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[Core] Remove tokenizer group in vLLM (#24078)

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Signed-off-by: Zhuohan Li <zhuohan123@gmail.com>
This commit is contained in:
Zhuohan Li
2025-09-17 01:42:59 -07:00
committed by GitHub
parent c15309a730
commit 6c47f6bfa4
49 changed files with 276 additions and 934 deletions
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28
tests/lora/test_llama_tp.py
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@@ -13,14 +13,6 @@ from ..utils import VLLM_PATH, create_new_process_for_each_test, multi_gpu_test
MODEL_PATH = "meta-llama/Llama-2-7b-hf"
EXPECTED_NO_LORA_OUTPUT = [
"\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_75 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_76 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_77 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_78 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user]", # noqa: E501
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_11 (nationality VARCHAR, elector VARCHAR)\n\n question: When Anchero Pantaleone was the elector what is under nationality? ", # noqa: E501
"\n\n answer: 1\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_96 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a high tone mora with a gloss of /˧kot/ [kòt]? [/user] [assistant]\n\n answer: 2\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_97 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a high tone mora with a gloss of /˧kot/ [kòt]? [/user] [assistant]\n\n answer: 2\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_98 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one m", # noqa: E501
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE candidate (people_id VARCHAR, unsure_rate INTEGER); CREATE TABLE people (sex VARCHAR, people_id VARCHAR)\n\n question: which gender got the highest average uncertain ratio. ", # noqa: E501
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_60 (pick INTEGER, former_wnba_team VARCHAR)\n\n question: What pick was a player that previously played for the Minnesota Lynx? ", # noqa: E501
"\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE", # noqa: E501
]
EXPECTED_LORA_OUTPUT = [
" SELECT icao FROM table_name_74 WHERE airport = 'lilongwe international airport' ", # noqa: E501
" SELECT nationality FROM table_name_11 WHERE elector = 'anchero pantaleone' ", # noqa: E501
@@ -79,23 +71,12 @@ def generate_and_test(llm,
sql_lora_files,
tensorizer_config_dict: Union[dict, None] = None):
print("lora adapter created")
assert do_sample(llm,
sql_lora_files,
tensorizer_config_dict=tensorizer_config_dict,
lora_id=0) == EXPECTED_NO_LORA_OUTPUT
print("lora 1")
assert do_sample(llm,
sql_lora_files,
tensorizer_config_dict=tensorizer_config_dict,
lora_id=1) == EXPECTED_LORA_OUTPUT
print("no lora")
assert do_sample(llm,
sql_lora_files,
tensorizer_config_dict=tensorizer_config_dict,
lora_id=0) == EXPECTED_NO_LORA_OUTPUT
print("lora 2")
assert do_sample(llm,
sql_lora_files,
@@ -110,6 +91,7 @@ def test_llama_lora(sql_lora_files):
llm = vllm.LLM(
MODEL_PATH,
tokenizer=sql_lora_files,
enable_lora=True,
# also test odd max_num_seqs
max_num_seqs=13,
@@ -123,6 +105,7 @@ def test_llama_lora_tp4(sql_lora_files):
llm = vllm.LLM(
MODEL_PATH,
tokenizer=sql_lora_files,
enable_lora=True,
max_num_seqs=16,
max_loras=4,
@@ -137,6 +120,7 @@ def test_llama_lora_tp4_fully_sharded_loras(sql_lora_files):
llm = vllm.LLM(
MODEL_PATH,
tokenizer=sql_lora_files,
enable_lora=True,
max_num_seqs=16,
max_loras=4,
@@ -184,6 +168,7 @@ def test_tp2_serialize_and_deserialize_lora(tmp_path, sql_lora_files,
tensorizer_config = TensorizerConfig(tensorizer_uri=str(model_uri))
loaded_llm = LLM(model=model_ref,
tokenizer=sql_lora_files,
load_format="tensorizer",
enable_lora=True,
enforce_eager=True,
@@ -195,11 +180,6 @@ def test_tp2_serialize_and_deserialize_lora(tmp_path, sql_lora_files,
tc_as_dict = tensorizer_config.to_serializable()
print("lora adapter created")
assert do_sample(loaded_llm,
sql_lora_files,
tensorizer_config_dict=tc_as_dict,
lora_id=0) == EXPECTED_NO_LORA_OUTPUT
print("lora 1")
assert do_sample(loaded_llm,
sql_lora_files,