forked from mrq/DL-Art-School
Add wandb_step_factor argument
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@ -210,7 +210,7 @@ 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, step=self.current_step)
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wandb.log(logs, step=int(self.current_step * opt_get(opt, ['wandb_step_factor'], 1)))
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self.logger.info(message)
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#### save models and training states
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