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* Update TensorRT-LLM --------- Co-authored-by: Tltin <TltinDeng01@gmail.com> Co-authored-by: zhaohb <zhaohbcloud@126.com> Co-authored-by: Bradley Heilbrun <brad@repl.it> Co-authored-by: nqbao11 <nqbao11.01@gmail.com> Co-authored-by: Nikhil Varghese <nikhil@bot-it.ai>
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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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 time
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import pynvml
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def get_memory_info(handle):
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mem_info = pynvml.nvmlDeviceGetMemoryInfo(handle,
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version=pynvml.nvmlMemory_v2)
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total = round(mem_info.total / 1024 / 1024 / 1024, 2)
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used = round(mem_info.used / 1024 / 1024 / 1024, 2)
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free = round(mem_info.free / 1024 / 1024 / 1024, 2)
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return total, used, free
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def mem_monitor(q1, q2):
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pynvml.nvmlInit()
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handle = pynvml.nvmlDeviceGetHandleByIndex(0)
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peak_used = 0
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while q1.empty():
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_, used, _ = get_memory_info(handle)
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peak_used = max(used, peak_used)
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time.sleep(0.1)
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pynvml.nvmlShutdown()
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q2.put(peak_used)
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