Global Functions
2 minute read
Global functions in W&B are top-level functions that you call directly, such as wandb.init() or wandb.login(). Unlike methods that belong to specific classes, these functions provide direct access to W&B’s core functionality without needing to instantiate objects first.
Available Functions
| Function | Description |
|---|---|
init() |
Start a new run to track and log to W&B. This is typically the first function you’ll call in your ML training pipeline. |
login() |
Set up W&B login credentials to authenticate your machine with the platform. |
setup() |
Prepare W&B for use in the current process and its children. Useful for multi-process applications. |
teardown() |
Clean up W&B resources and shut down the backend process. |
sweep() |
Initialize a hyperparameter sweep to search for optimal model configurations. |
agent() |
Create a sweep agent to run hyperparameter optimization experiments. |
controller() |
Manage and control sweep agents and their execution. |
restore() |
Restore a previous run or experiment state for resuming work. |
Example
The most common workflow begins with authenticating with W&B, initializing a run, and logging values (such as accuracy and loss) from your training loop. The first steps are to import wandb and use the global functions login() and init():
import wandb
# Authenticate with W&B
wandb.login()
# Hyperparameters and metadata
config = {
"learning_rate": 0.01,
"epochs": 10,
}
# Project that the run is recorded to
project = "my-awesome-project"
# Initialize a new run
with wandb.init(project=project, config=config) as run:
# Your training code here...
# Log values to W&B
run.log({"accuracy": 0.9, "loss": 0.1})
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