update code comment

modeling.py

@@ -337,8 +337,8 @@ class BertModel(nn.Module):
             token_type_ids = torch.zeros_like(input_ids)
 
         # We create a 3D attention mask from a 2D tensor mask.
-        # Sizes are [batch_size, 1, 1, from_seq_length]
-        # So we can broadcast to [batch_size, num_heads, to_seq_length, from_seq_length]
+        # Sizes are [batch_size, 1, 1, to_seq_length]
+        # So we can broadcast to [batch_size, num_heads, from_seq_length, to_seq_length]
         # this attention mask is more simple than the triangular masking of causal attention
         # used in OpenAI GPT, we just need to prepare the broadcast dimension here.
         extended_attention_mask = attention_mask.unsqueeze(1).unsqueeze(2)