mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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bukejiyu
127 lines
3.6 KiB
Python
127 lines
3.6 KiB
Python
# Copyright (c) 2026 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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import os
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import sys
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import pytest
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.abspath(os.path.join(current_dir, ".."))
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if project_root not in sys.path:
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sys.path.insert(0, project_root)
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from model_loader.utils import (
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form_model_get_output_topp0,
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get_paddle_model_path,
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run_with_timeout,
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)
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os.environ["FD_PD_REORDER"] = "1"
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model_param_map = {
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"ernie-4_5-21b-a3b-bf16-paddle": {
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"tensor_parallel_size": 2,
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"quantizations": [None],
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"max_num_seqs": 3,
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"graph_optimization_config": {"use_cudagraph": False},
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"env": {"FD_PD_REORDER": "1"},
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}
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}
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prompts = [
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"解释下温故而知新",
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"Hello, my name is",
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"鲁迅是谁",
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"将李白的静夜思改为现代诗歌",
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"你好",
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"请介绍下你自己",
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]
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params = []
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for model, cfg in model_param_map.items():
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for q in cfg["quantizations"]:
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if isinstance(q, dict):
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quant, backend, env = q["quant_type"], q.get("backend", "default"), q.get("env", {})
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else:
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quant, backend, env = q, "default", {}
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params.append(
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pytest.param(
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model,
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cfg.get("tensor_parallel_size", 1),
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cfg.get("max_num_seqs", 1),
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cfg.get("max_model_len", 1024),
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quant,
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cfg.get("max_tokens", 128),
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env,
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marks=[pytest.mark.core_model],
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id=f"{model}.{quant}.{backend}",
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)
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)
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@pytest.mark.parametrize(
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"model_name_or_path,tensor_parallel_size,max_num_seqs,max_model_len,quantization,max_tokens,env",
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params,
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)
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def test_model_against_baseline(
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fd_runner,
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model_name_or_path: str,
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tensor_parallel_size: int,
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max_num_seqs: int,
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max_model_len: int,
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max_tokens: int,
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quantization: str,
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env,
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monkeypatch,
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) -> None:
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"""
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Test that model output matches baseline file.
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"""
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model_path = get_paddle_model_path(model_name_or_path)
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for k, v in env.items():
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monkeypatch.setenv(k, v)
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# Run model
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_ = run_with_timeout(
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target=form_model_get_output_topp0,
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args=(
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fd_runner,
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model_path,
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tensor_parallel_size,
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max_num_seqs,
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max_model_len,
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max_tokens,
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quantization,
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"dummy",
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prompts,
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),
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)
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mtp_model_path = os.path.join(model_path, "mtp")
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speculative_config = {"method": "mtp", "num_speculative_tokens": 1, "model": mtp_model_path}
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_ = run_with_timeout(
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target=form_model_get_output_topp0,
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kwargs={
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"fd_runner": fd_runner,
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"model_path": model_path,
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"tensor_parallel_size": tensor_parallel_size,
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"max_num_seqs": max_num_seqs,
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"max_model_len": max_model_len,
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"max_tokens": max_tokens,
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"quantization": quantization,
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"load_choices": "dummy",
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"prompts": prompts,
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"speculative_config": speculative_config,
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},
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)
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