24. Pytorch 中 KL 计算出现负值 需加个 log import torch KL_criterion = torch.nn.KLDivLoss(size_average=False) a = torch.tensor([0.2, 0.1, 0.3, 0.4]) b = torch.tensor([0.1, 0.2, 0.3, 0.4]) loss1 = KL_criterion(a.log(), b) print(loss1) # tensor(0.0693) 加 log 正确 loss2...
KLD_Pytorchgithub.com/open-mmlab/mmrotate KLD_Jittorgithub.com/Jittor/JDet 效果比较:不加任何数据增强、多尺度训练和测试等tricks下,将RetinaNet-Res50上的Smooth L1 Loss换成KLD,模型在DOTA1.0数据集上的 AP50 从65.73%提高到71.28%, AP75 从32.31%提升到44.48%。 已经看过GWD的朋友可能会有这样子...
Here is my code for the VAE Loss: def loss_function(x, x_hat, mean, logvar, beta=1.0): criterion = nn.MSELoss(reduction="mean") reconstruction_loss = criterion(x_hat, x) KLD = - 0.5 * torch.mean(1+ logvar - mean.pow(2) - logvar.exp()) print(f"KLD = ...
PyTorch ≥ 1.7 CUDA 9.0 or higher Install CUDA Driver Version ≥ CUDA Toolkit Version(runtime version) = torch.version.cuda a. Create a conda virtual environment and activate it, e.g., conda create -n Py39_Torch1.10_cu11.3 python=3.9 -y source activate Py39_Torch1.10_cu11.3 ...