code can be found at https://github. Python · Butterfly & Moths Image Classification 100 species. swin transformer pytorch使用，##使用SwinTransformerPyTorch的步骤作为一名经验丰富的开发者，我将教你如何使用SwinTransformerPyTorch。下面是整个过程的步骤摘要：1. Significance is further explained in Yannic Kilcher's video. Video Recognition, See Video Swin Transformer. Requirements tensorflow >= 2. Installation pip install tfswin Examples. 그래서 pytorch 학습 코드에 모델만 허깅페이스의 트랜스포머로. The SwinTransformer models are based on the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows paper. As a transformer-based approach for computer vision, Swin UNETR employs MONAI, an open-source PyTorch framework for deep learning in healthcare imaging, including radiology and pathology. swin_transformer Shortcuts Source code for torchvision. The pretrained models locate at https://github. 1 （与显卡. Mar 29, 2021 · Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. We can treat the last 49 elements as a 7x7 spatial image, with 1024 channels. Parameters: weights ( Swin_T_Weights, optional) – The pretrained weights to use. The code and models are publicly available at~\url {https://github. 0 license. Training advise with swin_transformer - initialization with GELU, etc. Note: https://github. Using this pretraining scheme, Swin UNETR has set new state-of-the-art benchmarks for various medical image segmentation tasks and consistently demonstrates. Implementation of the Swin Transformer architecture. transformer 深度学习 人工智能 SwinTransformer:HierarchicalVisionTransformerusingShiftedWindowsswin:shiftedwindow因为之前的ViT已经将transformer用于图像分类。 本文的研究动机是使transformer兼容所有视觉领域的下游任务，包括检测、分割、. Windows10系统下swin-transformer目标检测环境搭建 Swin-Transformer-Object-Detection环境搭建 前言 刚搞明白了分类，又进来了检测这个大坑里。 CV第一步：从环境搭建开始！ 环境总览： Windows10/11+ Microsoft Visual Studio2019社区版 python3. Swin Transformer. 1 s - GPU P100 history Version 2 of 2 menu_open Swin Transformers ¶ This notebook trains a Vision Transformer on the Butterfly dataset. In this blog post, we use Llama 2 as an example model to demonstrate the power of PyTorch/XLA on Cloud TPUs for LLM training and inference. 3, 2019. Train Swin-Transformer v2 (PyTorch/JAX) Experiment & results. Contribute to MaoQiankun97/swin_transformer development by creating an account on GitHub. Contribute to csm-kr/swin_transformer_pytorch development by creating an account on GitHub. 如果想详细的看还是得看论文《Swin Transformer: Hierarchical Vision Transformer using Shifted Windows》 Swin是shift和window两个单词的结合. Object Detection and Instance Segmentation: See Swin Transformer for Object Detection. All the model builders internally rely on the torchvision. All the model builders internally rely on the torchvision. main (0. Implementation of the Swin Transformer architecture. This repository includes a pure PyTorch implementation of the Swin Transformer V2 and provides pre-trained weights (CIFAR10 & Places365). com%2fmicrosoft%2fSwin-Transformer/RK=2/RS=wZOGmWQF3AR9YJZo3vRirACj0Zs-" referrerpolicy="origin" target="_blank">See full list on github. The shifted windowing scheme brings greater efficiency by limiting self-attention. PyTorch Paper Replicating from the Zero to Mastery PyTorch course. Join the PyTorch developer community to contribute, learn, and get your questions answered. Using this pretraining scheme, Swin UNETR has set new state-of-the-art benchmarks for various medical image segmentation tasks and consistently demonstrates. - GitHub - berniwal/swin-transformer-pytorch: Implementation of the Swin Transformer in . The shifted window scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while. Pull requests. We can treat the last 49 elements as a 7x7. Please refer to the source code for more details about this class. SwinTransformer3d base class. py) DCN (mixed precision training not support, if you want use dcn, please close amp in line 292 of scripts/train. All the model builders internally rely on the torchvision. 一脚踹进ViT——Swin Transformer (下) 一、Shift-Window Attention image输入后提一个patch块，如果是4×4=16个pixel，就把它展开，来做conv/proj，经过处理后它就变成1×embed dim的tensor， 每一个就叫做embedding或vision tokens，真正输入Transformer的就是embedding或vision tokens，我们在此基础上需要进行切分window. Learn about PyTorch’s features and capabilities. See get_started. Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data. 1 基于CNN的遥感图像语义分割 2. 7 box AP and 51. Pytorch code for "BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment", CVPRW, 1st place in NTIRE 2022 BurstSR Challenge (real-world track). Libraries: Pytorch, Tensorflow, Numpy, Matplotlib; Developer Tools: Git;. Implementation of the Swin Transformer architecture. import torch import torchvision from torchvision import datasets from torchvision import transforms as T # for simplifying the transforms from torch import nn, optim from torch. Please refer to the source code for more details about this class. Constructs a swin_tiny architecture from Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. From the Abstract of the paper: Swin Transformer is compatible for a broad range of vision tasks, including image classification (87. PyTorch Foundation. swin V2 Unet/Upernet. 1 cudatoolkit=9. trace on the Swin Transformer model from a pretrained checkpoint so it can be exported to another format (e. swin_t (* [, weights, progress. Hey @rwightman – once you have a good idea of the interface I'm happy to help with this – I'd like to use it for my experimentation. Constructs a swin_tiny architecture from Video. Please refer to the source code for more details about this class. The rapid evolution of coronaviruses in respiratory diseases, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a significant challenge. 14030] Tensorflow code adapted from Swin-Transformer-TF MLP-Mixer and friends MLP-Mixer: An all-MLP Architecture for Vision [arXiv:2105. Implementation of the Swin Transformer architecture. Vision Transformer inference pipeline. py 文件，将以下代码复制进去： 参考上一篇的安装和运行代码经验，接上一步键入： conda install pytorch==1. Swin Transformer. In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection. Swin-T主要有4个点，patch embedding，Swin Transformer Block，patch merging， classification. Swin Transformer (Hierarchical Vision Transformer using Shifted. This paper presents a new vision Transformer, called Swin Transformer,. - GitHub - SwinTransformer/. Please refer to the source code for more details about this class. RepVGGplus outperformed several recent visual transformers with a top-1 accuracy of 84. GitHub - NVlabs/GCVit: Official PyTorch implementation of Global Context . Download the zip file [swin_moe_small_patch4_window12_192_32expert_32gpu_22k. 而 Swin Transformer Block 具体结构如右图所示，主要是 LayerNorm ， Window Attention ， Shifted Window Attention 和 MLP 组成 。 从代码的角度： 在微软亚洲研究院提供的代码中，是将 Patch Merging 作为每个 Stage 最后结束的操作，输入先进行 Swin Transformer Block 操作，再下采样。. PyTorch is the framework used by Stability AI on Stable Diffusion v1. This paper presents a new vision Transformer, called Swin Transformer,. Contribute to MaoQiankun97/swin_transformer development by creating an account on GitHub. 2 Swin Transformer BlocK 3. Learn about PyTorch’s features and capabilities. Oct 28, 2022 · Swin Transformer [github] Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. More weights pushed to HF hub along with multi-weight support, including: regnet. SwinTransformer — Torchvision main documentation SwinTransformer The SwinTransformer models are based on the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows paper. All the model builders internally rely on the torchvision. Yu, et al. The hierarchical design and the shifted window approach also prove beneficial for all-MLP architectures. The github. This repo is a simple usage of the official implementation "Video Swin Transformer". loukasiliason Oct 24, 2021. Implementation of the Swin Transformer architecture. Python · Butterfly & Moths Image Classification 100 species. GitHub - NVlabs/GCVit: Official PyTorch implementation of Global Context . Installation pip install tfswin Examples. shape B, C, H, W), and flatten/unflatten internally (to B, C, H*W). 7 -y conda activate open-mmlab # install latest pytorch prebuilt with the default prebuilt CUDA version (usually the latest) conda install -c pytorch pytorch torchvision -y # install the latest mmcv or mmcv-full, here we take mmcv as example pip install mmcv # install mmaction2 git clone. See get_started. 安装mmcv 三种方式可以选择，自行尝试哪一种可以安装成功，这里是个大坑！ （1）自动安装（不稳定不推荐） 或者在该 github 仓库将 code 打包下载然后解压，然后在 Anaconda Powershell Prompt 中使用 cd 命令切换到该根目录下，然后：. This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation. - GitHub - Algolzw/BSRT: Pytorch code for "BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment", CVPRW, 1st place. More specifically, VRT is composed of multiple scales, each of which consists of two kinds of modules: temporal mutual self attention (TMSA) and parallel warping. Using this pretraining scheme, Swin UNETR has set new state-of-the-art benchmarks for various medical image segmentation tasks and consistently demonstrates. SWIN_transformer_pytorch training own dataset. Currently (13. Challenges in adapting Transformer from language to vision arise from differences between the two domains, such as large. 0 2,350 58 1 Updated Aug 24, 2022. Add this topic to your repo. This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision. In case anyone else reads this, for swin and other transformer arch with fixed or contrained image sizes, it's best to resize/crop/pad the image in preprocessing to fit the network input. Aug 28, 2021 · Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. I've been setting up with swin_transformer but having a hard time getting it to actually train. HI, I have a dirty fix temporarily, you can try to replace torch. Supports variable. 1 s - GPU P100 history Version 2 of 2 menu_open Swin Transformers ¶ This notebook trains a Vision Transformer on the Butterfly dataset. However, for Swin-L, --int8-mode 1 cannot get a satisfactory result for PTQ accuracy. forward_features(INPUT), I got a different vector. From the Abstract of the paper: Swin Transformer is compatible for a broad range of vision tasks, including image classification (87. Based on Official Pytorch implementation. And also you can find that the procedure of training is intuitive thanks to the legibility of pytorch-lightning. In this paper, we propose a strong baseline model SwinIR for image restoration based on the Swin Transformer. " Learn more. 1 mmcv1. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. · Issue #35597 · pytorch/pytorch · GitHub 但其实之前用的就是3. swin_t can be instantiated with pre-trained weights and all others without. SwinTransformer base class. py) coord conv; drop_block; vgg, repvgg; tensorrt c++/python infer, triton server infer; gnn backbone; Notices. But regardless, I'm not able to get it to learn atm even after testing out a range of lr. For details, see Emerging Properties in Self-Supervised Vision Transformers. - swin-transformer-pytorch/swin_transformer. SwinTransformer base class. It is basically a hierarchical Transformer whose representation is computed with shifted windows. For Llama 2 70B parameters, we deliver 53% training MFU, 17 ms/token. A tag already exists with the provided branch name. Constructs a swin_tiny architecture from Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. Please open a GitHub issue for any help. for image classification, and demonstrates it on the CIFAR-100 dataset. Aug 23, 2021 · SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. models import resnet50 model = resnet50 (pretrained = True) target_layers = [model. berniwal swin-transformer-pytorch Public. main (0. It is a demonstration of how using vision transformers, metric learning, and a novel loss based on differential cross-entropy can lead to better retrieval than classical CNN-based methods. Constructs a swin_tiny architecture from Video. With image size=(256,256) and batch size 32 and 64 settings, both the JAX and the PyTorch took significantly longer during the first epoch, especially during the first iteration (batch). 2 release includes a standard transformer module based on the paper Attention is All You Need. See Swin_T_Weights below for more details, and. load examples can be used with the pip package via this basic change: # before torch. create_model ('swin_base_patch4_window7_224', pretrained=True) model. See Swin_T_Weights below for more details, and possible values. Implementation of the Swin Transformer architecture. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. 05537}, archivePrefix = {arXiv}, primaryClass = {eess. Object Detection: See Swin Transformer for Object Detection. PyTorch reimplementation of the paper "Swin Transformer V2: Scaling Up . By default, no pre-trained weights are used. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. The following model builders can be used to instanciate an SwinTransformer model. The abstract from the paper is the following: Large-scale NLP models have been shown to significantly improve. py, resnetv2. The following model builders can be used to instanciate an SwinTransformer model. Libraries: Pytorch, Tensorflow, Numpy, Matplotlib; Developer Tools: Git;. weights (Swin_T_Weights, optional) - The pretrained weights to use. By default, no pre-trained weights are used. 0 license. A place to discuss PyTorch code, issues, install, research. py, swin_transformer_v2_cr. 1 s - GPU P100 history Version 2 of 2 menu_open Swin Transformers ¶ This notebook trains a Vision Transformer on the Butterfly dataset. It set new performance records on 4 representative vision tasks, including ImageNet-V2 image classification. This is a tutorial on training a model to predict the next word in a sequence using the nn. This repo is the official implementation of. This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision. The official Swin . yaml --requirements-file requirements. model_targets import ClassifierOutputTarget from pytorch_grad_cam. 1 基于CNN的遥感图像语义分割 2. NUS-Tim commented on Sep 9, 2022. In this blog, we discuss how to improve the inference latencies of the Llama 2 family of models using PyTorch native optimizations such as native fast kernels, compile transformations from torch compile, and tensor parallel for distributed inference. Swin Transformer ( S hifted Win dow Transformer) can serve as a general-purpose backbone for computer vision. 9 top-1 accuracy on Kinetics-400 and 86. SwinTransformer — Torchvision main documentation SwinTransformer The SwinTransformer models are based on the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows paper. Significance is further explained in Yannic Kilcher's video. com%2fmicrosoft%2fSwin-Transformer/RK=2/RS=wZOGmWQF3AR9YJZo3vRirACj0Zs-" referrerpolicy="origin" target="_blank">See full list on github. Swin Transformer - PyTorch. Join the PyTorch developer community to contribute, learn, and get your questions answered. More weights pushed to HF hub along with multi-weight support, including: regnet. 2 Swin Transformer BlocK 3. PyTorch Foundation. 3（只是IDE，版本不同也没关系） 显卡 3060 12G Cuda 11. The following model builders can be used to instanciate an SwinTransformer model. Swin Transformer (Liu et al. Learn about the PyTorch foundation. There's really not much to code here, but may as well lay it out for everyone so we expedite the attention. Based on Official Pytorch implementation. Installation pip install tfswin Examples. 0 2,342 58 1 Updated Aug 24, 2022. 2 Swin Transformer BlocK 3. Implementation of the Swin Transformer architecture. The abstract from the paper is the following: Large-scale NLP models have been shown to significantly improve. 2; Platform: Linux-5. 5 mIoU，超过之前SOTA大概4. downtown phoenix bars
The official Swin transformer repository can be found here:. . Swin transformer github pytorch
安装mmcv 三种方式可以选择，自行尝试哪一种可以安装成功，这里是个大坑！ （1）自动安装（不稳定不推荐） 或者在该 github 仓库将 code 打包下载然后解压，然后在 Anaconda Powershell Prompt 中使用 cd 命令切换到该根目录下，然后：. Github; Google Scholar; CV Education. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. Swin Transformer - PyTorch. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. 1 cudatoolkit=9. The input size is (1,3,224,224), and other settings are default I want to extract feature maps from 4 stages, but this is the feature map size I got output size torch. More than 100 million people use GitHub to discover, fork, and contribute to over 330 million projects. We use Swin Transformers to inference on an image of a bird. Please open a GitHub issue for any help. This repository is the official PyTorch implementation of URSCT-SESR: Reinforced Swin-Convs Transformer for Simultaneous Underwater Sensing Scene Image Enhancement and Super-resolution. Constructs a swin_tiny architecture from Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. · Issue #35597 · pytorch/pytorch · GitHub 但其实之前用的就是3. This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision. This is the codebase for our research work. This paper presents a new vision Transformer, called Swin Transformer,. , 2021) is a transformer-based deep learning model with state-of-the-art performance in vision tasks. 如果想详细的看还是得看论文《Swin Transformer: Hierarchical Vision Transformer using Shifted Windows》 Swin是shift和window两个单词的结合. By default, no pre-trained weights are used. Aug 23, 2021 · SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. Please refer to the source code for more details about this class. I would like to ask you if the image used as input to the swin transformer will have input size [channels, H, W] or [H,W,channels]. This organization maintains repositories built on Swin Transformers. 如果想详细的看还是得看论文《Swin Transformer: Hierarchical Vision Transformer using Shifted Windows》 Swin是shift和window两个单词的结合. CI/CD & Automation. Email / CV / Google Scholar / Github / LinkedIn. main (0. As a transformer-based approach for computer vision, Swin UNETR employs MONAI, an open-source PyTorch framework for deep learning in healthcare imaging, including radiology and pathology. forward_features(INPUT), I got a different vector. Add this topic to your repo. Our training script is based on codebase of Swin Transformer. 関連手法：Swin Transformer V2 Ze Liu, et al. pth --handler swin_handler. I would like to create a PR for example of Swin Transformer in which I will create an example to generate gradient maps using swin transformer, as well as update the readme file for info. This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation. Please refer to the source code for more details about this class. Our approach results in 29ms/token latency for single user requests on the 70B LLaMa model (as. py, swin_transformer_v2. 13230}, year={2021} } @article{liu2021Swin, title={Swin Transformer: Hierarchical Vision Transformer using Shifted Windows}, author={Liu, Ze and Lin, Yutong and Cao, Yue and Hu, Han. txt # move the swin. SwinUNet3D Architecture, Video Swin-Transformer, Now-casting,. This Notebook has been. Apr 8, 2021 · swin-transformer-pytorch Implementation of the Swin Transformer architecture. With image size=(256,256) and batch size 32 and 64 settings, both the JAX and the PyTorch took significantly longer during the first epoch, especially during the first iteration (batch). Swin Transformer V2: Scaling Up Capacity and Resolution Ze Liu*, Han Hu*, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei,. PyTorch Foundation. Model builders. Image Classification: See Swin Transformer for Image Classification. Aug 28, 2021 · Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. It exploits the local structure of images by partitioning them into patches and only applying self-attention within each patch rather than over the entire image. load examples can be used with the pip package via this basic change: # before torch. ly/Q013P5Lj0 Includes: - Swin Transformer - Pyramid ViT - Compact ViT and many other! #machinelearning #deeplearning #ai #aisummer GitHub - SforAiDl/vformer: A modular PyTorch. 그래서 pytorch 학습 코드에 모델만 허깅페이스의 트랜스포머로. and models are publicly available at https://github. python pytorch swin-transformer实现分类. trace on the Swin Transformer model from a pretrained checkpoint so it can be exported to another format (e. 仅作为个人学习记录使用，侵权直接删除！转自这里（侵权删） 前期准备 PyCharm 2021. This repository contains code used to perform image retrieval using transformers. 1 top-1 accuracy on Kinetics-600 with ~20x less pre-training data and ~3x smaller model. Swin-T主要有4个点，patch embedding，Swin Transformer Block，patch merging， classification. Swin Transformer in PyTorch Python · Butterfly & Moths Image Classification 100 species Swin Transformer in PyTorch Notebook Input Output Logs Comments (2) Run 328. [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks. Python 1,043 Apache-2. License GPL-3. trace on the Swin Transformer model from a pretrained checkpoint so it can be exported to another format (e. PyTorch Libraries PyTorch torchaudio torchtext torchvision TorchElastic TorchServe PyTorch on XLA Devices Docs > Module code> torchvision> torchvision. Swin Transformer (Liu et al. from timm. SwinTransformer V2 models are based on the Swin Transformer V2: Scaling Up Capacity and Resolution paper. This repo is the official implementation of. How does it work with Vision Transformers. PyTorch Foundation. py --serialized-file weights/swin_tiny_patch4_window7_224. In [1]:. model = timm. [7] https://github. 安装mmcv 三种方式可以选择，自行尝试哪一种可以安装成功，这里是个大坑！ （1）自动安装（不稳定不推荐） 或者在该 github 仓库将 code 打包下载然后解压，然后在 Anaconda Powershell Prompt 中使用 cd 命令切换到该根目录下，然后：. py 文件，将以下代码复制进去： 参考上一篇的安装和运行代码经验，接上一步键入： conda install pytorch==1. We present a pretrained 3D backbone, named Swin3D, that first-time outperforms all state-of-the-art methods on downstream 3D indoor scene understanding tasks. It achieves state-of-the-art results on COCO object detection and semantic segmentation compared to the previous Vision Transformer (ViT) model. 1 torchvision==0. Implementation of the Swin Transformer architecture. we show a PyTorch-like pseudocode of our auxiliary task with the associated Ldrloc loss. SwinTransformer V2 models are based on the Swin Transformer V2: Scaling Up Capacity and Resolution paper. com/PyTorchLightning/pytorch-lightning, vol. We have introduced 3 new model variants for RetinaNet, FasterRCNN and MaskRCNN that include several post-paper architectural optimizations and improved training recipes. Learn about the PyTorch foundation. It performs very well on the Imagenet dataset, better than many other convolutional neural. This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose. PyTorch Foundation. 安装mmcv 三种方式可以选择，自行尝试哪一种可以安装成功，这里是个大坑！ （1）自动安装（不稳定不推荐） 或者在该 github 仓库将 code 打包下载然后解压，然后在 Anaconda Powershell Prompt 中使用 cd 命令切换到该根目录下，然后：. This notebook provides the simple walkthrough of the Vision Transformer. GitHub is where people build software. PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration. PyTorch Foundation. Swin-T主要有4个点，patch embedding，Swin Transformer Block，patch merging， classification. Implementation of the Swin Transformer architecture. This repository includes a pure PyTorch implementation of the Swin Transformer V2 and provides pre-trained weights (CIFAR10 & Places365). Swin-T主要有4个点，patch embedding，Swin Transformer Block，patch merging， classification. By Ze Liu*, Yutong Lin*, Yue Cao*, Han Hu*, Yixuan Wei, Zheng Zhang, Stephen Lin and Baining Guo. . lippert slide out motor wiring diagram, reina heart porn, jeremy ethier beginner shred pdf free download, jeremy ethier intermediate shred program pdf, warehouse jobs atlanta, mybjclub, qvc presenter dies on air, craigslist south carolina cars, sjylar snow, mamacachonda, old naked grannys, squirting pussies co8rr