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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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9
tests/entrypoints/openai/test_chat.py
View File

@@ -29,11 +29,7 @@ def monkeypatch_module():
@pytest.fixture(scope="module", params=[False, True])
def server(
request,
monkeypatch_module,
zephyr_lora_files, #noqa: F811
zephyr_lora_added_tokens_files): # noqa: F811
def server(request, monkeypatch_module, zephyr_lora_files): #noqa: F811
use_v1 = request.param
monkeypatch_module.setenv('VLLM_USE_V1', '1' if use_v1 else '0')
@@ -49,7 +45,6 @@ def server(
"--enable-lora",
"--lora-modules",
f"zephyr-lora={zephyr_lora_files}",
f"zephyr-lora2={zephyr_lora_added_tokens_files}",
"--max-lora-rank",
"64",
"--max-cpu-loras",
@@ -79,7 +74,7 @@ async def client(server):
@pytest.mark.parametrize(
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_no_logprobs_chat(client: openai.AsyncOpenAI, model_name: str):
messages = [{

23
tests/entrypoints/openai/test_completion.py
View File

@@ -27,7 +27,7 @@ GUIDED_DECODING_BACKENDS = ["outlines", "xgrammar", "guidance"]
@pytest.fixture(scope="module")
def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files):
def default_server_args(zephyr_lora_files):
return [
# use half precision for speed and memory savings in CI environment
"--dtype",
@@ -41,7 +41,6 @@ def default_server_args(zephyr_lora_files, zephyr_lora_added_tokens_files):
"--enable-lora",
"--lora-modules",
f"zephyr-lora={zephyr_lora_files}",
f"zephyr-lora2={zephyr_lora_added_tokens_files}",
"--max-lora-rank",
"64",
"--max-cpu-loras",
@@ -87,7 +86,7 @@ async def client(server):
@pytest.mark.parametrize(
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_single_completion(client: openai.AsyncOpenAI, model_name: str):
completion = await client.completions.create(model=model_name,
@@ -115,20 +114,6 @@ async def test_single_completion(client: openai.AsyncOpenAI, model_name: str):
assert completion.choices[0].prompt_logprobs is None
@pytest.mark.asyncio
async def test_added_lora_tokens(client: openai.AsyncOpenAI):
# test using token IDs
completion = await client.completions.create(
model="zephyr-lora2",
prompt=[0, 0, 32000, 32001, 32002],
echo=True,
max_tokens=5,
temperature=0.0,
)
# Added tokens should appear in tokenized prompt
assert completion.choices[0].text.startswith("<unk><unk>vllm1vllm2vllm3")
@pytest.mark.asyncio
async def test_added_lora_tokens_base_model(client: openai.AsyncOpenAI):
# test using token IDs
@@ -147,7 +132,7 @@ async def test_added_lora_tokens_base_model(client: openai.AsyncOpenAI):
@pytest.mark.parametrize(
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
[MODEL_NAME, "zephyr-lora"],
)
async def test_no_logprobs(client: openai.AsyncOpenAI, model_name: str):
# test using token IDs
@@ -713,7 +698,7 @@ async def test_guided_grammar(client: openai.AsyncOpenAI,
@pytest.mark.parametrize(
# first test base model, then test loras
"model_name",
[MODEL_NAME, "zephyr-lora", "zephyr-lora2"],
[MODEL_NAME, "zephyr-lora"],
)
@pytest.mark.parametrize("logprobs_arg", [1, 0])
async def test_echo_logprob_completion(client: openai.AsyncOpenAI,

5
tests/entrypoints/openai/test_completion_with_prompt_embeds.py
View File

@@ -21,10 +21,7 @@ CONFIG = AutoConfig.from_pretrained(MODEL_NAME)
@pytest.fixture(scope="module")
def default_server_args(
zephyr_lora_files,
zephyr_lora_added_tokens_files,
) -> list[str]:
def default_server_args() -> list[str]:
return [
# use half precision for speed and memory savings in CI environment
"--dtype",

10
tests/entrypoints/openai/test_lora_adapters.py
View File

@@ -67,12 +67,6 @@ def server_with_lora_modules_json(request, monkeypatch_module,
"base_model_name": MODEL_NAME
}
lora_module_2 = {
"name": "zephyr-lora2",
"path": zephyr_lora_files,
"base_model_name": MODEL_NAME
}
args = [
# use half precision for speed and memory savings in CI environment
"--dtype",
@@ -84,7 +78,6 @@ def server_with_lora_modules_json(request, monkeypatch_module,
"--enable-lora",
"--lora-modules",
json.dumps(lora_module_1),
json.dumps(lora_module_2),
"--max-lora-rank",
"64",
"--max-cpu-loras",
@@ -121,7 +114,6 @@ async def test_static_lora_lineage(client: openai.AsyncOpenAI,
for lora_model in lora_models)
assert all(lora_model.parent == MODEL_NAME for lora_model in lora_models)
assert lora_models[0].id == "zephyr-lora"
assert lora_models[1].id == "zephyr-lora2"
@pytest.mark.asyncio
@@ -209,7 +201,7 @@ async def test_dynamic_lora_badrequests(client: openai.AsyncOpenAI, tmp_path,
@pytest.mark.asyncio
async def test_multiple_lora_adapters(client: openai.AsyncOpenAI, tmp_path,
zephyr_lora_files):
"""Validate that many loras can be dynamically registered and inferenced
"""Validate that many loras can be dynamically registered and inferenced
with concurrently"""
# This test file configures the server with --max-cpu-loras=2 and this test

2
tests/entrypoints/openai/test_models.py
View File

@@ -26,7 +26,6 @@ def server(zephyr_lora_files):
"--enable-lora",
"--lora-modules",
f"zephyr-lora={zephyr_lora_files}",
f"zephyr-lora2={zephyr_lora_files}",
"--max-lora-rank",
"64",
"--max-cpu-loras",
@@ -56,4 +55,3 @@ async def test_check_models(client: openai.AsyncOpenAI, zephyr_lora_files):
assert all(lora_model.root == zephyr_lora_files
for lora_model in lora_models)
assert lora_models[0].id == "zephyr-lora"
assert lora_models[1].id == "zephyr-lora2"

28
tests/entrypoints/openai/test_tokenization.py
View File

@@ -14,7 +14,7 @@ MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
@pytest.fixture(scope="module")
def server(zephyr_lora_added_tokens_files: str): # noqa: F811
def server():
args = [
# use half precision for speed and memory savings in CI environment
"--dtype",
@@ -24,12 +24,6 @@ def server(zephyr_lora_added_tokens_files: str): # noqa: F811
"--enforce-eager",
"--max-num-seqs",
"128",
# lora config
"--enable-lora",
"--lora-modules",
f"zephyr-lora2={zephyr_lora_added_tokens_files}",
"--max-lora-rank",
"64",
"--enable-tokenizer-info-endpoint",
]
@@ -38,10 +32,8 @@ def server(zephyr_lora_added_tokens_files: str): # noqa: F811
@pytest.fixture(scope="module")
def tokenizer_name(model_name: str,
zephyr_lora_added_tokens_files: str): # noqa: F811
return zephyr_lora_added_tokens_files if (
model_name == "zephyr-lora2") else model_name
def tokenizer_name(model_name: str):
return model_name
@pytest_asyncio.fixture
@@ -53,7 +45,7 @@ async def client(server):
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name,tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_tokenize_completions(
@@ -86,7 +78,7 @@ async def test_tokenize_completions(
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name,tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_tokenize_chat(
@@ -148,7 +140,7 @@ async def test_tokenize_chat(
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name,tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_tokenize_chat_with_tools(
@@ -225,7 +217,7 @@ async def test_tokenize_chat_with_tools(
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name, tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_tokenize_with_return_token_strs(
@@ -260,7 +252,7 @@ async def test_tokenize_with_return_token_strs(
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name,tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_detokenize(
@@ -287,7 +279,7 @@ async def test_detokenize(
@pytest.mark.asyncio
@pytest.mark.parametrize(
"model_name,tokenizer_name",
[(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
[(MODEL_NAME, MODEL_NAME)],
indirect=["tokenizer_name"],
)
async def test_tokenizer_info_basic(
@@ -384,4 +376,4 @@ async def test_tokenizer_info_chat_template(server: RemoteOpenAIServer):
if chat_template:
assert isinstance(chat_template,
str), ("Chat template should be a string")
assert chat_template.strip(), "Chat template should not be empty"
assert chat_template.strip(), "Chat template should not be empty"

2
tests/entrypoints/openai/tool_parsers/test_hermes_tool_parser.py
View File

@@ -18,6 +18,8 @@ SERVER_ARGS = [
"--enable-lora",
"--lora-modules",
f"{LORA_MODEL}={LORA_MODEL}",
"--tokenizer",
f"{LORA_MODEL}",
]
TOOLS = [{