Creating a stable learn.train_dl for text classification class

Hi everyone,

I need to create a databunch for text classfication which has a stable train dataloader.
After reading the documentation for the fastai library, I made the following changes


class CustomTextClasDataBunch(TextDataBunch):
   "Create a `TextDataBunch` suitable for training an RNN classifier."
   def create(cls, train_ds, valid_ds, test_ds=None, path:PathOrStr='.', bs:int=32, val_bs:int=None, pad_idx=1,
           pad_first=True, device:torch.device=None, no_check:bool=False, backwards:bool=False, 
           dl_tfms:Optional[Collection[Callable]]=None, **dl_kwargs) -> DataBunch:
       "Function that transform the `datasets` in a `DataBunch` for classification. Passes `**dl_kwargs` on to `DataLoader()`"
       datasets = cls._init_ds(train_ds, valid_ds, test_ds)
       val_bs = ifnone(val_bs, bs)
       collate_fn = partial(pad_collate, pad_idx=pad_idx, pad_first=pad_first, backwards=backwards)
       train_dl = DataLoader(datasets[0], batch_size=bs, shuffle=False, **dl_kwargs)
       dataloaders = [train_dl]
       for ds in datasets[1:]:
           lengths = [len(t) for t in ds.x.items]
           sampler = SortSampler(ds.x, key=lengths.__getitem__)
           dataloaders.append(DataLoader(ds, batch_size=val_bs, sampler=sampler, **dl_kwargs))
       return cls(*dataloaders, path=path, device=device, dl_tfms=dl_tfms, collate_fn=None, no_check=no_check)

data_clas = CustomTextClasDataBunch.from_df(dataset_location, train_df=df_train, valid_df=df_dev, test_df=df_test, vocab=data_lm.train_ds.vocab, bs=bs)

learn = text_classifier_learner(data_clas, AWD_LSTM, drop_mult=0.5) =, num_workers=0)

I hoped this would do the work, but test cases for this are failing. Everytime I print the first batch, entries are different.

Can anyone point out the error and tell me how to do it?