mulinmeng / shuffle-transformer Goto Github PK
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License: MIT License
I write a shuffle-large config following swin-large and training on ImageNet22K dataset using apex O1. But the training process is unstable and the loss quickly become NAN. Is there any suggestions about shuffle-large design and training on larger dataset like ImageNet-22K?
if self.has_pos_embed:
self.pos_embed = nn.Parameter(data=get_sinusoid_encoding(n_position=num_patches, d_hid=embed_dim), requires_grad=False)
self.pos_drop = nn.Dropout(p=drop_rate)
Hello, is get_sinusoid_encoding used? Can I remove it if I don't use it? This function doesn't seem to be defined.
非常感谢您的开源,请问有C++部署代码?
您好,请问在模型实现代码中为什么只需要换一下ws1和hh、ws2和ww的位置就能实现shuffle的操作呢,在括号里相乘(AxB)和(BxA)应该没有什么区别吧,期待您的解答!
就是下面的代码
q, k, v = rearrange(qkv, 'b (qkv h d) (ws1 hh) (ws2 ww) -> qkv (b hh ww) h (ws1 ws2) d', h=self.num_heads, qkv=3, ws1=self.ws, ws2=self.ws)
q, k, v = rearrange(qkv, 'b (qkv h d) (hh ws1) (ww ws2) -> qkv (b hh ww) h (ws1 ws2) d', h=self.num_heads, qkv=3, ws1=self.ws, ws2=self.ws)
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