Sweep from Jupyter Notebook

Run sweeps from Jupyter notebooks
Initialize a sweep
import wandb
​
sweep_config = {
  "name": "My Sweep",
  "method": "grid",
  "parameters": {
        "param1": {
            "values": [1, 2, 3]
        }
    }
}
​
sweep_id = wandb.sweep(sweep_config)
Use the following methods in order to specify the entity or project for the sweep:
Arguments to wandb.sweep() For example: wandb.sweep(sweep_config, entity="user", project="my_project")
​Environment Variables WANDB_ENTITY and WANDB_PROJECT
​Command Line Interface using the wandb init command
​Sweep configuration using the keys "entity" and "project"
Run an agent
When running an agent from python, the agent runs a specified function instead of using the program key from the sweep configuration file.
import wandb
import time
​
def train():
    run = wandb.init()
    print("config:", dict(run.config))
    for epoch in range(35):
        print("running", epoch)
        wandb.log({"metric": run.config.param1, "epoch": epoch})
        time.sleep(1)
​
wandb.agent(sweep_id, function=train)
Quick overview: Run in colab​
Complete walkthrough of using sweeps in a project: Run in colab​
wandb.agent()
Arguments
sweep_id (dict): Sweep ID generated by the UI, CLI, or sweep API
entity (str, optional): username or team where you want to send runs
project (str, optional): project where you want to send runs
function (dir, optional): Configure sweep function
Run a local controller
If you want to develop your own parameter search algorithms you can run your controller from python.
The simplest way to run a controller:
sweep = wandb.controller(sweep_id)
sweep.run()
If you want more control of the controller loop:
import wandb
sweep = wandb.controller(sweep_id)
while not sweep.done():
    sweep.print_status()
    sweep.step()
    time.sleep(5)
Or even more control over the parameters being served:
import wandb
sweep = wandb.controller(sweep_id)
while not sweep.done():
    params = sweep.search()
    sweep.schedule(params)
    sweep.print_status()
If you want to specify your sweep entirely with code you can do something like this:
import wandb
from wandb.sweeps import GridSearch,RandomSearch,BayesianSearch
​
sweep = wandb.controller()
sweep.configure_search(GridSearch)
sweep.configure_program('train-dummy.py')
sweep.configure_controller(type="local")
sweep.configure_parameter('param1', value=3)
sweep.create()
sweep.run()
Common Questions
Local Controller
Last updated 4 weeks ago