[Frontend] Add /v1/audio/transcriptions OpenAI API endpoint (#12909)
This commit is contained in:
86
tests/entrypoints/openai/correctness/test_lmeval.py
Normal file
86
tests/entrypoints/openai/correctness/test_lmeval.py
Normal file
@@ -0,0 +1,86 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""
|
||||
This file test accuracy of the vLLM server via LMEval.
|
||||
It uses local-completions, which interacts with vLLM
|
||||
through the OAI API with N concurrent connections.
|
||||
This simulates real work usage of the API and makes
|
||||
sure that the zmq frontend mp RPC message passing and
|
||||
AsyncLLMEngine are working correctly.
|
||||
"""
|
||||
|
||||
import lm_eval
|
||||
import pytest
|
||||
|
||||
from vllm.platforms import current_platform
|
||||
|
||||
from ....utils import RemoteOpenAIServer
|
||||
|
||||
MODEL_NAME = "Qwen/Qwen2-1.5B-Instruct"
|
||||
NUM_CONCURRENT = 500
|
||||
TASK = "gsm8k"
|
||||
FILTER = "exact_match,strict-match"
|
||||
RTOL = 0.03
|
||||
EXPECTED_VALUE = 0.58
|
||||
DEFAULT_ARGS = ["--max-model-len", "2048", "--disable-log-requests"]
|
||||
MORE_ARGS_LIST = [
|
||||
[], # Default
|
||||
["--enable-chunked-prefill"], # Chunked
|
||||
["--num-scheduler-steps", "8"], # MS
|
||||
["--num-scheduler-steps", "8", "--multi-step-stream-outputs"] # MS+Stream
|
||||
]
|
||||
MAX_WAIT_SECONDS = None
|
||||
|
||||
if current_platform.is_tpu():
|
||||
MORE_ARGS_LIST = [
|
||||
[], # Default
|
||||
# ["--num-scheduler-steps", "8"], # Multi-step << currently fails
|
||||
]
|
||||
MAX_WAIT_SECONDS = 600
|
||||
|
||||
|
||||
def run_test(more_args):
|
||||
"""Run the end to end accuracy test."""
|
||||
|
||||
args = list(DEFAULT_ARGS)
|
||||
args.extend(more_args)
|
||||
print(f"Running with: {args}")
|
||||
|
||||
with RemoteOpenAIServer(
|
||||
MODEL_NAME, args,
|
||||
max_wait_seconds=MAX_WAIT_SECONDS) as remote_server:
|
||||
url = f"{remote_server.url_for('v1')}/completions"
|
||||
|
||||
model_args = (
|
||||
f"model={MODEL_NAME},"
|
||||
f"base_url={url},"
|
||||
f"num_concurrent={NUM_CONCURRENT},tokenized_requests=False")
|
||||
|
||||
results = lm_eval.simple_evaluate(
|
||||
model="local-completions",
|
||||
model_args=model_args,
|
||||
tasks=TASK,
|
||||
)
|
||||
|
||||
measured_value = results["results"][TASK][FILTER]
|
||||
assert (measured_value - RTOL < EXPECTED_VALUE
|
||||
and measured_value + RTOL > EXPECTED_VALUE
|
||||
), f"Expected: {EXPECTED_VALUE} | Measured: {measured_value}"
|
||||
|
||||
|
||||
@pytest.mark.skipif(not current_platform.is_cuda(),
|
||||
reason="V1 currently only supported on CUDA")
|
||||
def test_lm_eval_accuracy_v1_engine(monkeypatch):
|
||||
"""Run with the V1 Engine."""
|
||||
|
||||
with monkeypatch.context() as m:
|
||||
m.setenv("VLLM_USE_V1", "1")
|
||||
run_test([])
|
||||
|
||||
|
||||
@pytest.mark.parametrize("more_args", MORE_ARGS_LIST)
|
||||
def test_lm_eval_accuracy_v0_engine(monkeypatch, more_args):
|
||||
"""Run with the V0 Engine."""
|
||||
|
||||
with monkeypatch.context() as m:
|
||||
m.setenv("VLLM_USE_V1", "0")
|
||||
run_test(more_args)
|
||||
Reference in New Issue
Block a user