> ## Documentation Index
> Fetch the complete documentation index at: https://wb-21fd5541-docs-1917.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# How can I use wandb with multiprocessing, e.g. distributed training?

If a training program uses multiple processes, structure the program to avoid making wandb method calls from processes without `wandb.init()`.

Manage multiprocess training using these approaches:

1. Call `wandb.init` in all processes and use the [group](/models/runs/grouping) keyword argument to create a shared group. Each process will have its own wandb run, and the UI will group the training processes together.
2. Call `wandb.init` from only one process and pass data to log through [multiprocessing queues](https://docs.python.org/3/library/multiprocessing.html#exchanging-objects-between-processes).

<Note>
  Refer to the [Distributed Training Guide](/models/track/log/distributed-training) for detailed explanations of these approaches, including code examples with Torch DDP.
</Note>

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