modify logger, add logger_set level #467
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Songyuanwei
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| from mindocr.utils.visualize import recover_image | ||
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| logger = logging.getLogger("mindocr") |
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有些是 _logger， 有些是logger，保持一致会比较好
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主脚本用的是logger,例如train.py, eval.py等，其余调用的脚本用的_logger
tools/modelarts_adapter/modelarts.py
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不建议在modelarts.py 使用logger，因为modelart 会比 mindocr 先import，然后在modelart装必须的package等等再import mindocr。如果在这里预先import mindocr会出module missing等问题
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这里没有调用mindocr,之前调用的现在去掉了
| @@ -152,7 +146,7 @@ def on_train_step_end(self, run_context): | |||
| f"loss: {loss:.6f}, " + lr_str + f"per step time: {per_step_time:.3f} ms, fps: {fps:.2f} img/s" | |||
| ) | |||
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这里要加个if main_rank 保护，否则distributed training message会重复出现
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我试过了，分布式之后0卡打印，在logger.py文件设置了，只有0卡打印，然后main.py调用会全局生效。
| from mindocr.utils.logger import Logger | ||
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| _logger = Logger("mindocr") | ||
| _logger = logging.getLogger("mindocr") |
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_logger = logging.getLogger(__name__)?
| @@ -33,30 +36,26 @@ def main(cfg): | |||
| parallel_mode="data_parallel", | |||
| gradients_mean=True, | |||
| ) | |||
| set_logger( | |||
| name="mindocr", output_dir=cfg.train.ckpt_save_dir or "./", log_fn=f"log_eval_{rank_id}.txt", rank=rank_id | |||
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The name of logger here (mindocr) is different form initialized above (mindocr.eval)
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