没有找到官方实现.有一些非官方实现(GitHub: hosseinshn/GradNorm、brianlan/pytorch-grad-norm(简易版)、brianlan/complex-grad-norm(复杂版)). 下面是本人仿写的代码: import torch import torch.nn as nn import torch.optim as optim class GradNormLoss(nn.Module): def __init__(self, num_of_task, al...
PyTorch GradNorm This is a PyTorch-based implementation ofGradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks, which is a gradient normalization algorithm that automatically balances training in deep multitask models by dynamically tuning gradient magnitudes. ...
Repository files navigation README pytorch-grad-norm Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning adjustable weight coefficients. Packages No packages published ...
Input: Two synthetic regression tasks according to Ma et al. (KDD 2018) "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" Network: One shared layer and two task specific towers Framework: PytorchAbout No description, website, or topics provided. Resources ...
Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning adjustable weight coefficients. - brianlan/pytorch-grad-norm