caikit.core.model_management.model_trainer_base

A Trainer is responsible for managing execution of a training job for a given module class

Configuration for ModelTrainers lives under the config as follows:

model_management:

trainers:

<trainer name>:: type: <trainer type name> config:

<config option>: <value>

Classes

`TrainingInfo`
`ModelTrainerFutureBase`	Every JobBase implementation must have a JobFutureBase class that can access the
`ModelTrainerBase`	A class can be constructed by a factory if its constructor takes exactly

Module Contents

class caikit.core.model_management.model_trainer_base.TrainingInfo[source]: Bases: caikit.core.model_management.job_base.JobInfo

class caikit.core.model_management.model_trainer_base.ModelTrainerFutureBase(*args, **kwargs)[source]

Bases: caikit.core.model_management.job_base.JobFutureBase

Every JobBase implementation must have a JobFutureBase class that can access the job information in the infrastructure managed by the task.

_save_path

property save_path: str | None: If created with a save path, the future must expose it, including any injected background id

abstract load() → caikit.core.modules.ModuleBase[source]: A model future must be loadable with no additional arguments. Mainly useful in train results

result() → caikit.core.modules.ModuleBase[source]: The result of a model train future is the loaded model

class caikit.core.model_management.model_trainer_base.ModelTrainerBase(config: aconfig.Config, instance_name: str)[source]

Bases: caikit.core.model_management.job_base.JobBase

A class can be constructed by a factory if its constructor takes exactly one argument that is an aconfig.Config object and it has a name to identify itself with the factory.

__doc__ = Multiline-String

Show Value

"""
A Trainer is responsible for managing execution of a training job for a given
module class

Configuration for ModelTrainers lives under the config as follows:

model_management:
    trainers:
        <trainer name>:
            type: <trainer type name>
            config:
                <config option>: <value>
"""

ModelFutureBase

abstract train(module_class: Type[caikit.core.modules.ModuleBase], *args, save_path: str | caikit.interfaces.common.data_model.stream_sources.S3Path | None = None, save_with_id: bool = False, model_name: str | None = None, **kwargs) → ModelFutureBase[source]: Start training the given module and return a future to the trained model instance

abstract get_model_future(training_id: str) → ModelFutureBase[source]: Look up the model future for the given id

get_future(job_id: str) → caikit.core.model_management.job_base.JobFutureBase[source]: Look up the model future for the given id

classmethod get_trainer_name(training_id: str) → str[source]: Un-hash the trainer’s instance name from the given training id