Wandb is a library to help track machine learning experiments.
For more information on wandb see https://docs.wandb.com.
The most commonly used functions/objects are:
wandb.init — initialize a new run at the top of your training script
wandb.config — track hyperparameters
wandb.log — log metrics over time within your training loop
wandb.save — save files in association with your run, like model weights
wandb.restore — restore the state of your code when you ran a given run
For examples usage, see github.com/wandb/examples
class Api: Used for querying the wandb server.
class File: File is a class associated with a file saved by wandb.
class Files: Files is an iterable collection of
class Project: A project is a namespace for runs
class Projects: An iterable collection of
class Run: A single run associated with an entity and project.
class Runs: An iterable collection of runs associated with a project and optional filter.
class Sweep: A set of runs associated with a sweep