Add dummy_inputs for pytorch_version of vision_models
Author: kolonist-minjun
Pull request: yes

# What does this PR do?
```
from transformers import ViTForImageClassification
from transformers.utils.fx import symbolic_trace

model = ViTForImageClassification.from_pretrained("google/vit-base-patch16-224")
traced = symbolic_trace(model)
```
```
Traceback (most recent call last):
  File "bug_check.py", line 5, in <module>
    traced = symbolic_trace(model)
  File "/opt/conda/lib/python3.8/site-packages/transformers/utils/fx.py", line 1214, in symbolic_trace
    concrete_args = get_concrete_args(model, input_names)
  File "/opt/conda/lib/python3.8/site-packages/transformers/utils/fx.py", line 1167, in get_concrete_args
    raise ValueError(
ValueError: The model does not have input(s) named: input_ids, expected a subset of the following: pixel_values, head_mask, labels, output_attentions, output_hidden_states, interpolate_pos_encoding, return_dict
```
When using transformers.utils.fx.symbolic_trace,
the pytorch version of vision models throws an error. This is because the default setting of dummy_inputs is "input_ids".

It doesn't matter in TEXT MODELS,
but this problem occurs because
VISION MODELS requires "pixel_values" as a base.

Added dummy_inputs to several PyTorch version models by referring to the dummy_inputs of the Tensorflow version model.

This change fixes the
convnext, convnextv2, resnet, segformer, vit, and vit_hybrid models.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@amyeroberts 

Comments:
Hi @kolonist-minjun, thanks for opening this PR! 

The `dummy_inputs` is a legacy property of the pretrained models and not one we're actively supporting. To use `symbolic_trace`, you can directly pass in the input names: 

```py
from transformers import ViTForImageClassification
from transformers.utils.fx import symbolic_trace

model = ViTForImageClassification.from_pretrained("google/vit-base-patch16-224")
traced = symbolic_trace(model, input_names=['pixel_values'])
```

Hi @amyeroberts, thanks for the comment!
The TF version models have dummy_inputs, so I thought it would be good to have them in the PyTorch version models for unification.

@kolonist-minjun Yes, it's a bit confusing considering some PyTorch models also have `dummy_inputs` implemented - hopefully once fully deprecated and removed it'll be clearer. We have `dummy_inputs` for the TF models, because Keras models have to be built in order to load pretrained weights. 

@amyeroberts Thank you for your comment. I will close this PR!