add logs

src/transformers/cache_utils.py

@@ -395,6 +395,7 @@ class StaticCache(Cache):
         return k_out, v_out
 
     def get_seq_length(self, layer_idx: Optional[int] = 0) -> int:
+        print("self.seen_tokens in get_seq_length", self.seen_tokens)
         """Returns the sequence length of the cached states that were seen by the model. `layer_idx` kept for BC"""
         return self.seen_tokens
 

src/transformers/generation/utils.py

@@ -2386,7 +2386,10 @@ class GenerationMixin:
         unfinished_sequences = torch.ones(input_ids.shape[0], dtype=torch.long, device=input_ids.device)
 
         this_peer_finished = False  # used by synced_gpus only
+        count = 0
         while True:
+            print("------- forward in generate", count)
+            count += 1
             if synced_gpus:
                 # Under synced_gpus the `forward` call must continue until all gpus complete their sequence.
                 # The following logic allows an early break if all peers finished generating their sequence

src/transformers/models/llama/modeling_llama.py

@@ -1263,6 +1263,7 @@ class LlamaForCausalLM(LlamaPreTrainedModel):
         if past_key_value := getattr(self.model.layers[0].self_attn, "past_key_value", None):
             # generation with static cache
             past_length = past_key_value.get_seq_length()
+            print("past_length here", past_length)
             input_ids = input_ids[:, past_length:]
             position_ids = position_ids[:, past_length:]