convert_graph_to_onnx.py failing to run on Wav2Vec2 models
Author: hrahamim
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: Linux-4.15.0-143-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>


## Information

Model I am using (Bert, XLNet ...): facebook/wav2vec2-large-960h

The problem arises when using:

* [X ] the official example scripts: (give details below)
I am trying the next command:
python transformers/src/transformers/convert_graph_to_onnx.py --framework pt --quantize --model facebook/wav2vec2-large-960h wav2vec2_convert.onnx

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

run:
python transformers/src/transformers/convert_graph_to_onnx.py --framework pt --quantize --model facebook/wav2vec2-large-960h wav2vec2_convert.onnx

I get the next error:

python transformers/src/transformers/convert_graph_to_onnx.py --framework pt --quantize --model facebook/wav2vec2-large-960h wav2vec2_convert.onnx
/home/ptuser/anaconda3/envs/gong_env/lib/python3.6/site-packages/torchaudio/backend/utils.py:54: UserWarning: "sox" backend is being deprecated. The default backend will be changed to "sox_io" backend in 0.8.0 and "sox" backend will be removed in 0.9.0. Please migrate to "sox_io" backend. Please refer to https://github.com/pytorch/audio/issues/903 for the detail.
  '"sox" backend is being deprecated. '

====== Converting model to ONNX ======
ONNX opset version set to: 11
Loading pipeline (model: facebook/wav2vec2-large-960h, tokenizer: facebook/wav2vec2-large-960h)
Some weights of the model checkpoint at facebook/wav2vec2-large-960h were not used when initializing Wav2Vec2Model: ['lm_head.bias', 'lm_head.weight']
- This IS expected if you are initializing Wav2Vec2Model from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing Wav2Vec2Model from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of Wav2Vec2Model were not initialized from the model checkpoint at facebook/wav2vec2-large-960h and are newly initialized: ['wav2vec2.masked_spec_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Error while converting the model: __init__() got an unexpected keyword argument 'feature_extractor'

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->


Comments:
Hi, Wav2Vec2 is not supported by the ONNX converter. Please check out the following PR which offers the possibility to convert existing models to ONNX by defining an architecture: https://github.com/huggingface/transformers/pull/11786. You can see the docs (WIP) for that PR [here](https://235542-155220641-gh.circle-artifacts.com/0/docs/_build/html/serialization.html).

Will be happy if Wav2Vec2 will be supported in the future...

Think someone solved it here: https://github.com/huggingface/transformers/issues/10004

Thanks Patrick