🚨 Fix ViT image processor default interpolation to BICUBIC

[raimbekovm]

Summary

The original Vision Transformer implementation uses BICUBIC interpolation for image preprocessing, but the HuggingFace image processor defaulted to BILINEAR. This PR aligns the default with the original implementation.

Changes

• Update default resample from BILINEAR to BICUBIC in ViTImageProcessor
• Update default resample in ViTImageProcessorFast
• Update docstrings to reflect BICUBIC as the default

Reference

• TIMM (PyTorch Image Models) uses bicubic for ViT: https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/vision_transformer.py
• This is a breaking change as it modifies default preprocessing behavior

Related Issue

Fixes part of #28180

Testing

• Syntax validation passed
• Changes follow the same pattern as the recent ConvNeXt fix (🚨 Fix ConvNeXt image processor default interpolation to BICUBIC #42934)

[github-actions]

[For maintainers] Suggested jobs to run (before merge)

run-slow: efficientnet, imagegpt, layoutlmv2, layoutlmv3, pvt, segformer, vit

[raimbekovm]

Quick clarification on the file changes:

The second commit updates 6 additional models because they copy ViT's resize method. After changing ViT from BILINEAR to BICUBIC, these copies needed to stay in sync.

This PR complements the ongoing interpolation fixes (#28180) by @lukepayyapilli for other models.

Let me know if any changes are needed!

[CodersAcademy006]

This makes sense and aligns ViT preprocessing with expected defaults (e.g. TIMM). Since this changes a default behavior, it might be worth explicitly calling it out as a breaking change for users relying on the previous interpolation. A small regression test asserting the default resampling value could also help prevent accidental future changes.