Add dummy_inputs for pytorch_version of vision_models
# 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.

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@amyeroberts 
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!