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https://github.com/PaddlePaddle/FastDeploy.git
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30f9f33f34
* add fa deter * add ut * add long sentence * fix basic * fix bugs * fix adn * fix first * fix single * fix single * fix single test * refine * add more test * refine comments * add comments of bmm * fix ci * remove probe * add * remove not need * refine tests * fix comments and refine code * refine code * refine test * refine test * mv 4cards tests * fix tests * add * fix comments * fix cover * fix cover --------- Co-authored-by: gongweibao <gognweibao@baidu.com>
130 lines
3.9 KiB
Python
130 lines
3.9 KiB
Python
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Single-GPU determinism offline inference tests for coverage.
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Simplified from tests/e2e/4cards_cases/test_determinism_offline.py
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for single-GPU coverage testing.
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Usage:
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CUDA_VISIBLE_DEVICES=0 pytest tests/deterministic/test_determinism_offline_single_gpu.py -v
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"""
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import os
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from contextlib import contextmanager
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import pytest
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pytestmark = pytest.mark.gpu
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DEFAULT_MODEL_DIR = "./models"
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MODEL_NAME = "Qwen2-7B-Instruct"
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@contextmanager
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def env_override(mapping):
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"""Temporarily set env vars, restoring original values on exit."""
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old = {k: os.environ.get(k) for k in mapping}
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os.environ.update(mapping)
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try:
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yield
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finally:
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for k, v in old.items():
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if v is None:
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os.environ.pop(k, None)
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else:
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os.environ[k] = v
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@pytest.fixture(scope="module")
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def model_path():
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model_dir = os.getenv("MODEL_PATH", DEFAULT_MODEL_DIR)
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return os.path.join(model_dir, MODEL_NAME)
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@pytest.fixture(autouse=True)
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def _reset_deterministic_mode():
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"""Ensure every test starts with deterministic mode ON."""
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os.environ["FD_DETERMINISTIC_MODE"] = "1"
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yield
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os.environ["FD_DETERMINISTIC_MODE"] = "1"
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# ---------------------------------------------------------------------------
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# Fixtures
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# ---------------------------------------------------------------------------
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@pytest.fixture(scope="module", autouse=True)
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def _module_env():
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"""Set env vars before importing fastdeploy (must happen first)."""
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with env_override(
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{
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"CUDA_VISIBLE_DEVICES": os.environ.get("CUDA_VISIBLE_DEVICES", "0"),
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"FD_DETERMINISTIC_MODE": "1",
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"FD_CUSTOM_AR_MAX_SIZE_MB": "64",
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}
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):
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# Lazy import: env vars must be set before importing fastdeploy
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global LLM, SamplingParams # noqa: PLW0603
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from fastdeploy import LLM, SamplingParams
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yield
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@pytest.fixture(scope="module")
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def llm(model_path, _module_env):
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return LLM(
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model=model_path,
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tensor_parallel_size=1, # Single GPU
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max_model_len=4096,
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enable_prefix_caching=False,
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graph_optimization_config={"use_cudagraph": False},
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)
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _generate_text(llm, prompt, sp):
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"""Generate once, return (text, token_ids)."""
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out = llm.generate([prompt], sp)[0]
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return out.outputs.text, list(out.outputs.token_ids)
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def _assert_deterministic(llm, prompt, sp, runs=2):
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"""Run *runs* times and assert all outputs are identical."""
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results = [_generate_text(llm, prompt, sp) for _ in range(runs)]
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texts = [r[0] for r in results]
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token_ids = [r[1] for r in results]
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assert all(t == texts[0] for t in texts), "Text outputs differ across runs"
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assert all(t == token_ids[0] for t in token_ids), "Token IDs differ across runs"
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return texts[0], token_ids[0]
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# ===================== Core determinism tests =====================
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def test_deterministic_same_prompt(llm):
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"""Same prompt + same seed produces identical output across 3 runs."""
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sp = SamplingParams(temperature=0.8, top_p=0.95, max_tokens=30, seed=123)
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_assert_deterministic(llm, "What is AI?", sp, runs=3)
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if __name__ == "__main__":
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pytest.main(["-sv", __file__])
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