fix bugs in request_handler

colossalai/inference/core/engine.py

@@ -226,12 +226,15 @@ class InferenceEngine:
             self.v_cache,
         )
 
+        logits = logits[:, -1, :]
         self.request_handler.search_tokens(self.generation_config, logits)
-
         finished_sequences = self.request_handler.update()
 
+        print("finished_sequences: ", finished_sequences)
+
         # Decode completed sentences.
         for seq in finished_sequences:
+            print("seq.output_token_id: ", seq.output_token_id)
             if seq.prompt:
                 output_str = self.tokenizer.decode(seq.output_token_id, skip_special_tokens=True)
                 output_list.append(seq.prompt + output_str)
@@ -239,4 +242,6 @@ class InferenceEngine:
                 output_str = self.tokenizer.decode(seq.input_token_id + seq.output_token_id, skip_special_tokens=True)
                 output_list.append(output_str)
 
+        print("len(output_list): ", len(output_list))
+
         return output_list

colossalai/inference/core/request_handler.py

@@ -5,6 +5,7 @@ from transformers.configuration_utils import PretrainedConfig
 
 from colossalai.inference.config import InferenceConfig
 from colossalai.inference.kv_cache import KVCacheManager
+from colossalai.inference.logit_processors import logit_processor
 from colossalai.inference.sampler import *
 from colossalai.inference.struct import BatchInfo, Sequence
 
@@ -179,10 +180,10 @@ class RequestHandler:
         """
         # do logit processor
         # NOTE: need to decide the granularity to process logits (sequence or batch)
-        # for type in ["top_p", "top_k", "min_p"]:
+        for type in ["top_p", "top_k", "min_p"]:
-        #     config_dict = generation_config.to_dict()
+            config_dict = generation_config.to_dict()
-        #     if type in config_dict:
+            if type in config_dict:
-        #         logits = logit_processor(type, logits, config_dict[type])
+                logits = logit_processor(type, logits, config_dict[type])
 
         torch.cuda.synchronize()
 
@@ -207,11 +208,12 @@ class RequestHandler:
             self.running_list.prefill.clear()
             self.prefill_batch.clear_batch()
 
-        for seq in self.running_batch.sequences_set:
+        finish_seqs = self.running_batch.fliter_batch()
-            if seq.check_finish():
-                self.done_list.append(seq)
-                self.running_list.remove(seq)
-                self.running_batch.sequences_set.remove(seq)
-                self.cache_manager.free_block_table(seq.block_table)
 
-        return self.done_list
+        for seq in finish_seqs:
+            self.running_list.remove(seq)
+            self.cache_manager.free_block_table(seq.block_table)
+
+        self.done_list.extend(finish_seqs)
+
+        return finish_seqs

colossalai/inference/struct.py

@@ -106,7 +106,7 @@ class Sequence:
             return True
 
         if self.output_token_id:
-            if self.output_token_id[-1] >= self.eos_token_id or len(self.output_token_id) == self.max_output_len:
+            if self.output_token_id[-1] == self.eos_token_id or self.output_len >= self.max_output_len:
                 self.status = RequestStatus.COMPLETED
                 return True
 

tests/test_infer/test_inference_engine.py

@@ -28,6 +28,7 @@ def check_inference_engine():
     generation_config = GenerationConfig(top_k=2, top_p=0.8, do_sample=True)
     outputs = inference_engine.generate(generation_config)
 
+    print("len(outputs): ", len(outputs))
     print("outputs: ", outputs)
 
     # Engine still gets some bug