6ace6fba2c
Signed-off-by: Nick Hill <nickhill@us.ibm.com> Signed-off-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Signed-off-by: Nick Hill <nhill@redhat.com> Co-authored-by: Nick Hill <nickhill@us.ibm.com> Co-authored-by: Varun Sundar Rabindranath <varun@neuralmagic.com> Co-authored-by: Nick Hill <nhill@redhat.com> Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com>
86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
"""
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This file test accuracy of the vLLM server via LMEval.
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It uses local-completions, which interacts with vLLM
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through the OAI API with N concurrent connections.
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This simulates real work usage of the API and makes
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sure that the zmq frontend mp RPC message passing and
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AsyncLLMEngine are working correctly.
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"""
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import lm_eval
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import pytest
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from vllm.platforms import current_platform
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from ...utils import RemoteOpenAIServer
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MODEL_NAME = "Qwen/Qwen2-1.5B-Instruct"
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NUM_CONCURRENT = 500
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TASK = "gsm8k"
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FILTER = "exact_match,strict-match"
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RTOL = 0.03
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EXPECTED_VALUE = 0.58
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DEFAULT_ARGS = ["--max-model-len", "2048", "--disable-log-requests"]
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MORE_ARGS_LIST = [
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[], # Default
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["--enable-chunked-prefill"], # Chunked
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["--num-scheduler-steps", "8"], # MS
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["--num-scheduler-steps", "8", "--multi-step-stream-outputs"] # MS+Stream
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]
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MAX_WAIT_SECONDS = None
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if current_platform.is_tpu():
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MORE_ARGS_LIST = [
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[], # Default
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# ["--num-scheduler-steps", "8"], # Multi-step << currently fails
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]
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MAX_WAIT_SECONDS = 600
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def run_test(more_args):
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"""Run the end to end accuracy test."""
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args = list(DEFAULT_ARGS)
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args.extend(more_args)
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print(f"Running with: {args}")
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with RemoteOpenAIServer(
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MODEL_NAME, args,
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max_wait_seconds=MAX_WAIT_SECONDS) as remote_server:
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url = f"{remote_server.url_for('v1')}/completions"
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model_args = (
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f"model={MODEL_NAME},"
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f"base_url={url},"
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f"num_concurrent={NUM_CONCURRENT},tokenized_requests=False")
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results = lm_eval.simple_evaluate(
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model="local-completions",
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model_args=model_args,
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tasks=TASK,
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)
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measured_value = results["results"][TASK][FILTER]
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assert (measured_value - RTOL < EXPECTED_VALUE
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and measured_value + RTOL > EXPECTED_VALUE
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), f"Expected: {EXPECTED_VALUE} | Measured: {measured_value}"
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@pytest.mark.skipif(not current_platform.is_cuda(),
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reason="V1 currently only supported on CUDA")
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def test_lm_eval_accuracy_v1_engine(monkeypatch):
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"""Run with the V1 Engine."""
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with monkeypatch.context() as m:
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m.setenv("VLLM_USE_V1", "1")
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run_test([])
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@pytest.mark.parametrize("more_args", MORE_ARGS_LIST)
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def test_lm_eval_accuracy_v0_engine(monkeypatch, more_args):
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"""Run with the V0 Engine."""
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with monkeypatch.context() as m:
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m.setenv("VLLM_USE_V1", "0")
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run_test(more_args)
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