wehub-resource-sync
113 lines
3.2 KiB
Python
113 lines
3.2 KiB
Python
# Copyright (c) 2022 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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from __future__ import annotations
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import json
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import os
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import sys
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import unittest
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from parameterized import parameterized_class
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from paddlenlp.utils.env import SAFE_OPTIMIZER_INDEX_NAME
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from tests.parallel_launch import TestMultipleGpus
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from tests.testing_utils import argv_context_guard, load_test_config
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from .testing_utils import LLMTest
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@parameterized_class(
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["model_dir"],
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[
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["llama"],
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["chatglm"],
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# ["bloom"], @skip("Skip and wait to fix.")
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["chatglm2"],
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["qwen"],
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["qwen2"],
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["baichuan"],
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],
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)
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class FinetuneTest(LLMTest, unittest.TestCase):
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config_path: str = "./tests/fixtures/llm/finetune.yaml"
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model_dir: str = None
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def setUp(self) -> None:
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LLMTest.setUp(self)
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sys.path.insert(0, self.model_dir)
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def tearDown(self) -> None:
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LLMTest.tearDown(self)
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def test_finetune(self):
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finetune_config = load_test_config(self.config_path, "finetune", self.model_dir)
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finetune_config["dataset_name_or_path"] = self.data_dir
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finetune_config["output_dir"] = self.output_dir
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with argv_context_guard(finetune_config):
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from run_finetune import main
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main()
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# TODO(wj-Mcat): disable chatglm2 test temporarily
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if self.model_dir not in ["qwen", "qwen2", "baichuan", "chatglm2"]:
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self.run_predictor({"inference_model": True})
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self.run_predictor({"inference_model": False})
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@parameterized_class(
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["model_dir"],
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[
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["llama"],
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],
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)
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class CkptQuantTest(LLMTest, TestMultipleGpus):
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config_path: str = "./tests/fixtures/llm/finetune.yaml"
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model_dir: str = None
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def setUp(self) -> None:
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LLMTest.setUp(self)
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sys.path.insert(0, self.model_dir)
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self.run_sft = "llm/run_finetune.py"
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def tearDown(self) -> None:
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LLMTest.tearDown(self)
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def test_ckpt_quant(self):
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finetune_config = load_test_config(self.config_path, "ckpt_quant", self.model_dir)
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finetune_config["dataset_name_or_path"] = self.data_dir
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finetune_config["output_dir"] = self.output_dir
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self.runfirst(finetune_config)
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# get `quant_ckpt_resume_times`
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with open(os.path.join(self.output_dir, "checkpoint-1", SAFE_OPTIMIZER_INDEX_NAME), "r") as r:
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index = json.loads(r.read())
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quant_ckpt_resume_times = index["quant_ckpt_resume_times"]
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self.rerun(finetune_config)
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self.assertEqual(quant_ckpt_resume_times, 0)
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def runfirst(self, train_args):
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self.run_n1c2(self.run_sft, **train_args)
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def rerun(self, train_args):
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self.run_n1c2(self.run_sft, **train_args)
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