softmax of the attention vector

[batman47steam]

attention_vector = torch.cat( [ self.conv_ex(Z).unsqueeze(dim=1), self.conv_ex(Z).unsqueeze(dim=1) ], dim=1)
attention_vector = self.softmax(attention_vector)
and self.softmax = nn.Softmax(dim=1)
it seems that the elements of the attention_vector are the same, so if you apply softmax on dim=1，the result of the softmax will all be the same, 0.5 for sure

so why are we doing this，i don't know if i have missed something