diff --git a/DCNv4_op/DCNv4/modules/flash_deform_attn.py b/DCNv4_op/DCNv4/modules/flash_deform_attn.py
index d10f72d..d7340de 100644
--- a/DCNv4_op/DCNv4/modules/flash_deform_attn.py
+++ b/DCNv4_op/DCNv4/modules/flash_deform_attn.py
@@ -111,7 +111,6 @@ class FlashDeformAttn(nn.Module):
         value = value.view(N, Len_in, self.n_heads, self.d_model // self.n_heads)
         sampling_offsets = self.sampling_offsets(query).view(N, Len_q, self.n_heads, self.n_levels, self.n_points, 2)
         attention_weights = self.attention_weights(query).view(N, Len_q, self.n_heads, self.n_levels * self.n_points)
-        attention_weights = F.softmax(attention_weights, -1).view(N, Len_q, self.n_heads, self.n_levels, self.n_points)
         # N, Len_q, n_heads, n_levels, n_points, 2
         if reference_points.shape[-1] == 2:
             offset_normalizer = torch.stack([input_spatial_shapes[..., 1], input_spatial_shapes[..., 0]], -1)
@@ -131,7 +130,6 @@ class FlashDeformAttn(nn.Module):
             
         # Cat sampling_offsets and attention_weights, generate sampling_loc_attn:
         sampling_locations = sampling_locations.flatten(-3).half()
-        attention_weights = attention_weights.flatten(-2)
         sampling_loc_attn = torch.cat([sampling_locations, attention_weights], dim=-1)
 
         output = FlashDeformAttnFunction.apply(