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W&B DDP fix #2574

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Mar 23, 2021
Merged

W&B DDP fix #2574

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8 changes: 5 additions & 3 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,14 +66,16 @@ def train(hyp, opt, device, tb_writer=None):
is_coco = opt.data.endswith('coco.yaml')

# Logging- Doing this before checking the dataset. Might update data_dict
loggers = {'wandb': None} # loggers dict
if rank in [-1, 0]:
opt.hyp = hyp # add hyperparameters
run_id = torch.load(weights).get('wandb_id') if weights.endswith('.pt') and os.path.isfile(weights) else None
wandb_logger = WandbLogger(opt, Path(opt.save_dir).stem, run_id, data_dict)
loggers['wandb'] = wandb_logger.wandb
data_dict = wandb_logger.data_dict
if wandb_logger.wandb:
weights, epochs, hyp = opt.weights, opt.epochs, opt.hyp # WandbLogger might update weights, epochs if resuming
loggers = {'wandb': wandb_logger.wandb} # loggers dict

nc = 1 if opt.single_cls else int(data_dict['nc']) # number of classes
names = ['item'] if opt.single_cls and len(data_dict['names']) != 1 else data_dict['names'] # class names
assert len(names) == nc, '%g names found for nc=%g dataset in %s' % (len(names), nc, opt.data) # check
Expand Down Expand Up @@ -381,6 +383,7 @@ def train(hyp, opt, device, tb_writer=None):
fi = fitness(np.array(results).reshape(1, -1)) # weighted combination of [P, R, mAP@.5, mAP@.5-.95]
if fi > best_fitness:
best_fitness = fi
wandb_logger.end_epoch(best_result=best_fitness == fi)

# Save model
if (not opt.nosave) or (final_epoch and not opt.evolve): # if save
Expand All @@ -402,7 +405,6 @@ def train(hyp, opt, device, tb_writer=None):
wandb_logger.log_model(
last.parent, opt, epoch, fi, best_model=best_fitness == fi)
del ckpt
wandb_logger.end_epoch(best_result=best_fitness == fi)

# end epoch ----------------------------------------------------------------------------------------------------
# end training
Expand Down Expand Up @@ -442,10 +444,10 @@ def train(hyp, opt, device, tb_writer=None):
wandb_logger.wandb.log_artifact(str(final), type='model',
name='run_' + wandb_logger.wandb_run.id + '_model',
aliases=['last', 'best', 'stripped'])
wandb_logger.finish_run()
else:
dist.destroy_process_group()
torch.cuda.empty_cache()
wandb_logger.finish_run()
return results


Expand Down
5 changes: 4 additions & 1 deletion utils/wandb_logging/wandb_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,9 +16,9 @@

try:
import wandb
from wandb import init, finish
except ImportError:
wandb = None
print(f"{colorstr('wandb: ')}Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)")

WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'

Expand Down Expand Up @@ -71,6 +71,9 @@ def __init__(self, opt, name, run_id, data_dict, job_type='Training'):
self.data_dict = self.setup_training(opt, data_dict)
if self.job_type == 'Dataset Creation':
self.data_dict = self.check_and_upload_dataset(opt)
else:
print(f"{colorstr('wandb: ')}Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)")


def check_and_upload_dataset(self, opt):
assert wandb, 'Install wandb to upload dataset'
Expand Down