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@ -800,6 +800,7 @@ class WindowAttention(nn.Module):
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x: input features with shape of (num_windows*B, N, C)
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x: input features with shape of (num_windows*B, N, C)
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mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None
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mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None
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"""
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"""
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B_, N, C = x.shape
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qkv_bias = None
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qkv_bias = None
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if self.q_bias is not None:
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if self.q_bias is not None:
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qkv_bias = torch.cat((self.q_bias, torch.zeros_like(self.v_bias, requires_grad=False), self.v_bias))
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qkv_bias = torch.cat((self.q_bias, torch.zeros_like(self.v_bias, requires_grad=False), self.v_bias))
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