> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.

> Initialize a W&B Sweep using the Python SDK or CLI to start hyperparameter searches with your sweep configuration.

# Initialize a sweep

W\&B uses a *Sweep Controller* to manage sweeps on the cloud (standard), locally (local) across one or more machines. After a run completes, the sweep controller will issue a new set of instructions describing a new run to execute. These instructions are picked up by *agents* who actually perform the runs. In a typical W\&B Sweep, the controller lives on the W\&B server. Agents live on *your* machines.

The following code snippets demonstrate how to initialize sweeps with the CLI and within a Jupyter Notebook or Python script.

<Warning>
  1. Before you initialize a sweep, make sure you have a sweep configuration defined either in a YAML file or a nested Python dictionary object in your script. For more information, see [Define sweep configuration](/models/sweeps/define-sweep-configuration/).
  2. Both the W\&B Sweep and the W\&B Run must be in the same project. Therefore, the name you provide when you initialize W\&B ([`wandb.init()`](/models/ref/python/functions/init)) must match the name of the project you provide when you initialize a W\&B Sweep ([`wandb.sweep()`](/models/ref/python/functions/sweep)).
</Warning>

<Tabs>
  <Tab title="Python script or notebook">
    Use the W\&B SDK to initialize a sweep. Pass the sweep configuration dictionary to the `sweep` parameter. Optionally provide the name of the project for the project parameter (`project`) where you want the output of the W\&B Run to be stored. If the project is not specified, the run is put in an "Uncategorized" project.

    ```python theme={null}
    import wandb

    # Example sweep configuration
    sweep_configuration = {
        "method": "random",
        "name": "sweep",
        "metric": {"goal": "maximize", "name": "val_acc"},
        "parameters": {
            "batch_size": {"values": [16, 32, 64]},
            "epochs": {"values": [5, 10, 15]},
            "lr": {"max": 0.1, "min": 0.0001},
        },
    }

    sweep_id = wandb.sweep(sweep=sweep_configuration, project="project-name")
    ```

    The [`wandb.sweep()`](/models/ref/python/functions/sweep) function returns the sweep ID. The sweep ID includes the entity name and the project name. Make a note of the sweep ID.
  </Tab>

  <Tab title="CLI">
    Use the W\&B CLI to initialize a sweep. Provide the name of your configuration file. Optionally provide the name of the project for the `project` flag. If the project is not specified, the W\&B Run is put in an "Uncategorized" project.

    Use the [`wandb sweep`](/models/ref/cli/wandb-sweep) command to initialize a sweep. The following code example initializes a sweep for a `sweeps_demo` project and uses a `config.yaml` file for the configuration.

    ```bash theme={null}
    wandb sweep --project sweeps_demo config.yaml
    ```

    This command will print out a sweep ID. The sweep ID includes the entity name and the project name. Make a note of the sweep ID.
  </Tab>
</Tabs>