Global Functions
2 minute read
The W&B Python SDK provides a set of global functions that serve as the primary entry points for interacting with the platform. These functions are called directly on the wandb module and form the foundation of most W&B workflows.
Overview
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. |
finish() |
Complete a run and upload any remaining data to ensure all information is synced to the server. |
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. |
Getting Started
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:
import wandb
# Authenticate with W&B
wandb.login()
config = {
"learning_rate": 0.01,
"epochs": 10,
}
# Project where logs
project = "my-awesome-project"
# Start a new run
with wandb.init(project=project, config=config) as run:
# Your training code here...
# Log values to W&B
run.log({"accuracy": acc, "loss": loss})
## Key Concepts
- **Runs**: The fundamental unit of tracking in W&B, representing a single execution of your code
- **Authentication**: Required to sync data with the W&B platform
- **Configuration**: Store hyperparameters and metadata for your experiments
- **Sweeps**: Automated hyperparameter optimization across multiple runs
For detailed information about each function, click on the function names above to view their complete documentation, including parameters, examples, and usage patterns.
Feedback
Was this page helpful?
Glad to hear it! If you have more to say, please let us know.
Sorry to hear that. Please tell us how we can improve.