Trainer can't estimate SpeechEncoderDecoder tokens for `floating_point_ops`
## 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: 4.16.2
- Platform: Ubuntu
- Python version: 3.7
- PyTorch version (GPU?): 1.9
- Tensorflow version (GPU?): NA
- Using GPU in script?: Y
- Using distributed or parallel set-up in script?: N

### Who can help
Maybe @sgugger?

## Information

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

Training the model results in `Could not estimate the number of tokens of the input, floating-point operations will not be computed` warnings due to [this function](https://github.com/huggingface/transformers/blob/240cc6cbdc07fc1a7c103d71cfe38d5e60e489e4/src/transformers/modeling_utils.py#L378) being unable to find the correct `self.main_input_name`. For `SpeechEncoderDecoderModel`s, the default name is [`inputs` ](https://github.com/huggingface/transformers/blob/v4.16.2/src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py#L183) even though the encoder should either accept `input_values` or `input_features`. The function expects `inputs` to be in the `input_dict` but could only find the main input name of the encoder.

## To reproduce

Steps to reproduce the behavior:

1. Train a `SpeechEncoderDecoderModel` using the `Seq2SeqTrainer` and monitor console output.

## Expected behavior

The function should be able to determine the correct `main_input_name` of a `SpeechEncoderDecoderModel`. Presumably that of the encoder. I'm not sure if this applies to `VisionEncoderDecoderModel`s but I suspect it would.

I don't think this can be solved since the model input name is not always the same. You can just ignore the warning.

cc @patrickvonplaten for the model input name, to see if there is a way to fix it.<|||||>@OllieBroadhurst, 

I think we could solve this if we rename `input_values` to `inputs` in the speech-encoder-decoder training script here: https://github.com/huggingface/transformers/blob/2f2fefd6afa496ea72312ff38686706717f8aa22/examples/pytorch/speech-recognition/run_speech_recognition_seq2seq.py#L197 

Could you try this out? Think this is the cleanest way of solving it<|||||>cc @sanchit-gandhi <|||||>Nice idea @patrickvonplaten! I have my own collate function anyway so it's a simple change. Of course you'll be changing `input_features` to `inputs` if you're using `Speech2Text` (as opposed to `input_values`).

