MisconfigurationException: `train_dataloader` must be implemented to be used with the Lightning Trainer

[antitheos]

i am trying to run train a model using the following command python train.py --model_name RN50 --folder ArchDaily --batch_size 512 --accelerator cuda

i get the above error: _File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/core/hooks.py", line 485, in train_dataloader raise MisconfigurationException("train_dataloader must be implemented to be used with the Lightning Trainer") pytorch_lightning.utilities.exceptions.MisconfigurationException: train_dataloader must be implemented to be used with the Lightning Trainer_

grateful for any assistance

and here is full messages log

Using 16bit native Automatic Mixed Precision (AMP) GPU available: True (cuda), used: True TPU available: False, using: 0 TPU cores IPU available: False, using: 0 IPUs HPU available: False, using: 0 HPUs /usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/configuration_validator.py:119: PossibleUserWarning: You defined a validation_step but have no val_dataloader. Skipping val loop. category=PossibleUserWarning, LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] Traceback (most recent call last): File "train.py", line 31, in main(args) File "train.py", line 20, in main trainer.fit(model, dm) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 701, in fit self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 654, in _call_and_handle_interrupt return trainer_fn(*args, *kwargs) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 741, in _fit_impl results = self._run(model, ckpt_path=self.ckpt_path) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 1147, in _run self.strategy.setup(self) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/strategies/single_device.py", line 74, in setup super().setup(trainer) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/strategies/strategy.py", line 153, in setup self.setup_optimizers(trainer) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/strategies/strategy.py", line 142, in setup_optimizers self.lightning_module File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/core/optimizer.py", line 179, in _init_optimizers_and_lr_schedulers optim_conf = model.trainer._call_lightning_module_hook("configure_optimizers", pl_module=model) File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 1549, in _call_lightning_module_hook output = fn(args, kwargs) File "/content/train-CLIP/models/wrapper.py", line 146, in configure_optimizers first_cycle_steps=self.num_training_steps, File "/content/train-CLIP/models/wrapper.py", line 38, in num_training_steps dataset = self.train_dataloader() File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/core/hooks.py", line 485, in train_dataloader raise MisconfigurationException("train_dataloader must be implemented to be used with the Lightning Trainer") pytorch_lightning.utilities.exceptions.MisconfigurationException: train_dataloader must be implemented to be used with the Lightning Trainer**

[ZachData]

I had the same issue. It looks like the num_training_steps function can't access the DataLoader for some reason. I circumvented the problem by explicitly returning the data length and data batch size in the setup function to plug them into num_training_steps.

[kyunghoyu]

I soved this problem. I downgraded the pytorch-lightning version. my pytorch-lightning version is 1.4.9

[tyjiao123]

you can change wrapper.py. dataset = self.train_dataloader() to dataset = self.trainer.datamodule.train_dataloader()