Since DistilBERT is an encoder-based model, its configuration inherits from
OnnxConfig:
```python
from typing import Mapping, OrderedDict
from transformers.onnx import OnnxConfig
class DistilBertOnnxConfig(OnnxConfig):
...     @property
...     def inputs(self) -> Mapping[str, Mapping[int, str]]:
...         return OrderedDict(
...             [
...                 ("input_ids", {0: "batch", 1: "sequence"}),
...                 ("attention_mask", {0: "batch", 1: "sequence"}),
...             ]
...         )
```
Every configuration object must implement the inputs property and return a
mapping, where each key corresponds to an expected input, and each value
indicates the axis of that input. For DistilBERT, we can see that two inputs are
required: input_ids and attention_mask. These inputs have the same shape of
