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[NeurIPS 2021] [T-PAMI] Global Filter Networks for Image Classification

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您好,感谢您的工作。我有两个问题想咨询。 1.我在有关序列任务上尝试了你的模型,我的序列长度为256,tensor为(B,256,512)输入到你的模型,我这里忽略了输入的意义,直接将序列256看作是2维信号 (即 H W 为16) ,强行让模型学习,但是奇怪的是结果却很好。我想问一下如何直接使用1D FFT对序列进行操作,代码如何编写? 2.在进行2D FFT,输入的信号必须像文中的图片那样 H W是一样的吗?如何可以不一样,代码需要做那些修改? 打扰了,期待您的回复!再次感谢!

Thanks to share your nice work. I have followed up on your art since the last year and I found out TPAMI paper which is enhanced from the NeurIPS version....

import torch import torch.nn as nn import torch.fft class GlobalFilter(nn.Module): def __init__(self, dim, h=14, w=8): super().__init__() self.complex_weight = nn.Parameter(torch.randn(h, w, dim, 2, dtype=torch.float32) * 0.02) def forward(self, x): B, H,...

I read the paper, it was providing straight ideas about how does GFNT tackled the limitation of using Self-Attention with a Vision-Transformer in computations cost and complexity also, i would...

why I can only replicate the whole model on different gpu, not the model parallel that distributed part of the model to the gpu? I follow the instruction on the...

Hello, i am new to pytorch and wanted to know how exactly the trained model could be used for prediction with images? thank you

Ask about the reasoning speed of an fft filter: After using GlobalFilter, I found that this will greatly affect the speed of model reasoning, which is almost half of that...

Thank you very much for your work, but when I realized the visualization of the frequency domain filter, the image is different from the one you provided. And I would...