Support chatglm2 in pytorch_poc (#360)

* draft support for chatglm2

* debug llama

* gitignore

* update input_id

* better patching

* patch chatglm2 model

* fix after merge

* remove inits

* q_seq_info & remove some debug & orig_self

* remove old unqeuzze inputid

* update patch and model config

* remove debugs and clean codes

* clean codes

* add credit

* add update id / fix dependency

lmdeploy/model.py

@@ -87,6 +87,10 @@ def stop_words(self):
         """Return the stop-words' token ids."""
         return None
 
+    def update_input_ids(self, input_ids: List[int]):
+        """Further modify input ids of the prompt."""
+        return input_ids
+
 
 @MODELS.register_module(name='vicuna')
 class Vicuna(BaseModel):
@@ -481,6 +485,25 @@ def stop_words(self):
         return [151645]  # <|im_end|>
 
 
+@MODELS.register_module(name='chatglm2-6b')
+class ChatGLM2(BaseModel):
+
+    def __init__(self):
+        super().__init__()
+        self.count = 0
+
+    def get_prompt(self, prompt, sequence_start=True):
+        # need more check
+        # https://github.com/THUDM/ChatGLM2-6B/issues/48
+        # [64790, 64792] to be prepended
+        self.count += 1
+        return f'[Round {self.count}]\n\n问：{prompt}\n\n答：'
+
+    def update_input_ids(self, input_ids: List):
+        input_ids = [64790, 64792] + input_ids
+        return input_ids
+
+
 def main(model_name: str = 'test'):
     assert model_name in MODELS.module_dict.keys(), \
         f"'{model_name}' is not supported. " \

lmdeploy/pytorch_poc/chat.py

@@ -33,6 +33,9 @@ def main(
         model_path,
         model_name: str,  # can not get model_name from hf model
         session_id: int = 1,
+        top_k=40,
+        top_p=0.8,
+        temperature=0.8,
         repetition_penalty: float = 1.0,
         tp: int = 1,
         stream_output=True):
@@ -73,12 +76,13 @@ def main(
                 continue
             prompt = model.get_prompt(prompt, nth_round == 1)
             input_ids = tokenizer.encode(prompt)
+            input_ids = model.update_input_ids(input_ids)
             print(f'{prompt} ', end='', flush=True)
             response_size = 0
             sampling_param = SamplingParam(
-                top_k=40,
-                top_p=0.8,
-                temperature=0.8,
+                top_k=top_k,
+                top_p=top_p,
+                temperature=temperature,
                 repetition_penalty=repetition_penalty,
                 ignore_eos=False,
                 random_seed=seed,

lmdeploy/pytorch_poc/engine/engine.py

@@ -447,14 +447,25 @@ def __init__(
             cache_config = CacheConfig(block_size=64,
                                        num_cpu_blocks=0,
                                        num_gpu_blocks=0)
-        model_config = ModelConfig(
-            hf_config.hidden_size,
-            hf_config.num_hidden_layers,
-            hf_config.num_attention_heads,
-            bos_token_id=hf_config.bos_token_id,
-            eos_token_id=hf_config.eos_token_id,
-            dtype=torch_dtype,
-        )
+        if 'chatglm' in model_path:
+            model_config = ModelConfig(
+                hf_config.hidden_size // hf_config.num_attention_heads *
+                hf_config.multi_query_group_num,
+                hf_config.num_layers,
+                hf_config.multi_query_group_num,
+                bos_token_id=hf_config.bos_token_id,
+                eos_token_id=hf_config.eos_token_id,
+                dtype=torch_dtype,
+            )
+        else:
+            model_config = ModelConfig(
+                hf_config.hidden_size,
+                hf_config.num_hidden_layers,
+                hf_config.num_attention_heads,
+                bos_token_id=hf_config.bos_token_id,
+                eos_token_id=hf_config.eos_token_id,
+                dtype=torch_dtype,
+            )
 
         self.scheduler_config = scheduler_config
         self.cache_config = cache_config