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.
`DeleteCompletedTrainingJobRequest`	Abstract base class for protocol messages.
`DeleteCompletedTrainingJobResponse`	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.
`ListTrainingJobsRequest`	Abstract base class for protocol messages.
`ListTrainingJobsResponse`	Abstract base class for protocol messages.
`ModelFramework`
`ModelType`
`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`

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.

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

Async:

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

Async:

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

Async:

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

Async:

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

Async:

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

Async:

abstract GetTrainingJobLogs(stream: grpclib.server.Stream[app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsRequest, app.mltraining.v1.ml_training_pb2.GetTrainingJobLogsResponse]) → 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

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]

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.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.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: 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, 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: 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.

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

property 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.

property metadata: global___TrainingJobMetadata

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, 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.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.

property 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.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: 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

property 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 = ..., 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

property 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

property time: google.protobuf.timestamp_pb2.Timestamp

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, 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 = ...)

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

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

property error_status: google.rpc.status_pb2.Status

property created_on: google.protobuf.timestamp_pb2.Timestamp

property last_modified: google.protobuf.timestamp_pb2.Timestamp

property training_started: google.protobuf.timestamp_pb2.Timestamp

property training_ended: google.protobuf.timestamp_pb2.Timestamp

property tags: google.protobuf.internal.containers.RepeatedScalarFieldContainer[str]

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, 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