viam.proto.app.mltraining ========================= .. py:module:: viam.proto.app.mltraining .. autoapi-nested-parse:: @generated by Viam. Do not edit manually! Classes ------- .. autoapisummary:: viam.proto.app.mltraining.MLTrainingServiceBase viam.proto.app.mltraining.MLTrainingServiceStub viam.proto.app.mltraining.UnimplementedMLTrainingServiceBase viam.proto.app.mltraining.CancelTrainingJobRequest viam.proto.app.mltraining.CancelTrainingJobResponse viam.proto.app.mltraining.DeleteCompletedTrainingJobRequest viam.proto.app.mltraining.DeleteCompletedTrainingJobResponse viam.proto.app.mltraining.GetTrainingJobLogsRequest viam.proto.app.mltraining.GetTrainingJobLogsResponse viam.proto.app.mltraining.GetTrainingJobRequest viam.proto.app.mltraining.GetTrainingJobResponse viam.proto.app.mltraining.ListTrainingJobsRequest viam.proto.app.mltraining.ListTrainingJobsResponse viam.proto.app.mltraining.ModelFramework viam.proto.app.mltraining.ModelType viam.proto.app.mltraining.SubmitCustomTrainingJobRequest viam.proto.app.mltraining.SubmitCustomTrainingJobResponse viam.proto.app.mltraining.SubmitTrainingJobRequest viam.proto.app.mltraining.SubmitTrainingJobResponse viam.proto.app.mltraining.TrainingJobLogEntry viam.proto.app.mltraining.TrainingJobMetadata viam.proto.app.mltraining.TrainingStatus Package Contents ---------------- .. py:class:: MLTrainingServiceBase Bases: :py:obj:`abc.ABC` Helper class that provides a standard way to create an ABC using inheritance. .. py:method:: SubmitTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitTrainingJobResponse]) -> None :abstractmethod: :async: .. py:method:: SubmitCustomTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobResponse]) -> None :abstractmethod: :async: .. py:method:: GetTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobResponse]) -> None :abstractmethod: :async: .. py:method:: ListTrainingJobs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListTrainingJobsRequest, app.mltraining.v1.ml_training_pb2.ListTrainingJobsResponse]) -> None :abstractmethod: :async: .. py:method:: CancelTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.CancelTrainingJobRequest, app.mltraining.v1.ml_training_pb2.CancelTrainingJobResponse]) -> None :abstractmethod: :async: .. py:method:: DeleteCompletedTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobRequest, app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobResponse]) -> None :abstractmethod: :async: .. py:method:: GetTrainingJobLogs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsResponse]) -> None :abstractmethod: :async: .. py:method:: __mapping__() -> Dict[str, grpclib.const.Handler] .. py:class:: MLTrainingServiceStub(channel: grpclib.client.Channel) .. py:attribute:: SubmitTrainingJob .. py:attribute:: SubmitCustomTrainingJob .. py:attribute:: GetTrainingJob .. py:attribute:: ListTrainingJobs .. py:attribute:: CancelTrainingJob .. py:attribute:: DeleteCompletedTrainingJob .. py:attribute:: GetTrainingJobLogs .. py:class:: UnimplementedMLTrainingServiceBase Bases: :py:obj:`MLTrainingServiceBase` Helper class that provides a standard way to create an ABC using inheritance. .. py:method:: SubmitTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitTrainingJobResponse]) -> None :async: .. py:method:: SubmitCustomTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobResponse]) -> None :async: .. py:method:: GetTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobResponse]) -> None :async: .. py:method:: ListTrainingJobs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListTrainingJobsRequest, app.mltraining.v1.ml_training_pb2.ListTrainingJobsResponse]) -> None :async: .. py:method:: CancelTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.CancelTrainingJobRequest, app.mltraining.v1.ml_training_pb2.CancelTrainingJobResponse]) -> None :async: .. py:method:: DeleteCompletedTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobRequest, app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobResponse]) -> None :async: .. py:method:: GetTrainingJobLogs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsResponse]) -> None :async: .. py:class:: CancelTrainingJobRequest(*, id: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:class:: CancelTrainingJobResponse Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:class:: DeleteCompletedTrainingJobRequest(*, id: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:class:: DeleteCompletedTrainingJobResponse Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:class:: GetTrainingJobLogsRequest(*, id: str = ..., page_token: str | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:attribute:: page_token :type: str .. py:method:: HasField(field_name: Literal['_page_token', b'_page_token', 'page_token', b'page_token']) -> bool Checks if a certain field is set for the message. For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, :exc:`ValueError` will be raised. :param field_name: The name of the field to check for presence. :type field_name: str :returns: Whether a value has been set for the named field. :rtype: bool :raises ValueError: if the `field_name` is not a member of this message. .. py:method:: WhichOneof(oneof_group: Literal['_page_token', b'_page_token']) -> Literal['page_token'] | None Returns the name of the field that is set inside a oneof group. If no field is set, returns None. :param oneof_group: the name of the oneof group to check. :type oneof_group: str :returns: The name of the group that is set, or None. :rtype: str or None :raises ValueError: no group with the given name exists .. py:class:: GetTrainingJobLogsResponse(*, logs: collections.abc.Iterable[global___TrainingJobLogEntry] | None = ..., next_page_token: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: next_page_token :type: str .. py:property:: logs :type: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TrainingJobLogEntry] .. py:class:: GetTrainingJobRequest(*, id: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:class:: GetTrainingJobResponse(*, metadata: global___TrainingJobMetadata | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:property:: metadata :type: global___TrainingJobMetadata .. py:method:: HasField(field_name: Literal['metadata', b'metadata']) -> bool Checks if a certain field is set for the message. For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, :exc:`ValueError` will be raised. :param field_name: The name of the field to check for presence. :type field_name: str :returns: Whether a value has been set for the named field. :rtype: bool :raises ValueError: if the `field_name` is not a member of this message. .. py:class:: ListTrainingJobsRequest(*, organization_id: str = ..., status: global___TrainingStatus = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: organization_id :type: str .. py:attribute:: status :type: global___TrainingStatus .. py:class:: ListTrainingJobsResponse(*, jobs: collections.abc.Iterable[global___TrainingJobMetadata] | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:property:: jobs :type: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___TrainingJobMetadata] .. py:class:: ModelFramework Bases: :py:obj:`_ModelFramework` .. py:class:: ModelType Bases: :py:obj:`_ModelType` .. py:class:: SubmitCustomTrainingJobRequest(*, dataset_id: str = ..., registry_item_id: str = ..., registry_item_version: str = ..., organization_id: str = ..., model_name: str = ..., model_version: str = ..., arguments: collections.abc.Mapping[str, str] | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:class:: ArgumentsEntry(*, key: str = ..., value: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: key :type: str .. py:attribute:: value :type: str .. py:attribute:: dataset_id :type: str .. py:attribute:: registry_item_id :type: str .. py:attribute:: registry_item_version :type: str .. py:attribute:: organization_id :type: str .. py:attribute:: model_name :type: str .. py:attribute:: model_version :type: str .. py:property:: arguments :type: google.protobuf.internal.containers.ScalarMap[str, str] .. py:class:: SubmitCustomTrainingJobResponse(*, id: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:class:: SubmitTrainingJobRequest(*, dataset_id: str = ..., organization_id: str = ..., model_name: str = ..., model_version: str = ..., model_type: global___ModelType = ..., model_framework: global___ModelFramework = ..., tags: collections.abc.Iterable[str] | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: dataset_id :type: str .. py:attribute:: organization_id :type: str .. py:attribute:: model_name :type: str .. py:attribute:: model_version :type: str .. py:attribute:: model_type :type: global___ModelType .. py:attribute:: model_framework :type: global___ModelFramework .. py:property:: tags :type: google.protobuf.internal.containers.RepeatedScalarFieldContainer[str] .. py:class:: SubmitTrainingJobResponse(*, id: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:class:: TrainingJobLogEntry(*, level: str = ..., time: google.protobuf.timestamp_pb2.Timestamp | None = ..., message: str = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: level :type: str .. py:attribute:: message :type: str .. py:property:: time :type: google.protobuf.timestamp_pb2.Timestamp .. py:method:: HasField(field_name: Literal['time', b'time']) -> bool Checks if a certain field is set for the message. For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, :exc:`ValueError` will be raised. :param field_name: The name of the field to check for presence. :type field_name: str :returns: Whether a value has been set for the named field. :rtype: bool :raises ValueError: if the `field_name` is not a member of this message. .. py:class:: TrainingJobMetadata(*, id: str = ..., dataset_id: str = ..., organization_id: str = ..., model_name: str = ..., model_version: str = ..., model_type: global___ModelType = ..., model_framework: global___ModelFramework = ..., is_custom_job: bool = ..., registry_item_id: str = ..., registry_item_version: str = ..., status: global___TrainingStatus = ..., error_status: google.rpc.status_pb2.Status | None = ..., created_on: google.protobuf.timestamp_pb2.Timestamp | None = ..., last_modified: google.protobuf.timestamp_pb2.Timestamp | None = ..., training_started: google.protobuf.timestamp_pb2.Timestamp | None = ..., training_ended: google.protobuf.timestamp_pb2.Timestamp | None = ..., synced_model_id: str = ..., tags: collections.abc.Iterable[str] | None = ...) Bases: :py:obj:`google.protobuf.message.Message` Abstract base class for protocol messages. Protocol message classes are almost always generated by the protocol compiler. These generated types subclass Message and implement the methods shown below. .. py:attribute:: id :type: str .. py:attribute:: dataset_id :type: str .. py:attribute:: organization_id :type: str .. py:attribute:: model_name :type: str .. py:attribute:: model_version :type: str .. py:attribute:: model_type :type: global___ModelType .. py:attribute:: model_framework :type: global___ModelFramework .. py:attribute:: is_custom_job :type: bool .. py:attribute:: registry_item_id :type: str .. py:attribute:: registry_item_version :type: str .. py:attribute:: status :type: global___TrainingStatus .. py:attribute:: synced_model_id :type: str .. py:property:: error_status :type: google.rpc.status_pb2.Status .. py:property:: created_on :type: google.protobuf.timestamp_pb2.Timestamp .. py:property:: last_modified :type: google.protobuf.timestamp_pb2.Timestamp .. py:property:: training_started :type: google.protobuf.timestamp_pb2.Timestamp .. py:property:: training_ended :type: google.protobuf.timestamp_pb2.Timestamp .. py:property:: tags :type: google.protobuf.internal.containers.RepeatedScalarFieldContainer[str] .. py:method:: HasField(field_name: Literal['created_on', b'created_on', 'error_status', b'error_status', 'last_modified', b'last_modified', 'training_ended', b'training_ended', 'training_started', b'training_started']) -> bool Checks if a certain field is set for the message. For a oneof group, checks if any field inside is set. Note that if the field_name is not defined in the message descriptor, :exc:`ValueError` will be raised. :param field_name: The name of the field to check for presence. :type field_name: str :returns: Whether a value has been set for the named field. :rtype: bool :raises ValueError: if the `field_name` is not a member of this message. .. py:class:: TrainingStatus Bases: :py:obj:`_TrainingStatus`