Issue while using DPR with tensorflow and py torch
Author: MaheshChandrra
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.6.1
- Platform:Windows
- Python version:3.6
- PyTorch version (GPU?No):1.7.0
- Tensorflow version (GPU? No):2.3.1
- Using GPU in script?:No
- Using distributed or parallel set-up in script?:No

### Who can help
Hi @LysandreJik , @Rocketknight1 ,@patrickvonplaten, @lhoestq ,@sgugger

I'm trying the basic example mentioned in the DPR documentation but facing the below issue,
can you please help me,and can you please let me know using what functionality I can get the answer for a given question to the provided text, as `relevance_logits` is just giving a number which I'm not understanding the significance.

Thanks you all!!

```
#########################################################################

##Using **pt** as return tensors
from transformers import DPRReader, DPRReaderTokenizer
tokenizer = DPRReaderTokenizer.from_pretrained('facebook/dpr-reader-single-nq-base')
model = DPRReader.from_pretrained('facebook/dpr-reader-single-nq-base')
encoded_inputs = tokenizer(
     questions=["What is love ?"],
     titles=["Haddaway"],
     texts=["'What Is Love' is a song recorded by the artist Haddaway"],
     return_tensors='pt'
 )
outputs = model(**encoded_inputs)
start_logits = outputs.stat_logits
end_logits = outputs.end_logits
relevance_logits = outputs.relevance_logits
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-1-86e12c26a869> in <module>
      9  )
     10 outputs = model(**encoded_inputs)
---> 11 start_logits = outputs.stat_logits
     12 end_logits = outputs.end_logits
     13 relevance_logits = outputs.relevance_logits

AttributeError: 'DPRReaderOutput' object has no attribute 'stat_logits' 

#########################################################################

##Using tf as return_tensors
from transformers import DPRReader, DPRReaderTokenizer
tokenizer = DPRReaderTokenizer.from_pretrained('facebook/dpr-reader-single-nq-base')
model = DPRReader.from_pretrained('facebook/dpr-reader-single-nq-base')
encoded_inputs = tokenizer(
     questions=["What is love ?"],
     titles=["Haddaway"],
     texts=["'What Is Love' is a song recorded by the artist Haddaway"],
     return_tensors='tf'
 )
outputs = model(**encoded_inputs)
start_logits = outputs.stat_logits
end_logits = outputs.end_logits
relevance_logits = outputs.relevance_logits

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-6-6f88caac8403> in <module>
      8      return_tensors='tf'
      9  )
---> 10 outputs = model(**encoded_inputs)
     11 start_logits = outputs.stat_logits
     12 end_logits = outputs.end_logits

~\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

~\Anaconda3\lib\site-packages\transformers\models\dpr\modeling_dpr.py in forward(self, input_ids, attention_mask, inputs_embeds, output_attentions, output_hidden_states, return_dict)
    641             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
    642         elif input_ids is not None:
--> 643             input_shape = input_ids.size()
    644         elif inputs_embeds is not None:
    645             input_shape = inputs_embeds.size()[:-1]

AttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no attribute 'size'

```




Comments:
Hey @MaheshChandrra, 

It seems like there is a type as it should be called `outputs.start_logits` instead of `outputs.stat_logits`. Would you like to open a PR to fix it? :-)

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