viam.proto.app.mltraining

@generated by Viam. Do not edit manually!

Classes

`MLTrainingServiceBase`	Helper class that provides a standard way to create an ABC using
`MLTrainingServiceStub`
`UnimplementedMLTrainingServiceBase`	Helper class that provides a standard way to create an ABC using
`CancelTrainingJobRequest`	Abstract base class for protocol messages.
`CancelTrainingJobResponse`	Abstract base class for protocol messages.
`Container`	Abstract base class for protocol messages.
`DeleteCompletedTrainingJobRequest`	Abstract base class for protocol messages.
`DeleteCompletedTrainingJobResponse`	Abstract base class for protocol messages.
`DeleteCustomTrainingContainerRequest`	Abstract base class for protocol messages.
`DeleteCustomTrainingContainerResponse`	Abstract base class for protocol messages.
`GetContainerRequest`	Abstract base class for protocol messages.
`GetContainerResponse`	Abstract base class for protocol messages.
`GetTrainingJobLogsRequest`	Abstract base class for protocol messages.
`GetTrainingJobLogsResponse`	Abstract base class for protocol messages.
`GetTrainingJobRequest`	Abstract base class for protocol messages.
`GetTrainingJobResponse`	Abstract base class for protocol messages.
`ListContainersRequest`	Abstract base class for protocol messages.
`ListContainersResponse`	Abstract base class for protocol messages.
`ListSupportedContainersRequest`	Abstract base class for protocol messages.
`ListSupportedContainersResponse`	Abstract base class for protocol messages.
`ListTrainingJobsRequest`	Abstract base class for protocol messages.
`ListTrainingJobsResponse`	Abstract base class for protocol messages.
`ModelFramework`
`ModelType`
`RegisterCustomTrainingContainerRequest`	Abstract base class for protocol messages.
`RegisterCustomTrainingContainerResponse`	Abstract base class for protocol messages.
`SubmitCustomTrainingJobRequest`	Abstract base class for protocol messages.
`SubmitCustomTrainingJobResponse`	Abstract base class for protocol messages.
`SubmitTrainingJobRequest`	Abstract base class for protocol messages.
`SubmitTrainingJobResponse`	Abstract base class for protocol messages.
`TrainingJobLogEntry`	Abstract base class for protocol messages.
`TrainingJobMetadata`	Abstract base class for protocol messages.
`TrainingStatus`
`Visibility`

Package Contents

class viam.proto.app.mltraining.MLTrainingServiceBase[source]

Bases: abc.ABC

Helper class that provides a standard way to create an ABC using inheritance.

abstractmethod SubmitTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitTrainingJobResponse]) → None[source]

Async:

abstractmethod SubmitCustomTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobResponse]) → None[source]

Async:

abstractmethod GetTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobResponse]) → None[source]

Async:

abstractmethod ListTrainingJobs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListTrainingJobsRequest, app.mltraining.v1.ml_training_pb2.ListTrainingJobsResponse]) → None[source]

Async:

abstractmethod CancelTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.CancelTrainingJobRequest, app.mltraining.v1.ml_training_pb2.CancelTrainingJobResponse]) → None[source]

Async:

abstractmethod DeleteCompletedTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobRequest, app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobResponse]) → None[source]

Async:

abstractmethod GetTrainingJobLogs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsResponse]) → None[source]

Async:

abstractmethod ListSupportedContainers(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListSupportedContainersRequest, app.mltraining.v1.ml_training_pb2.ListSupportedContainersResponse]) → None[source]

Async:

abstractmethod ListContainers(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListContainersRequest, app.mltraining.v1.ml_training_pb2.ListContainersResponse]) → None[source]

Async:

abstractmethod GetContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetContainerRequest, app.mltraining.v1.ml_training_pb2.GetContainerResponse]) → None[source]

Async:

abstractmethod RegisterCustomTrainingContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.RegisterCustomTrainingContainerRequest, app.mltraining.v1.ml_training_pb2.RegisterCustomTrainingContainerResponse]) → None[source]

Async:

abstractmethod DeleteCustomTrainingContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCustomTrainingContainerRequest, app.mltraining.v1.ml_training_pb2.DeleteCustomTrainingContainerResponse]) → None[source]

Async:

__mapping__() → Dict[str, grpclib.const.Handler][source]

class viam.proto.app.mltraining.MLTrainingServiceStub(channel: grpclib.client.Channel)[source]

SubmitTrainingJob

SubmitCustomTrainingJob

GetTrainingJob

ListTrainingJobs

CancelTrainingJob

DeleteCompletedTrainingJob

GetTrainingJobLogs

ListSupportedContainers

ListContainers

GetContainer

RegisterCustomTrainingContainer

DeleteCustomTrainingContainer

class viam.proto.app.mltraining.UnimplementedMLTrainingServiceBase[source]

Bases: MLTrainingServiceBase

Helper class that provides a standard way to create an ABC using inheritance.

async SubmitTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitTrainingJobResponse]) → None[source]

async SubmitCustomTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobRequest, app.mltraining.v1.ml_training_pb2.SubmitCustomTrainingJobResponse]) → None[source]

async GetTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobResponse]) → None[source]

async ListTrainingJobs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListTrainingJobsRequest, app.mltraining.v1.ml_training_pb2.ListTrainingJobsResponse]) → None[source]

async CancelTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.CancelTrainingJobRequest, app.mltraining.v1.ml_training_pb2.CancelTrainingJobResponse]) → None[source]

async DeleteCompletedTrainingJob(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobRequest, app.mltraining.v1.ml_training_pb2.DeleteCompletedTrainingJobResponse]) → None[source]

async GetTrainingJobLogs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsResponse]) → None[source]

async ListSupportedContainers(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListSupportedContainersRequest, app.mltraining.v1.ml_training_pb2.ListSupportedContainersResponse]) → None[source]

async ListContainers(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.ListContainersRequest, app.mltraining.v1.ml_training_pb2.ListContainersResponse]) → None[source]

async GetContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetContainerRequest, app.mltraining.v1.ml_training_pb2.GetContainerResponse]) → None[source]

async RegisterCustomTrainingContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.RegisterCustomTrainingContainerRequest, app.mltraining.v1.ml_training_pb2.RegisterCustomTrainingContainerResponse]) → None[source]

async DeleteCustomTrainingContainer(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.DeleteCustomTrainingContainerRequest, app.mltraining.v1.ml_training_pb2.DeleteCustomTrainingContainerResponse]) → None[source]

class viam.proto.app.mltraining.CancelTrainingJobRequest(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.CancelTrainingJobResponse

Bases: 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.

class viam.proto.app.mltraining.Container(*, key: str = ..., uri: str = ..., framework: str = ..., description: str = ..., eol: google.protobuf.timestamp_pb2.Timestamp | None = ..., organization_id: str = ..., created_on: google.protobuf.timestamp_pb2.Timestamp | None = ..., id: str = ..., visibility: Global___Visibility = ...)

Bases: 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.

key: str

tag)

Type:: custom container keys are derived from the Docker URI (image

uri: str

framework: str: unset for custom containers

description: str: will serve as display name

organization_id: str

id: str: unique id of the container

visibility: Global___Visibility: public or private

eol() → google.protobuf.timestamp_pb2.Timestamp: unset for custom containers

created_on() → google.protobuf.timestamp_pb2.Timestamp

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

class viam.proto.app.mltraining.DeleteCompletedTrainingJobRequest(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.DeleteCompletedTrainingJobResponse

Bases: 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.

class viam.proto.app.mltraining.DeleteCustomTrainingContainerRequest(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.DeleteCustomTrainingContainerResponse

Bases: 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.

class viam.proto.app.mltraining.GetContainerRequest(*, id: str = ...)

Bases: 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.

id: str: The ID of the container to retrieve.

class viam.proto.app.mltraining.GetContainerResponse(*, container: Global___Container | None = ...)

Bases: 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.

container() → Global___Container

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

class viam.proto.app.mltraining.GetTrainingJobLogsRequest(*, id: str = ..., page_token: str | None = ...)

Bases: 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.

id: str

page_token: str

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

WhichOneof(oneof_group: _WhichOneofArgType__page_token) → _WhichOneofReturnType__page_token | None

Returns the name of the field that is set inside a oneof group.

If no field is set, returns None.

Parameters:: oneof_group (str) – the name of the oneof group to check.
Returns:: The name of the group that is set, or None.
Return type:: str or None
Raises:: ValueError – no group with the given name exists

class viam.proto.app.mltraining.GetTrainingJobLogsResponse(*, logs: collections.abc.Iterable[Global___TrainingJobLogEntry] | None = ..., next_page_token: str = ...)

Bases: 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.

next_page_token: str

logs() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___TrainingJobLogEntry]

class viam.proto.app.mltraining.GetTrainingJobRequest(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.GetTrainingJobResponse(*, metadata: Global___TrainingJobMetadata | None = ...)

Bases: 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.

metadata() → Global___TrainingJobMetadata

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

class viam.proto.app.mltraining.ListContainersRequest(*, organization_id: str = ...)

Bases: 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.

organization_id: str: The associated Viam organization ID.

class viam.proto.app.mltraining.ListContainersResponse(*, containers: collections.abc.Iterable[Global___Container] | None = ...)

Bases: 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.

containers() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___Container]

class viam.proto.app.mltraining.ListSupportedContainersRequest

Bases: 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.

class viam.proto.app.mltraining.ListSupportedContainersResponse(*, container_map: collections.abc.Mapping[str, Global___Container] | None = ...)

Bases: 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.

class ContainerMapEntry(*, key: str = ..., value: Global___Container | None = ...)

Bases: 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.

key: str

value() → Global___Container

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

container_map() → google.protobuf.internal.containers.MessageMap[str, Global___Container]

ex value: container_map: {

“tf:2.15”: Container {
key: “tf:2.15” uri: “us-docker.pkg.dev/vertex-ai/training/tf-gpu.2-15.py310:latest” framework: Tensorflow description: “Tensorflow 2.15” eol: { seconds: 1772630400, nanos: 0 } // 2026-03-03T00:00:00Z created_on: 2026-01-15T01:30:15.01Z organization_id: “xyz” visibility: VISIBILITY_PUBLIC

}

}

class viam.proto.app.mltraining.ListTrainingJobsRequest(*, organization_id: str = ..., status: Global___TrainingStatus = ...)

Bases: 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.

organization_id: str

status: Global___TrainingStatus

class viam.proto.app.mltraining.ListTrainingJobsResponse(*, jobs: collections.abc.Iterable[Global___TrainingJobMetadata] | None = ...)

Bases: 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.

jobs() → google.protobuf.internal.containers.RepeatedCompositeFieldContainer[Global___TrainingJobMetadata]

class viam.proto.app.mltraining.ModelFramework: Bases: _ModelFramework

class viam.proto.app.mltraining.ModelType: Bases: _ModelType

class viam.proto.app.mltraining.RegisterCustomTrainingContainerRequest(*, organization_id: str = ..., image_uri: str = ..., description: str = ...)

Bases: 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.

organization_id: str

image_uri: str

<tag>.

Type:: Docker Hub reference, official images normalize to docker.io/library/<image>

description: str: will serve as display name

class viam.proto.app.mltraining.RegisterCustomTrainingContainerResponse(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.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 = ..., container_version: str = ..., container_id: str = ...)

Bases: 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.

class ArgumentsEntry(*, key: str = ..., value: str = ...)

Bases: 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.

key: str

value: str

dataset_id: str

registry_item_id: str

registry_item_version: str

organization_id: str

model_name: str

model_version: str

container_version: str

container_id: str

arguments() → google.protobuf.internal.containers.ScalarMap[str, str]

class viam.proto.app.mltraining.SubmitCustomTrainingJobResponse(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.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: 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.

dataset_id: str

organization_id: str

model_name: str

model_version: str

model_type: Global___ModelType

model_framework: Global___ModelFramework

tags() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[str]

class viam.proto.app.mltraining.SubmitTrainingJobResponse(*, id: str = ...)

Bases: 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.

id: str

class viam.proto.app.mltraining.TrainingJobLogEntry(*, level: str = ..., time: google.protobuf.timestamp_pb2.Timestamp | None = ..., message: str = ...)

Bases: 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.

level: str

message: str

time() → google.protobuf.timestamp_pb2.Timestamp

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

class viam.proto.app.mltraining.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 = ..., arguments: collections.abc.Mapping[str, str] | None = ..., container_version: str = ..., container_id: str = ...)

Bases: 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.

class ArgumentsEntry(*, key: str = ..., value: str = ...)

Bases: 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.

key: str

value: str

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

synced_model_id: str

container_version: str

container_id: str

error_status() → google.rpc.status_pb2.Status

created_on() → google.protobuf.timestamp_pb2.Timestamp

last_modified() → google.protobuf.timestamp_pb2.Timestamp

training_started() → google.protobuf.timestamp_pb2.Timestamp

training_ended() → google.protobuf.timestamp_pb2.Timestamp

tags() → google.protobuf.internal.containers.RepeatedScalarFieldContainer[str]

arguments() → google.protobuf.internal.containers.ScalarMap[str, str]

HasField(field_name: _HasFieldArgType) → 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, ValueError will be raised.

Parameters:: field_name (str) – The name of the field to check for presence.
Returns:: Whether a value has been set for the named field.
Return type:: bool
Raises:: ValueError – if the field_name is not a member of this message.

class viam.proto.app.mltraining.TrainingStatus: Bases: _TrainingStatus

class viam.proto.app.mltraining.Visibility: Bases: _Visibility