypercomputecluster.mtls.googleapis.com/'

  _PACKAGE = 'hypercomputecluster'
  _SCOPES = ['https://www.googleapis.com/auth/cloud-platform']
  _VERSION = 'v1alpha'
  _CLIENT_ID = 'CLIENT_ID'
  _CLIENT_SECRET = 'CLIENT_SECRET'
  _USER_AGENT = 'google-cloud-sdk'
  _CLIENT_CLASS_NAME = 'HypercomputeclusterV1alpha'
  _URL_VERSION = 'v1alpha'
  _API_KEY = None

  def __init__(self, url='', credentials=None,
               get_credentials=True, http=None, model=None,
               log_request=False, log_response=False,
               credentials_args=None, default_global_params=None,
               additional_http_headers=None, response_encoding=None):
    """Create a new hypercomputecluster handle."""
    url = url or self.BASE_URL
    super(HypercomputeclusterV1alpha, self).__init__(
        url, credentials=credentials,
        get_credentials=get_credentials, http=http, model=model,
        log_request=log_request, log_response=log_response,
        credentials_args=credentials_args,
        default_global_params=default_global_params,
        additional_http_headers=additional_http_headers,
        response_encoding=response_encoding)
    self.projects_locations_clusters_nodes = self.ProjectsLocationsClustersNodesService(self)
    self.projects_locations_clusters = self.ProjectsLocationsClustersService(self)
    self.projects_locations_machineLearningRuns_monitoredEvents = self.ProjectsLocationsMachineLearningRunsMonitoredEventsService(self)
    self.projects_locations_machineLearningRuns_profileSessions = self.ProjectsLocationsMachineLearningRunsProfileSessionsService(self)
    self.projects_locations_machineLearningRuns_profilerSessions = self.ProjectsLocationsMachineLearningRunsProfilerSessionsService(self)
    self.projects_locations_machineLearningRuns_profilerTargets = self.ProjectsLocationsMachineLearningRunsProfilerTargetsService(self)
    self.projects_locations_machineLearningRuns = self.ProjectsLocationsMachineLearningRunsService(self)
    self.projects_locations_operations = self.ProjectsLocationsOperationsService(self)
    self.projects_locations = self.ProjectsLocationsService(self)
    self.projects = self.ProjectsService(self)

  class ProjectsLocationsClustersNodesService(base_api.BaseApiService):
    """Service class for the projects_locations_clusters_nodes resource."""

    _NAME = 'projects_locations_clusters_nodes'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsClustersNodesService, self).__init__(client)
      self._upload_configs = {
          }

    def Get(self, request, global_params=None):
      r"""Gets details of a single Node.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersNodesGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Node) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters/{clustersId}/nodes/{nodesId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.clusters.nodes.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsClustersNodesGetRequest',
        response_type_name='Node',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists Nodes in a given cluster.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersNodesListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListNodesResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters/{clustersId}/nodes',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.clusters.nodes.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['filter', 'orderBy', 'pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/nodes',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsClustersNodesListRequest',
        response_type_name='ListNodesResponse',
        supports_download=False,
    )

  class ProjectsLocationsClustersService(base_api.BaseApiService):
    """Service class for the projects_locations_clusters resource."""

    _NAME = 'projects_locations_clusters'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsClustersService, self).__init__(client)
      self._upload_configs = {
          }

    def Create(self, request, global_params=None):
      r"""Creates a new Cluster in a given project and location.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersCreateRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Create')
      return self._RunMethod(
          config, request, global_params=global_params)

    Create.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.clusters.create',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['clusterId', 'requestId'],
        relative_path='v1alpha/{+parent}/clusters',
        request_field='cluster',
        request_type_name='HypercomputeclusterProjectsLocationsClustersCreateRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Deletes a single Cluster.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters/{clustersId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.clusters.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['requestId'],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsClustersDeleteRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Gets details of a single Cluster.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Cluster) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters/{clustersId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.clusters.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsClustersGetRequest',
        response_type_name='Cluster',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists Clusters in a given project and location.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListClustersResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.clusters.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['filter', 'orderBy', 'pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/clusters',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsClustersListRequest',
        response_type_name='ListClustersResponse',
        supports_download=False,
    )

    def Patch(self, request, global_params=None):
      r"""Updates the parameters of a single Cluster.

      Args:
        request: (HypercomputeclusterProjectsLocationsClustersPatchRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Patch')
      return self._RunMethod(
          config, request, global_params=global_params)

    Patch.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/clusters/{clustersId}',
        http_method='PATCH',
        method_id='hypercomputecluster.projects.locations.clusters.patch',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['requestId', 'updateMask'],
        relative_path='v1alpha/{+name}',
        request_field='cluster',
        request_type_name='HypercomputeclusterProjectsLocationsClustersPatchRequest',
        response_type_name='Operation',
        supports_download=False,
    )

  class ProjectsLocationsMachineLearningRunsMonitoredEventsService(base_api.BaseApiService):
    """Service class for the projects_locations_machineLearningRuns_monitoredEvents resource."""

    _NAME = 'projects_locations_machineLearningRuns_monitoredEvents'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsMachineLearningRunsMonitoredEventsService, self).__init__(client)
      self._upload_configs = {
          }

    def Create(self, request, global_params=None):
      r"""Creates a Monitored Event.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsCreateRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Create')
      return self._RunMethod(
          config, request, global_params=global_params)

    Create.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/monitoredEvents',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.monitoredEvents.create',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['monitoredEventId'],
        relative_path='v1alpha/{+parent}/monitoredEvents',
        request_field='monitoredEvent',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsCreateRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Deletes a Monitored Event.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/monitoredEvents/{monitoredEventsId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.monitoredEvents.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsDeleteRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Gets a specific Monitored Event.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (MonitoredEvent) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/monitoredEvents/{monitoredEventsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.monitoredEvents.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsGetRequest',
        response_type_name='MonitoredEvent',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists Monitored Events for a run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListMonitoredEventsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/monitoredEvents',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.monitoredEvents.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['filter', 'orderBy', 'pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/monitoredEvents',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsListRequest',
        response_type_name='ListMonitoredEventsResponse',
        supports_download=False,
    )

    def Patch(self, request, global_params=None):
      r"""Updates a Monitored Event.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsPatchRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Patch')
      return self._RunMethod(
          config, request, global_params=global_params)

    Patch.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/monitoredEvents/{monitoredEventsId}',
        http_method='PATCH',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.monitoredEvents.patch',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['updateMask'],
        relative_path='v1alpha/{+name}',
        request_field='monitoredEvent',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsMonitoredEventsPatchRequest',
        response_type_name='Operation',
        supports_download=False,
    )

  class ProjectsLocationsMachineLearningRunsProfileSessionsService(base_api.BaseApiService):
    """Service class for the projects_locations_machineLearningRuns_profileSessions resource."""

    _NAME = 'projects_locations_machineLearningRuns_profileSessions'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsMachineLearningRunsProfileSessionsService, self).__init__(client)
      self._upload_configs = {
          }

    def Get(self, request, global_params=None):
      r"""Deprecated: Use `GetProfilerSession` instead. Gets a Profile Session.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfileSessionsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ProfileSession) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profileSessions/{profileSessionsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profileSessions.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfileSessionsGetRequest',
        response_type_name='ProfileSession',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Deprecated: Use `ListProfilerSessions` instead. Lists Profile Sessions for a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfileSessionsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListProfileSessionsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profileSessions',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profileSessions.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/profileSessions',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfileSessionsListRequest',
        response_type_name='ListProfileSessionsResponse',
        supports_download=False,
    )

  class ProjectsLocationsMachineLearningRunsProfilerSessionsService(base_api.BaseApiService):
    """Service class for the projects_locations_machineLearningRuns_profilerSessions resource."""

    _NAME = 'projects_locations_machineLearningRuns_profilerSessions'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsMachineLearningRunsProfilerSessionsService, self).__init__(client)
      self._upload_configs = {
          }

    def Create(self, request, global_params=None):
      r"""Create a Profiler Session.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsCreateRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Create')
      return self._RunMethod(
          config, request, global_params=global_params)

    Create.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerSessions',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerSessions.create',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['profilerSessionId'],
        relative_path='v1alpha/{+parent}/profilerSessions',
        request_field='profilerSession',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsCreateRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Delete a Profiler Session.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Empty) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerSessions/{profilerSessionsId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerSessions.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsDeleteRequest',
        response_type_name='Empty',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Get Profiler Session.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ProfilerSession) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerSessions/{profilerSessionsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerSessions.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsGetRequest',
        response_type_name='ProfilerSession',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists Profiler Sessions for a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListProfilerSessionsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerSessions',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerSessions.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/profilerSessions',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerSessionsListRequest',
        response_type_name='ListProfilerSessionsResponse',
        supports_download=False,
    )

  class ProjectsLocationsMachineLearningRunsProfilerTargetsService(base_api.BaseApiService):
    """Service class for the projects_locations_machineLearningRuns_profilerTargets resource."""

    _NAME = 'projects_locations_machineLearningRuns_profilerTargets'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsMachineLearningRunsProfilerTargetsService, self).__init__(client)
      self._upload_configs = {
          }

    def Create(self, request, global_params=None):
      r"""Creates a Profiler Target.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsCreateRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Create')
      return self._RunMethod(
          config, request, global_params=global_params)

    Create.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerTargets',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerTargets.create',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['profilerTargetId'],
        relative_path='v1alpha/{+parent}/profilerTargets',
        request_field='profilerTarget',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsCreateRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Delete a Profiler Target.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Empty) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerTargets/{profilerTargetsId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerTargets.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsDeleteRequest',
        response_type_name='Empty',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Gets a Profiler Target.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ProfilerTarget) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerTargets/{profilerTargetsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerTargets.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsGetRequest',
        response_type_name='ProfilerTarget',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""List Profiler Targets for a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListProfilerTargetsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}/profilerTargets',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.profilerTargets.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/profilerTargets',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsProfilerTargetsListRequest',
        response_type_name='ListProfilerTargetsResponse',
        supports_download=False,
    )

  class ProjectsLocationsMachineLearningRunsService(base_api.BaseApiService):
    """Service class for the projects_locations_machineLearningRuns resource."""

    _NAME = 'projects_locations_machineLearningRuns'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsMachineLearningRunsService, self).__init__(client)
      self._upload_configs = {
          }

    def Create(self, request, global_params=None):
      r"""Creates a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsCreateRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Create')
      return self._RunMethod(
          config, request, global_params=global_params)

    Create.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.create',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['machineLearningRunId'],
        relative_path='v1alpha/{+parent}/machineLearningRuns',
        request_field='machineLearningRun',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsCreateRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Deletes a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['force'],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsDeleteRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Gets a Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (MachineLearningRun) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsGetRequest',
        response_type_name='MachineLearningRun',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists Machine Learning Runs.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListMachineLearningRunsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.list',
        ordered_params=['parent'],
        path_params=['parent'],
        query_params=['filter', 'orderBy', 'pageSize', 'pageToken'],
        relative_path='v1alpha/{+parent}/machineLearningRuns',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsListRequest',
        response_type_name='ListMachineLearningRunsResponse',
        supports_download=False,
    )

    def Patch(self, request, global_params=None):
      r"""Updates an Machine Learning Run.

      Args:
        request: (HypercomputeclusterProjectsLocationsMachineLearningRunsPatchRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Patch')
      return self._RunMethod(
          config, request, global_params=global_params)

    Patch.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/machineLearningRuns/{machineLearningRunsId}',
        http_method='PATCH',
        method_id='hypercomputecluster.projects.locations.machineLearningRuns.patch',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['updateMask'],
        relative_path='v1alpha/{+name}',
        request_field='machineLearningRun',
        request_type_name='HypercomputeclusterProjectsLocationsMachineLearningRunsPatchRequest',
        response_type_name='Operation',
        supports_download=False,
    )

  class ProjectsLocationsOperationsService(base_api.BaseApiService):
    """Service class for the projects_locations_operations resource."""

    _NAME = 'projects_locations_operations'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsOperationsService, self).__init__(client)
      self._upload_configs = {
          }

    def Cancel(self, request, global_params=None):
      r"""Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.

      Args:
        request: (HypercomputeclusterProjectsLocationsOperationsCancelRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Empty) The response message.
      """
      config = self.GetMethodConfig('Cancel')
      return self._RunMethod(
          config, request, global_params=global_params)

    Cancel.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:cancel',
        http_method='POST',
        method_id='hypercomputecluster.projects.locations.operations.cancel',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}:cancel',
        request_field='cancelOperationRequest',
        request_type_name='HypercomputeclusterProjectsLocationsOperationsCancelRequest',
        response_type_name='Empty',
        supports_download=False,
    )

    def Delete(self, request, global_params=None):
      r"""Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.

      Args:
        request: (HypercomputeclusterProjectsLocationsOperationsDeleteRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Empty) The response message.
      """
      config = self.GetMethodConfig('Delete')
      return self._RunMethod(
          config, request, global_params=global_params)

    Delete.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}',
        http_method='DELETE',
        method_id='hypercomputecluster.projects.locations.operations.delete',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsOperationsDeleteRequest',
        response_type_name='Empty',
        supports_download=False,
    )

    def Get(self, request, global_params=None):
      r"""Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.

      Args:
        request: (HypercomputeclusterProjectsLocationsOperationsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Operation) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.operations.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsOperationsGetRequest',
        response_type_name='Operation',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.

      Args:
        request: (HypercomputeclusterProjectsLocationsOperationsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListOperationsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}/operations',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.operations.list',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['filter', 'pageSize', 'pageToken', 'returnPartialSuccess'],
        relative_path='v1alpha/{+name}/operations',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsOperationsListRequest',
        response_type_name='ListOperationsResponse',
        supports_download=False,
    )

  class ProjectsLocationsService(base_api.BaseApiService):
    """Service class for the projects_locations resource."""

    _NAME = 'projects_locations'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsLocationsService, self).__init__(client)
      self._upload_configs = {
          }

    def Get(self, request, global_params=None):
      r"""Gets information about a location.

      Args:
        request: (HypercomputeclusterProjectsLocationsGetRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (Location) The response message.
      """
      config = self.GetMethodConfig('Get')
      return self._RunMethod(
          config, request, global_params=global_params)

    Get.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations/{locationsId}',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.get',
        ordered_params=['name'],
        path_params=['name'],
        query_params=[],
        relative_path='v1alpha/{+name}',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsGetRequest',
        response_type_name='Location',
        supports_download=False,
    )

    def List(self, request, global_params=None):
      r"""Lists information about the supported locations for this service. This method lists locations based on the resource scope provided in the ListLocationsRequest.name field: * **Global locations**: If `name` is empty, the method lists the public locations available to all projects. * **Project-specific locations**: If `name` follows the format `projects/{project}`, the method lists locations visible to that specific project. This includes public, private, or other project-specific locations enabled for the project. For gRPC and client library implementations, the resource name is passed as the `name` field. For direct service calls, the resource name is incorporated into the request path based on the specific service implementation and version.

      Args:
        request: (HypercomputeclusterProjectsLocationsListRequest) input message
        global_params: (StandardQueryParameters, default: None) global arguments
      Returns:
        (ListLocationsResponse) The response message.
      """
      config = self.GetMethodConfig('List')
      return self._RunMethod(
          config, request, global_params=global_params)

    List.method_config = lambda: base_api.ApiMethodInfo(
        flat_path='v1alpha/projects/{projectsId}/locations',
        http_method='GET',
        method_id='hypercomputecluster.projects.locations.list',
        ordered_params=['name'],
        path_params=['name'],
        query_params=['extraLocationTypes', 'filter', 'pageSize', 'pageToken'],
        relative_path='v1alpha/{+name}/locations',
        request_field='',
        request_type_name='HypercomputeclusterProjectsLocationsListRequest',
        response_type_name='ListLocationsResponse',
        supports_download=False,
    )

  class ProjectsService(base_api.BaseApiService):
    """Service class for the projects resource."""

    _NAME = 'projects'

    def __init__(self, client):
      super(HypercomputeclusterV1alpha.ProjectsService, self).__init__(client)
      self._upload_configs = {
          }
