# Is wandb in Trainer configured for distributed training?

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**Category:** 🤗Transformers\
**Created:** [July 31, 2022, 2:44pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fis-wandb-in-trainer-configured-for-distributed-training%2F21067 "2022-07-31T14:44:49Z")\
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**Author:** ![brando](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/brando/32/30114_2.png) [@brando](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fbrando)%5C
**Post date:** [August 18, 2022, 3:29pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fis-wandb-in-trainer-configured-for-distributed-training%2F21067%2F3 "2022-08-18T15:29:25Z")

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seems only doing init with main worker worked for me and it stopped having the 8 workers all logging to wandb, code:

```auto
report_to = "none"
report_to = "wandb"
if report_to != 'none' and is_main_process_using_local_rank():
        wandb.init(project="proj", entity="me", name='run_name_clean_wandb_dist', group='group_expt_name')

def is_main_process_using_local_rank() -> bool:
    """
    Determines if it's the main process using the local rank.

    based on print statements:
        local_rank=0
        local_rank=1

    other ref:
        # - set up processes a la l2l
        local_rank: int = get_local_rank()
        print(f'{local_rank=}')
        init_process_group_l2l(args, local_rank=local_rank, world_size=args.world_size, init_method=args.init_method)
        rank: int = torch.distributed.get_rank() if is_running_parallel(local_rank) else -1
        args.rank = rank # have each process save the rank
        set_devices_and_seed_ala_l2l(args) # args.device = rank or .device
        print(f'setup process done for rank={args.rank}')
    """
    local_rank: int = get_local_rank()
    return local_rank == -1 or local_rank == 0 # -1 means serial, 0 likely means parallel

```

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