otx.algorithms.common.tasks.base_task#
Base task of OTX.
Classes
|
Base task of OTX. |
|
OnHookInitialized class. |
- class otx.algorithms.common.tasks.base_task.OTXTask(task_environment: TaskEnvironment, output_path: str | None = None)[source]#
Bases:
IInferenceTask
,IExportTask
,IEvaluationTask
,IUnload
,ABC
Base task of OTX.
- cancel_hook_initialized(cancel_interface: CancelInterfaceHook)[source]#
Initialization of cancel_interface hook.
- cancel_training()[source]#
Cancel training function in trining task.
Sends a cancel training signal to gracefully stop the optimizer. The signal consists of creating a ‘.stop_training’ file in the current work_dir. The runner checks for this file periodically. The stopping mechanism allows stopping after each iteration, but validation will still be carried out. Stopping will therefore take some time.
- abstract evaluate(output_resultset: ResultSetEntity, evaluation_metric: str | None = None)[source]#
Evaluate function of OTX Task.
- abstract explain(dataset: DatasetEntity, explain_parameters: ExplainParameters | None = None) DatasetEntity [source]#
Main explain function of OTX Task.
- abstract export(export_type: ExportType, output_model: ModelEntity, precision: ModelPrecision = ModelPrecision.FP32, dump_features: bool = True)[source]#
Export function of OTX Task.
- abstract infer(dataset: DatasetEntity, inference_parameters: InferenceParameters | None = None) DatasetEntity [source]#
Main infer function.
- abstract save_model(output_model: ModelEntity)[source]#
Save best model weights in trining task.
- abstract train(dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters | None = None, seed: int | None = None, deterministic: bool = False)[source]#
Train function for OTX task.
- property config#
Config of OTX task.