autointent.context.optimization_info.OptimizationInfo#
- class autointent.context.optimization_info.OptimizationInfo#
Tracks optimization results, including trials, artifacts, and modules.
This class provides methods for logging optimization results, retrieving the best-performing modules and artifacts, and generating configuration for inference nodes.
- artifacts#
Container for storing optimization artifacts.
- trials#
Container for storing optimization trials.
- modules#
Container for storing module instances.
- pipeline_metrics#
Dictionary storing pipeline-level metrics.
- artifacts#
- trials#
- modules#
- log_module_optimization(node_type, module_name, module_params, metric_value, metric_name, metrics, artifact, module_dump_dir, module=None)#
Log optimization results for a module.
- Parameters:
node_type (str) – Type of the node being optimized.
module_name (str) – Type of the module.
module_params (dict[str, Any]) – Parameters of the module for the trial.
metric_value (float) – Metric value achieved by the module.
metric_name (str) – Name of the evaluation metric.
metrics (dict[str, float]) – Dictionary of metric names and their values.
artifact (autointent.context.optimization_info._data_models.Artifact) – Artifact generated by the module.
module_dump_dir (str | None) – Directory where the module is dumped.
module (BaseModule | None) – The module instance, if available.
- Return type:
None
- get_best_embedder()#
Retrieve the name of the best embedder from the retriever node.
- Returns:
Configuration of the best embedder.
- Return type:
- get_best_train_scores()#
Retrieve the train scores from the best scorer node.
- Returns:
Train scores as a numpy array.
- Return type:
numpy.typing.NDArray[numpy.float64] | None
- get_best_validation_scores()#
Retrieve the validation scores from the best scorer node.
- Returns:
Validation scores as a numpy array.
- Return type:
numpy.typing.NDArray[numpy.float64] | None
- get_best_folded_scores()#
Retrieve the validation scores from the best scorer node.
- Returns:
Validation scores as a numpy array.
- Return type:
list[numpy.typing.NDArray[numpy.float64]] | None
- get_best_test_scores()#
Retrieve the test scores from the best scorer node.
- Returns:
Test scores as a numpy array.
- Return type:
numpy.typing.NDArray[numpy.float64] | None
- dump_evaluation_results()#
Dump evaluation results for all nodes.
- get_inference_nodes_config(asdict=False)#
Generate configuration for inference nodes based on the best trials.
- Parameters:
asdict (bool) – Whether to return the configuration as dictionaries.
- Returns:
List of configurations for inference nodes.
- Return type:
- get_best_modules()#
Retrieve the best modules for all node types.
- Returns:
Dictionary of the best modules for each node type.
- Return type:
dict[autointent.custom_types.NodeType, autointent.modules.base.BaseModule]