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[rank0]: Traceback (most recent call last):
[rank0]: File "/kaggle/input/donut1/donut/train.py", line 173, in
[rank0]: train(config)
[rank0]: File "/kaggle/input/donut1/donut/train.py", line 157, in train
[rank0]: trainer.fit(model_module, data_module, ckpt_path=config.get("resume_from_checkpoint_path", None))
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 538, in fit
[rank0]: call._call_and_handle_interrupt(
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 46, in _call_and_handle_interrupt
[rank0]: return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch
[rank0]: return function(*args, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 574, in _fit_impl
[rank0]: self._run(model, ckpt_path=ckpt_path)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 981, in _run
[rank0]: results = self._run_stage()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1025, in _run_stage
[rank0]: self.fit_loop.run()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py", line 205, in run
[rank0]: self.advance()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py", line 363, in advance
[rank0]: self.epoch_loop.run(self._data_fetcher)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 141, in run
[rank0]: self.on_advance_end(data_fetcher)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 295, in on_advance_end
[rank0]: self.val_loop.run()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/utilities.py", line 178, in _decorator
[rank0]: return loop_run(self, *args, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 142, in run
[rank0]: return self.on_run_end()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 254, in on_run_end
[rank0]: self._on_evaluation_epoch_end()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 334, in _on_evaluation_epoch_end
[rank0]: call._call_lightning_module_hook(trainer, hook_name)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 167, in _call_lightning_module_hook
[rank0]: output = fn(*args, **kwargs)
[rank0]: File "/kaggle/input/donut1/donut/lightning_module.py", line 112, in on_validation_epoch_end
[rank0]: val_metric[i] = total_metric[i] / cnt[i]
[rank0]: ZeroDivisionError: division by zero
Epoch 0: 100%|██████████| 1437/1437 [24:26<00:00, 0.98it/s, loss=0.000102, exp_name=train_rvlcdip, exp_version=test_experiment]
The text was updated successfully, but these errors were encountered:
[rank0]: Traceback (most recent call last):
[rank0]: File "/kaggle/input/donut1/donut/train.py", line 173, in
[rank0]: train(config)
[rank0]: File "/kaggle/input/donut1/donut/train.py", line 157, in train
[rank0]: trainer.fit(model_module, data_module, ckpt_path=config.get("resume_from_checkpoint_path", None))
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 538, in fit
[rank0]: call._call_and_handle_interrupt(
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 46, in _call_and_handle_interrupt
[rank0]: return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch
[rank0]: return function(*args, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 574, in _fit_impl
[rank0]: self._run(model, ckpt_path=ckpt_path)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 981, in _run
[rank0]: results = self._run_stage()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1025, in _run_stage
[rank0]: self.fit_loop.run()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py", line 205, in run
[rank0]: self.advance()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py", line 363, in advance
[rank0]: self.epoch_loop.run(self._data_fetcher)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 141, in run
[rank0]: self.on_advance_end(data_fetcher)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 295, in on_advance_end
[rank0]: self.val_loop.run()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/utilities.py", line 178, in _decorator
[rank0]: return loop_run(self, *args, **kwargs)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 142, in run
[rank0]: return self.on_run_end()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 254, in on_run_end
[rank0]: self._on_evaluation_epoch_end()
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 334, in _on_evaluation_epoch_end
[rank0]: call._call_lightning_module_hook(trainer, hook_name)
[rank0]: File "/opt/conda/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 167, in _call_lightning_module_hook
[rank0]: output = fn(*args, **kwargs)
[rank0]: File "/kaggle/input/donut1/donut/lightning_module.py", line 112, in on_validation_epoch_end
[rank0]: val_metric[i] = total_metric[i] / cnt[i]
[rank0]: ZeroDivisionError: division by zero
Epoch 0: 100%|██████████| 1437/1437 [24:26<00:00, 0.98it/s, loss=0.000102, exp_name=train_rvlcdip, exp_version=test_experiment]
The text was updated successfully, but these errors were encountered: