Add OneFormer Model (#20577)
* Add Oneformer Model * Add OneFormer Tests * Add UNIVERSAL_SEGMENTATION_MAPPING * Fix config * 🐛 Fix error encountered while writing tests * 🔨 Fix instance segmentation post processing * Format Files and Add Documentation * Add Documentation mdx file * Run make fixup * Run make fix-copies * Remove unnecessary code * Format modeling_oneformer.py * Add OneFormer to ImageSegmentationPipeline * Format files * Add Demo link to Readme * Fix fomatting errors * Fix test failures * Update Table in index.mdx * Fix version * Fix style * Remove OneFormer from TF * Fix Imports * Fix dummy objects * Fix tests * Add newline * Remove OneFormerFeatureExtractor * Remove CUDA Kernels * Use AutoBackbone for Swin * Fix description * Use Image Processor * Fix copies * Fix formatting * Fix import order * Fix flake8 errors * Fix doc errors * Add Hindi Readme entry * Update supported backbones * Update supported backbones * Undo Changes * Fix type of config * Fix isort * Fix auto.mdx * Fix swin config * Replace DinatBackbone with AutoBackbone * Use SwinBackbone * Use SwinBackbone * Fix conversion script * Fix arguments * Add argument description * Fix style * Add OneFormerProcessor * Fix OneFormerProcessor Tests * Fix mapping * Fix imports * Fix inits * Fix style * Fix comment * Fix docstring * Move OneFormer to MultiModal * Fix Copies * Remove size divisor * Fix check_repo.py * Fix copies * Add Processor for Testing Pipeline * Fix padding for tokens * Fix variables * Fix formatting with correct black version * Add Image Processor Test * Apply suggestions * Revert common modeling * Add check for task * Fix conversion script * Fix initialization order * Fix tests * Undo Pipeline Changes * Fix layers in MLP * Fix copies * Update image paths * Fix copies * Apply suggestions
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@@ -139,6 +139,7 @@ specific language governing permissions and limitations under the License.
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1. **[Nezha](model_doc/nezha)** (from Huawei Noah’s Ark Lab) released with the paper [NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204) by Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen and Qun Liu.
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1. **[NLLB](model_doc/nllb)** (from Meta) released with the paper [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) by the NLLB team.
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1. **[Nyströmformer](model_doc/nystromformer)** (from the University of Wisconsin - Madison) released with the paper [Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention](https://arxiv.org/abs/2102.03902) by Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh.
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1. **[OneFormer](model_doc/oneformer)** (from SHI Labs) released with the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi.
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1. **[OPT](master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
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1. **[OWL-ViT](model_doc/owlvit)** (from Google AI) released with the paper [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby.
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1. **[Pegasus](model_doc/pegasus)** (from Google) released with the paper [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://arxiv.org/abs/1912.08777) by Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu.
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