Problem while using tokenizer.encode_plus for sentence pairs
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## Details
Hi, thanks for this great work.
I was trying to use tokenizer.encode_plus to encode sentence pairs. The code looks like

```py
training_encoded_dict = tokenizer.encode_plus(
            seq0,
            seq1,
            add_spicial_tokens = True,
            max_length = 256,
            truncation_strategy = 'only_second',
            pad_to_max_length = True,
            return_attention_mask = True,
            return_token_type_ids = True,
            return_tensors = 'pt',

        )
```

However, the problem looks like
```
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-17-ae3ce93d62ba> in <module>()
     24             return_attention_mask = True,
     25             return_token_type_ids = True,
---> 26             return_tensors = 'pt',
     27 
     28         )

2 frames
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils.py in truncate_sequences(self, ids, pair_ids, num_tokens_to_remove, truncation_strategy, stride)
   2068             ids = ids[:-num_tokens_to_remove]
   2069         elif truncation_strategy == "only_second":
-> 2070             assert pair_ids is not None and len(pair_ids) > num_tokens_to_remove
   2071             window_len = min(len(pair_ids), stride + num_tokens_to_remove)
   2072             overflowing_tokens = pair_ids[-window_len:]

AssertionError: 
```

This issue doesn't occur while using truncation_strategy = 'longest_first', and it happens with other truncation_strategy such as 'only_second' and 'only_first'.
I was wondering does anyone have the same issue or have any idea about how to fix it? Thanks a lot in advance.
**A link to original question on the forum/Stack Overflow**:
Could you provide some `seq0` and `seq1` values so that we may investigate further?<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
