If your reproducation perf. is not so good, maybe you can enlarge yourtraining epochto get longer training. And MAML is notorious for its hard training. Therefore, this implementation only provide you a basic start point to begin your research. and the performance below is true and achieved ...
For First-Order Approximation Implementation, Reptile namely, please visitHERE. Platform python: 3.x Pytorch: 0.4+ MiniImagenet Howto For 5-way 1-shot exp., it allocates nearly 6GB GPU memory. downloadMiniImagenetdataset fromhere, splitting:train/val/test.csvfromhere. ...
Implementation 本节中,我们将讨论教程的输入参数,定义攻击下的模型,以及相关的测试 Inputs 三个输入: epsilons: epsilon 列表值,保持 0 在列表中非常重要,代表着原始模型的性能。 epsilon 越大代表着攻击越大。 pretrained_model: 预训练模型,训练模型的代码在这里. 也可以直接下载预训练模型. 因为 google drive ...
track_higher_grads=False实际上不起作用的原因是，它分离了后适应 * 参数 * 的梯度，而不仅仅是 * ...
pytorch 这是MAML模型的正确实现吗？这似乎是大多数正确的，但有些是错误的方式方面的准确性计算。
pytorch 这是MAML模型的正确实现吗？这似乎是大多数正确的，但有些是错误的方式方面的准确性计算。
Meta-learning with zero-initialized classifier head.The official implementation learns a meta-initialization for both the encoder and the classifier head. This prevents one from varying the number of categories at training or test time. With our implementation, one may opt to learn a meta-initializa...
For First-Order Approximation Implementation, Reptile namely, please visit HERE. Platform python: 3.x Pytorch: 0.4+ MiniImagenet Howto For 5-way 1-shot exp., it allocates nearly 6GB GPU memory. download MiniImagenet dataset from here, splitting: train/val/test.csv from here. extract it li...
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML) - MAML-Pytorch/learner.py at master · xiaofeng-github/MAML-Pytorch
For First-Order Approximation Implementation, Reptile namely, please visit [HERE](https://github.com/dragen1860/Reptile-Pytorch).  # Platform - python: 3.x - Pytorch: 0.4+ Binary file added BIN +3.75 KB res/heart.gif Loading Viewer requires iframe. 0 comments ...