Update utils_llama.py

research/long-context-llama/H2O/utils_llama.py

@@ -278,8 +278,6 @@ class H2OLlamaAttention(nn.Module):
         if past_key_value is not None:
             past_key_value.update_slimming(attn_weights, self.num_key_value_groups, self.layer_idx, cache_kwargs)
 
-
-
         attn_weights = nn.functional.dropout(attn_weights, p=self.attention_dropout, training=self.training)
         attn_output = torch.matmul(attn_weights, value_states)
 
@@ -303,6 +301,8 @@ class H2OLlamaAttention(nn.Module):
         if not output_attentions:
             attn_weights = None
 
+        pdb.set_trace()
+
         return attn_output, attn_weights, past_key_value