91 lines
2.8 KiB
Python
91 lines
2.8 KiB
Python
# Copyright 2023-2024 SGLang Team
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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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import multiprocessing as mp
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import os
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import unittest
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from typing import List
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from utils import (
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ALL_OTHER_MULTI_LORA_MODELS,
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BACKENDS,
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CI_MULTI_LORA_MODELS,
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TORCH_DTYPES,
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LoRAModelCase,
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run_lora_test_one_by_one,
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)
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from sglang.test.test_utils import CustomTestCase, is_in_ci
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# All prompts are used at once in a batch.
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PROMPTS = [
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"AI is a field of computer science focused on",
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"""
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### Instruction:
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Tell me about llamas and alpacas
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### Response:
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Llamas are large, long-necked animals with a woolly coat. They have two toes on each foot instead of three like other camelids.
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### Question:
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What do you know about llamas?
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### Answer:
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""",
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]
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class TestMultiLoRABackend(CustomTestCase):
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def _run_multi_lora_test_on_model_cases(self, model_cases: List[LoRAModelCase]):
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for model_case in model_cases:
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# If skip_long_prompt is True, filter out prompts longer than 1000 characters.
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batch_prompts = (
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PROMPTS
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if not model_case.skip_long_prompt
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else [p for p in PROMPTS if len(p) < 1000]
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)
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for torch_dtype in TORCH_DTYPES:
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for backend in BACKENDS:
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run_lora_test_one_by_one(
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batch_prompts,
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model_case,
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torch_dtype,
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max_new_tokens=32,
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backend=backend,
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test_tag="multi-lora-backend",
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)
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def test_ci_lora_models(self):
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self._run_multi_lora_test_on_model_cases(CI_MULTI_LORA_MODELS)
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def test_all_lora_models(self):
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if is_in_ci():
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return
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# Retain ONLY_RUN check here
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filtered_models = []
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for model_case in ALL_OTHER_MULTI_LORA_MODELS:
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if "ONLY_RUN" in os.environ and os.environ["ONLY_RUN"] != model_case.base:
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continue
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filtered_models.append(model_case)
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self._run_multi_lora_test_on_model_cases(filtered_models)
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if __name__ == "__main__":
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try:
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mp.set_start_method("spawn")
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except RuntimeError:
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pass
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unittest.main(warnings="ignore")
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