Update .pre-commit-config.yaml (#11009)

* Update .pre-commit-config.yaml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update __init__.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update .pre-commit-config.yaml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Pre-commit updates

* Pre-commit updates

---------

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

train.py

@@ -148,7 +148,7 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
     # Batch size
     if RANK == -1 and batch_size == -1:  # single-GPU only, estimate best batch size
         batch_size = check_train_batch_size(model, imgsz, amp)
-        loggers.on_params_update({"batch_size": batch_size})
+        loggers.on_params_update({'batch_size': batch_size})
 
     # Optimizer
     nbs = 64  # nominal batch size
@@ -522,7 +522,7 @@ def main(opt, callbacks=Callbacks()):
         assert torch.cuda.device_count() > LOCAL_RANK, 'insufficient CUDA devices for DDP command'
         torch.cuda.set_device(LOCAL_RANK)
         device = torch.device('cuda', LOCAL_RANK)
-        dist.init_process_group(backend="nccl" if dist.is_nccl_available() else "gloo")
+        dist.init_process_group(backend='nccl' if dist.is_nccl_available() else 'gloo')
 
     # Train
     if not opt.evolve:
@@ -635,6 +635,6 @@ def run(**kwargs):
     return opt
 
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     opt = parse_opt()
     main(opt)