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Fix batch-size on resume for multi-gpu (#1942)

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NanoCode012 2021-01-15 00:53:13 +07:00 committed by GitHub
parent b75c432ea0
commit 3a56cac414
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1 changed files with 1 additions and 1 deletions
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train.py
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@ -477,7 +477,7 @@ if __name__ == '__main__':
apriori = opt.global_rank, opt.local_rank apriori = opt.global_rank, opt.local_rank
with open(Path(ckpt).parent.parent / 'opt.yaml') as f: with open(Path(ckpt).parent.parent / 'opt.yaml') as f:
opt = argparse.Namespace(**yaml.load(f, Loader=yaml.FullLoader)) # replace opt = argparse.Namespace(**yaml.load(f, Loader=yaml.FullLoader)) # replace
opt.cfg, opt.weights, opt.resume, opt.global_rank, opt.local_rank = '', ckpt, True, *apriori # reinstate opt.cfg, opt.weights, opt.resume, opt.batch_size, opt.global_rank, opt.local_rank = '', ckpt, True, opt.total_batch_size, *apriori # reinstate
logger.info('Resuming training from %s' % ckpt) logger.info('Resuming training from %s' % ckpt)
else: else:
# opt.hyp = opt.hyp or ('hyp.finetune.yaml' if opt.weights else 'hyp.scratch.yaml') # opt.hyp = opt.hyp or ('hyp.finetune.yaml' if opt.weights else 'hyp.scratch.yaml')