DataCollatorForWholeWordMask is missing _tensorize_batch method
## Environment info
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- `transformers` version: 3.4.0
- Platform: Google Colab
- Python version: 3.6
- PyTorch version (GPU?): Yes
- Tensorflow version (GPU?):
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
 @sgugger 
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 Summarization: @sshleifer
 TextGeneration: @TevenLeScao 
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 nlp datasets: [different repo](https://github.com/huggingface/nlp)
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## Information

Model I am using (Bert, XLNet ...):BERT

The problem arises when using: 
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

Not sure if it's considered official, but it's just finetuning for language modeling on a custom dataset. 
## To reproduce

Steps to reproduce the behavior:
```python
from transformers import DataCollatorForWholeWordMask
from transformers import Trainer, TrainingArguments
from transformers import TextDataset
from transformers import BertTokenizer
from transformers import BertForMaskedLM

tokenizer = BertTokenizer.from_pretrained('bert-large-uncased-whole-word-masking')
tokenizer.add_tokens(["[new]"])
model = BertForMaskedLM.from_pretrained('bert-large-uncased-whole-word-masking')
model.resize_token_embeddings(len(tokenizer)) 

model.train()
dataset = TextDataset(
      tokenizer=tokenizer,
      file_path="./bert_train_set.txt",
      block_size=512
  )
data_collator = DataCollatorForWholeWordMask(
    tokenizer
)

training_args = TrainingArguments(
    output_dir="./BERT",
    overwrite_output_dir=True,
    num_train_epochs=10,
    per_gpu_train_batch_size=16,
    save_steps=500,
    save_total_limit=2,
    learning_rate = 2e-5
)

trainer = Trainer(
    model=model,
    args=training_args,
    data_collator=data_collator,
    train_dataset=dataset,
    prediction_loss_only=True,
)
trainer.train()
```
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```
/usr/local/lib/python3.6/dist-packages/transformers/data/data_collator.py in __call__(self, examples)
    316             examples = [{"input_ids": e} for e in examples]
    317 
--> 318         batch_input = self._tensorize_batch(input_ids)
    319 
    320         mask_labels = []

AttributeError: 'DataCollatorForWholeWordMask' object has no attribute '_tensorize_batch'
```
## Expected behavior

Trainer should proceed to feed tensors to the model. I think someone just forgot to copypaste _tensorize_batch from DataCollatorForPermutationLanguageModeling, either that or inheritance is off.
@RedneckedCrake Hey please checkout my PR and let me know if it works!<|||||>Should be fixed by #8379, thanks for flagging this!