Improve wandb logging
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0604060580
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@ -84,7 +84,8 @@ class Trainer:
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if opt['wandb'] and self.rank <= 0:
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import wandb
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os.makedirs(os.path.join(opt['path']['log'], 'wandb'), exist_ok=True)
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wandb.init(project=opt['name'], dir=opt['path']['log'])
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project_name = opt_get(opt, ['wandb_project_name'], opt['name'])
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wandb.init(project=project_name, dir=opt['path']['log'], config=opt)
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#### random seed
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seed = opt['train']['manual_seed']
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@ -203,7 +204,7 @@ class Trainer:
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self.tb_logger.add_scalar(k, v, self.current_step)
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if opt['wandb'] and self.rank <= 0:
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import wandb
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wandb.log(logs)
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wandb.log(logs, step=self.current_step)
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self.logger.info(message)
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#### save models and training states
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@ -284,7 +285,7 @@ class Trainer:
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if __name__ == '__main__':
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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_gpt_asr_mass_hf.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_gpt_asr_mass_hf2.yml')
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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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args = parser.parse_args()
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