Prompt user for gpu_id if multiple gpus are detected
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@ -32,7 +32,7 @@ def init_dist(backend='nccl', **kwargs):
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def main():
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def main():
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#### options
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#### options
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_exd_imgset_spsr7_multiloss.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_exd_imgset_ssgr.yml')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
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parser.add_argument('--local_rank', type=int, default=0)
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parser.add_argument('--local_rank', type=int, default=0)
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args = parser.parse_args()
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args = parser.parse_args()
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@ -61,6 +61,12 @@ def main():
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opt['dist'] = False
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opt['dist'] = False
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rank = -1
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rank = -1
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print('Disabled distributed training.')
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print('Disabled distributed training.')
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if torch.cuda.device_count() > 1:
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gpu = input('I noticed you have multiple GPUs. Starting two jobs on the same GPU sucks. Please confirm which GPU'
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'you want to use. Press enter to use the specified one [%i]' % (opt['gpu_ids']))
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if gpu:
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opt['gpu_ids'] = [int(gpu)]
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else:
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else:
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opt['dist'] = True
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opt['dist'] = True
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init_dist()
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init_dist()
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