crested.tl.default_configs

crested.tl.default_configs(task, num_classes=None)

Get default loss, optimizer, and metrics for an existing task.

Possible tasks are: - “topic_classification” - “peak_regression”

If what you want to do is not supported, you can create your own by using the TaskConfig class.

Example

>>> configs = default_configs("topic_classification")
>>> optimizer, loss, metrics = configs.optimizer, configs.loss, configs.metrics
>>> trainer = Crested(data, model, config=configs, project_name="test")

Parameters:

• tasks – Task for which to get default components.

• num_classes (Optional[int] (default: None)) – Number of output classes of model. Required for Spearman correlation metric.

Return type:

TaskConfig

Returns:

Optimizer, loss, and metrics for the given task.

See also

crested.tl.TaskConfig