Run

Class wandb.Run

A unit of computation logged by W&B. Typically, this is an ML experiment. Call wandb.init() to create a new run. wandb.init() starts a new run and returns a wandb.Run object. Each run is associated with a unique ID (run ID). W&B recommends using a context (with statement) manager to automatically finish the run. For distributed training experiments, you can either track each process separately using one run per process or track all processes to a single run. See Log distributed training experiments for more information. You can log data to a run with wandb.Run.log(). Anything you log using wandb.Run.log() is sent to that run. See Create an experiment or wandb.init API reference page or more information. There is a another Run object in the wandb.apis.public namespace. Use this object is to interact with runs that have already been created.

Attributes

summary: (Summary) A summary of the run, which is a dictionary-like object. For more information, see Log summary metrics.

Examples

Create a run with wandb.init():

import wandb

# Start a new run and log some data
# Use context manager (`with` statement) to automatically finish the run
with wandb.init(entity="entity", project="project") as run:
    run.log({"accuracy": acc, "loss": loss})

W&B Models

W&B Weave

Serverless Inference

Serverless Training

Class wandb.Run

Attributes

Examples

​Class wandb.Run

​Attributes

​Examples

Class wandb.Run

Attributes

Examples