mirror of
https://github.com/vllm-project/vllm-ascend.git
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787010a637
V1 is enabled by default, no need to set it by hand now. This PR remove
the useless setting in example and tests
- vLLM version: v0.9.2
- vLLM main:
9ad0a4588b
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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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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# This file is a part of the vllm-ascend project.
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#
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import os
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import torch
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from vllm import LLM, SamplingParams
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from vllm.utils import GiB_bytes
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os.environ["VLLM_USE_MODELSCOPE"] = "True"
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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if __name__ == "__main__":
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prompt = "How are you?"
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free, total = torch.npu.mem_get_info()
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print(f"Free memory before sleep: {free / 1024 ** 3:.2f} GiB")
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# record npu memory use baseline in case other process is running
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used_bytes_baseline = total - free
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llm = LLM("Qwen/Qwen2.5-0.5B-Instruct", enable_sleep_mode=True)
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sampling_params = SamplingParams(temperature=0, max_tokens=10)
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output = llm.generate(prompt, sampling_params)
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llm.sleep(level=1)
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free_npu_bytes_after_sleep, total = torch.npu.mem_get_info()
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print(
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f"Free memory after sleep: {free_npu_bytes_after_sleep / 1024 ** 3:.2f} GiB"
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)
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used_bytes = total - free_npu_bytes_after_sleep - used_bytes_baseline
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# now the memory usage should be less than the model weights
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# (0.5B model, 1GiB weights)
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assert used_bytes < 1 * GiB_bytes
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llm.wake_up()
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output2 = llm.generate(prompt, sampling_params)
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# cmp output
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assert output[0].outputs[0].text == output2[0].outputs[0].text
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