Turn attentions and hidden-states into a tensor
# What does this PR do?

This PR turns the `all_attentions` and `all_hidden_states` values into tensors instead of a tuple. This update is to properly allow the dict outputs in TF serving, because the value of each key cannot be something else than a TF tensor.

Here a simple piece of code to produce the issue:
```
from transformers import TFBertModel, BertConfig
import tensorflow as tf
config = BertConfig.from_pretrained("bert-base-cased", output_attentions=True)
model = TFBertModel.from_pretrained("bert-base-cased", config=config)
tf.saved_model.save(model, "my_model")
```

Gets the error:
```
ValueError: Got a dictionary containing non-Tensor value (<tf.Tensor 'StatefulPartitionedCall:0' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:1' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:2' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:3' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:4' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:5' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:6' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:7' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:8' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:9' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:10' shape=(None, 12, None, None) dtype=float32>, <tf.Tensor 'StatefulPartitionedCall:11' shape=(None, 12, None, None) dtype=float32>) for key attentions in the output of the function __inference_serving_15889 used to generate a SavedModel signature. Dictionaries outputs for functions used as signatures should have one Tensor output per string key.
```
After an offline discussion we decided to proceed differently. Then closing this PR.