Attention Mask for TFXLM Model doesn't work
# 🐛 Bug

## Information

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

Language I am using the model on (English, Chinese ...): English

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

## To reproduce

Steps to reproduce the behavior:

```
from transformers import *
tokenizer = XLMTokenizer.from_pretrained('xlm-mlm-enfr-1024')
model = TFXLMModel.from_pretrained('xlm-mlm-enfr-1024')
text = "Good evening."
input_ids = tokenizer.encode(text, add_special_tokens=True)
last_hidden_states = model(np.array([input_ids]), attention_mask=np.ones_like(np.array(input_ids)))
```

Error output:
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py", line 822, in __call__
    outputs = self.call(cast_inputs, *args, **kwargs)
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/transformers/modeling_tf_xlm.py", line 589, in call
    outputs = self.transformer(inputs, **kwargs)
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py", line 822, in __call__
    outputs = self.call(cast_inputs, *args, **kwargs)
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/transformers/modeling_tf_xlm.py", line 348, in call
    mask, attn_mask = get_masks(slen, lengths, self.causal, padding_mask=attention_mask)
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/transformers/modeling_tf_xlm.py", line 88, in get_masks
    tf.debugging.assert_equal(shape_list(mask), [bs, slen])
  File "/Users/daksh/miniconda3/envs/rasa-tf2/lib/python3.6/site-packages/transformers/modeling_tf_utils.py", line 546, in shape_list
    static = x.shape.as_list()
AttributeError: 'tuple' object has no attribute 'as_list'
```

Works fine if I attention mask is removed

## Expected behavior
`last_hidden_states` is a tuple of type `tf.Tensor`

## Environment info
     
- `transformers` version: 2.3.0
- Platform: OSX
- Python version: 3.6.5
- Tensorflow version (GPU?): 2.1.0(CPU)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

Hi! There seems to be an error in the current implementation where it doesn't accept NumPy arrays, only TensorFlow arrays. I'm working on it in [the branch fix-tf-xlm](https://github.com/huggingface/transformers/tree/fix-tf-xlm). In the meantime, you can use a tf.Tensor instead and it should work fine.

Please be aware that your attention mask should be defined as `np.ones_like(np.array([input_ids]))` instead of your current `np.ones_like(np.array(input_ids))` or else it'll be a dimension short.

The following code is your code modified to run:

```py
from transformers import *
import numpy as np
import tensorflow as tf

tokenizer = XLMTokenizer.from_pretrained('xlm-mlm-enfr-1024')
model = TFXLMModel.from_pretrained('xlm-mlm-enfr-1024')
text = "Good evening."
input_ids = tokenizer.encode(text, add_special_tokens=True)
last_hidden_states = model(np.array([input_ids]), attention_mask=tf.constant(np.ones_like(np.array([input_ids]))))

```<|||||>Hi @LysandreJik When can we expect your fix to be merged and released in an official release?<|||||>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.
<|||||>Hi, is this bug now fixed? 
Thanks!