typeerror: textinputsequence must be str
## Describe the bug
I use dataset.map() to encode the data, but get this problem.

#   I use the code to transfer data to local csv files,.As i use colab, local files are more convenient.

dataset = load_dataset(path='glue', name='mnli')
keys = ['train', 'validation_matched','validation_mismatched']
for k in keys:
  result = []
  for record in dataset[k]:
    c1, c2, c3 = record['premise'], record['hypothesis'], record['label']
    if c1 and c2 and c3 in {0,1,2}:
      result.append(c1,c2,c3))
  result = pd.DataFrame(result, columns=['premise','hypothesis','label'])
  result.to_csv('mnli_'+k+'.csv',index=False)

# then I process data like this ,and get the issue.
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)

def encode(batch):
  return tokenizer(batch['premise'], 
           batch['hypothesis'],
           max_length=MAXLEN,
           padding='max_length',
           truncation=True
           )

train_dict = load_dataset('csv', data_files=train_data_path)
train_dataset = train_dict['train']
train_dataset = train_dataset.map(encode, batched=True)


## Expected results
encode the data successfully.

## Actual results
TypeError                                 Traceback (most recent call last)
<ipython-input-19-00acc2cded49> in <module>()
      5 val_dataset = val_dict['train']
      6 
----> 7 train_dataset = train_dataset.map(encode, batched=True)
      8 val_dataset = val_dataset.map(encode, batched=True)
      9 

/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
   1680                 new_fingerprint=new_fingerprint,
   1681                 disable_tqdm=disable_tqdm,
-> 1682                 desc=desc,
   1683             )
   1684         else:

/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
    183         }
    184         # apply actual function
--> 185         out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
    186         datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
    187         # re-apply format to the output

/usr/local/lib/python3.7/dist-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
    395             # Call actual function
    396 
--> 397             out = func(self, *args, **kwargs)
    398 
    399             # Update fingerprint of in-place transforms + update in-place history of transforms

/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc)
   2018                                 indices,
   2019                                 check_same_num_examples=len(input_dataset.list_indexes()) > 0,
-> 2020                                 offset=offset,
   2021                             )
   2022                         except NumExamplesMismatch:

/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples, offset)
   1904                 effective_indices = [i + offset for i in indices] if isinstance(indices, list) else indices + offset
   1905             processed_inputs = (
-> 1906                 function(*fn_args, effective_indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
   1907             )
   1908             if update_data is None:

<ipython-input-11-3dad555201d4> in encode(batch)
      6            max_length=MAXLEN,
      7            padding='max_length',
----> 8            truncation=True
      9            )

/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_base.py in __call__(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
   2383                 return_length=return_length,
   2384                 verbose=verbose,
-> 2385                 **kwargs,
   2386             )
   2387         else:

/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_base.py in batch_encode_plus(self, batch_text_or_text_pairs, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
   2568             return_length=return_length,
   2569             verbose=verbose,
-> 2570             **kwargs,
   2571         )
   2572 

/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_fast.py in _batch_encode_plus(self, batch_text_or_text_pairs, add_special_tokens, padding_strategy, truncation_strategy, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose)
    406             batch_text_or_text_pairs,
    407             add_special_tokens=add_special_tokens,
--> 408             is_pretokenized=is_split_into_words,
    409         )
    410 

TypeError: TextInputSequence must be str

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:1.11.0
- Platform:colab
- Python version:3.7
- PyArrow version:
@lhoestq 
by the way ,the same code works when i process the xnli dataset.<|||||>Hi @justwangqian,

I think your issue is with the `transformers` library. I guess you should update it, but I prefer transferring your issue to them, so that they can keep the record.

Feel free to reopen an issue in `datasets` if there is finally a bug here. :)<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.