test cossim

model_custom.py

@@ -25,16 +25,17 @@ class PositionalEncoding(nn.Module):
         pe = torch.zeros(max_len, 1, d_model)
         pe[:, 0, 0::2] = torch.sin(position * div_term)
         pe[:, 0, 1::2] = torch.cos(position * div_term)
+        print(d_model, max_len)
         self.register_buffer('pe', pe)
 
     def forward(self, x):
-        print(x.size())
+
         x = torch.permute(x, (1, 0, 2))
         """
         Arguments:
             x: Tensor, shape ``[seq_len, batch_size, embedding_dim]``
         """
-        print(self.pe[:x.size(0)].size())
+
         x = x + self.pe[:x.size(0)]
         return self.dropout(x)