所以transform中直接ToTensor就好。最近抄了FedML框架中的的数据预处理,结果从CIFAR100移植到FashionMNIST的时候训练集和测试集的数据之间差了一个255的归一化,直接导致测试准确率在50%到70%之间飘忽不定。后来逐行增量调试才找到这个问题,所以抄代码如果不确定每一行的意思最好不要随便抄哇。#PyTorch #
First, to create a docker container using NVIDIA’s PyTorch base image, create the following Dockerfile: FROM nvcr.io/nvidia/pytorch:24.07-py3 # Set up working directory WORKDIR /app RUN pip install protobuf==3.20.0 RUN python -m pip install --upgrade pip # Download CIFAR-10 or other ...
Official PyTorch implementation of "GuidedMixup An Efficient Mixup Strategy Guided by Saliency Maps" (AAAI'23 Oral) - GuidedMixup/load_data.py at main · kdst-team/GuidedMixup
# in pytorch/torch/utils/data/sampler.py 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 1. Available Datasets MNISTQMNISTFakeDataCOCOCaptionsDetectionLSUNImageFolderDatasetFolderImageNetCIFARSTL10SVHNPhotoTourSBUFlickrVOCCi...