Document `wandb.sweep`
Documents the wandb.sweep function with tf-docs style docstrings and code examples.
@@ -738,6 +738,50 @@ def _sweep_status(sweep_obj, sweep_conf, sweep_runs):
def sweep(sweep, entity=None, project=None):
+ """Initialize a hyperparameter sweep.
+
+ To generate hyperparameter suggestions from the sweep and use them
+ to train a model, call `wandb.agent` with the sweep_id returned by
+ this command. For command line functionality, see the command line
+ tool `wandb sweep` (https://docs.wandb.ai/ref/cli/wandb-sweep).
+
+ Args:
+ sweep: dict, SweepConfig, or callable. The sweep configuration
+ (or configuration generator). If a dict or SweepConfig,
+ should conform to the W&B sweep config specification
+ (https://docs.wandb.ai/guides/sweeps/configuration). If a
+ callable, should take no arguments and return a dict that
+ conforms to the W&B sweep config spec.
+ entity: str (optional). An entity is a username or team name
+ where you're sending runs. This entity must exist before you
+ can send runs there, so make sure to create your account or
+ team in the UI before starting to log runs. If you don't
+ specify an entity, the run will be sent to your default
+ entity, which is usually your username. Change your default
+ entity in [Settings](wandb.ai/settings) under "default
+ location to create new projects".
+ project: str (optional). The name of the project where you're
+ sending the new run. If the project is not specified, the
+ run is put in an "Uncategorized" project.
+
+ Returns:
+ sweep_id: str. A unique identifier for the sweep.
+
+ Examples:
+ Basic usage
+ ```python
+ # this line initializes the sweep
+ sweep_id = wandb.sweep({'name': 'my-awesome-sweep',
+ 'metric': 'accuracy',
+ 'method': 'grid',
+ 'parameters': {'a': {'values': [1, 2, 3, 4]}}})
+
+ # this line actually runs it -- parameters are available to
+ # my_train_func via wandb.config
+ wandb.agent(sweep_id, function=my_train_func)
+ ```
+ """
+
from wandb.sweeps.config import SweepConfig
import types
