question: cannot assign 'int' as child module 'precision' (torch.nn.Module or None expected) Error
context: I am trying to run trainer.fit with only models passed. However, I am getting the following error.
  Traceback (most recent call last):
    File "train.py", line 116, in <module>
      main_func(args)
    File "train.py", line 55, in main_func
      trainer.fit(model, train_dataloader=train_dataloader, val_dataloaders=val_dataloader)
    File "/netscratch/gsingh/EVN/Anaconda/envs/lighting_neptune/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 443, in fit
      self.model_connector.copy_trainer_model_properties(model)
    File "/netscratch/gsingh/EVN/Anaconda/envs/lighting_neptune/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/model_connector.py", line 39, in copy_trainer_model_properties
      m.precision = self.trainer.precision
    File "/netscratch/gsingh/EVN/Anaconda/envs/lighting_neptune/lib/python3.8/site-packages/torch/nn/modules/module.py", line 982, in __setattr__
      raise TypeError("cannot assign '{}' as child module '{}' "
  TypeError: cannot assign 'int' as child module 'precision' (torch.nn.Module or None expected)
  
  I am unable to figure this out. Any help would be appreciated
      trainer = Trainer(
          logger=logger, resume_from_checkpoint=args.resume_from_checkpoint, max_epochs=args.num_epochs,
          accumulate_grad_batches=args.gradient_accumulation_steps, 
          default_root_dir=args.experiment_path, checkpoint_callback=ckpt, num_sanity_val_steps=args.num_sanity_val_steps, 
          gradient_clip_val=args.gradient_clip_val, gpus=1, auto_select_gpus=True, sync_batchnorm=args.sync_batchnorm
      )
                          
      criterion = torch.nn.CrossEntropyLoss()
      criterion_val = torch.nn.CrossEntropyLoss()
      
      model = Model(args, tr_dl=train_dataloader, val_dl=val_dataloader, test_dl=test_dataloader, criterion=criterion, criterion_val=criterion_val)
      trainer.fit(model)
  Here precision value is the default.
  Thank You
answer: Do you have any properties in your Model class named precision ?