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128 lines
4.3 KiB
128 lines
4.3 KiB
# Copyright (c) 2020 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 glob |
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import os |
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import platform |
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import subprocess |
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import sys |
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import cv2 |
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import paddle |
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import paddlers.models.ppseg as ppseg |
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IS_WINDOWS = sys.platform == 'win32' |
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def _find_cuda_home(): |
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'''Finds the CUDA install path. It refers to the implementation of |
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pytorch <https://github.com/pytorch/pytorch/blob/master/torch/utils/cpp_extension.py>. |
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''' |
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# Guess #1 |
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cuda_home = os.environ.get('CUDA_HOME') or os.environ.get('CUDA_PATH') |
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if cuda_home is None: |
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# Guess #2 |
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try: |
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which = 'where' if IS_WINDOWS else 'which' |
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nvcc = subprocess.check_output([which, |
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'nvcc']).decode().rstrip('\r\n') |
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cuda_home = os.path.dirname(os.path.dirname(nvcc)) |
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except Exception: |
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# Guess #3 |
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if IS_WINDOWS: |
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cuda_homes = glob.glob( |
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'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*') |
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if len(cuda_homes) == 0: |
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cuda_home = '' |
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else: |
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cuda_home = cuda_homes[0] |
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else: |
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cuda_home = '/usr/local/cuda' |
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if not os.path.exists(cuda_home): |
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cuda_home = None |
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return cuda_home |
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def _get_nvcc_info(cuda_home): |
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if cuda_home is not None and os.path.isdir(cuda_home): |
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try: |
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nvcc = os.path.join(cuda_home, 'bin/nvcc') |
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if not IS_WINDOWS: |
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nvcc = subprocess.check_output( |
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"{} -V".format(nvcc), shell=True).decode() |
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else: |
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nvcc = subprocess.check_output( |
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"\"{}\" -V".format(nvcc), shell=True).decode() |
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nvcc = nvcc.strip().split('\n')[-1] |
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except subprocess.SubprocessError: |
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nvcc = "Not Available" |
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else: |
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nvcc = "Not Available" |
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return nvcc |
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def _get_gpu_info(): |
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try: |
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gpu_info = subprocess.check_output(['nvidia-smi', |
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'-L']).decode().strip() |
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gpu_info = gpu_info.split('\n') |
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for i in range(len(gpu_info)): |
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gpu_info[i] = ' '.join(gpu_info[i].split(' ')[:4]) |
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except: |
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gpu_info = ' Can not get GPU information. Please make sure CUDA have been installed successfully.' |
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return gpu_info |
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def get_sys_env(): |
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"""collect environment information""" |
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env_info = {} |
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env_info['platform'] = platform.platform() |
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env_info['Python'] = sys.version.replace('\n', '') |
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# TODO is_compiled_with_cuda() has not been moved |
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compiled_with_cuda = paddle.is_compiled_with_cuda() |
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env_info['Paddle compiled with cuda'] = compiled_with_cuda |
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if compiled_with_cuda: |
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cuda_home = _find_cuda_home() |
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env_info['NVCC'] = _get_nvcc_info(cuda_home) |
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# refer to https://github.com/PaddlePaddle/Paddle/blob/release/2.0-rc/paddle/fluid/platform/device_context.cc#L327 |
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v = paddle.get_cudnn_version() |
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v = str(v // 1000) + '.' + str(v % 1000 // 100) |
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env_info['cudnn'] = v |
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if 'gpu' in paddle.get_device(): |
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gpu_nums = paddle.distributed.ParallelEnv().nranks |
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else: |
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gpu_nums = 0 |
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env_info['GPUs used'] = gpu_nums |
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env_info['CUDA_VISIBLE_DEVICES'] = os.environ.get( |
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'CUDA_VISIBLE_DEVICES') |
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if gpu_nums == 0: |
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os.environ['CUDA_VISIBLE_DEVICES'] = '' |
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env_info['GPU'] = _get_gpu_info() |
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try: |
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gcc = subprocess.check_output(['gcc', '--version']).decode() |
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gcc = gcc.strip().split('\n')[0] |
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env_info['GCC'] = gcc |
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except: |
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pass |
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env_info['PaddleSeg'] = ppseg.__version__ |
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env_info['PaddlePaddle'] = paddle.__version__ |
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env_info['OpenCV'] = cv2.__version__ |
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return env_info
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