dump environment info

dygraph/infer.py

@@ -84,7 +84,7 @@ def parse_args():
 def main(args):
     env_info = get_environ_info()
     places = fluid.CUDAPlace(ParallelEnv().dev_id) \
-        if env_info['place'] == 'cuda' and fluid.is_compiled_with_cuda() \
+        if env_info['Paddle compiled with cuda'] and env_info['GPUs used'] \
         else fluid.CPUPlace()
 
     if args.dataset not in DATASETS:

dygraph/train.py

@@ -21,6 +21,7 @@ from dygraph.datasets import DATASETS
 import dygraph.transforms as T
 from dygraph.models import MODELS
 from dygraph.utils import get_environ_info
+from dygraph.utils import logger
 from dygraph.core import train
 
 
@@ -129,8 +130,13 @@ def parse_args():
 
 def main(args):
     env_info = get_environ_info()
+    info = ['{}: {}'.format(k, v) for k, v in env_info.items()]
+    info = '\n'.join(['\n', format('Environment Information', '-^48s')] + info +
+                     ['-' * 48])
+    logger.info(info)
+
     places = fluid.CUDAPlace(ParallelEnv().dev_id) \
-        if env_info['place'] == 'cuda' and fluid.is_compiled_with_cuda() \
+        if env_info['Paddle compiled with cuda'] and env_info['GPUs used'] \
         else fluid.CPUPlace()
 
     if args.dataset not in DATASETS:

dygraph/utils/__init__.py

@@ -17,3 +17,4 @@ from . import download
 from .metrics import ConfusionMatrix
 from .utils import *
 from .timer import Timer, calculate_eta
+from .get_environ_info import get_environ_info

dygraph/utils/get_environ_info.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import sys
+from collections import OrderedDict
+import subprocess
+import glob
+
+import paddle
+import paddle.fluid as fluid
+import cv2
+
+IS_WINDOWS = sys.platform == 'win32'
+
+
+def _find_cuda_home():
+    '''Finds the CUDA install path. It refers to the implementation of
+    pytorch <https://github.com/pytorch/pytorch/blob/master/torch/utils/cpp_extension.py>.
+    '''
+    # Guess #1
+    cuda_home = os.environ.get('CUDA_HOME') or os.environ.get('CUDA_PATH')
+    if cuda_home is None:
+        # Guess #2
+        try:
+            which = 'where' if IS_WINDOWS else 'which'
+            nvcc = subprocess.check_output([which,
+                                            'nvcc']).decode().rstrip('\r\n')
+            cuda_home = os.path.dirname(os.path.dirname(nvcc))
+        except Exception:
+            # Guess #3
+            if IS_WINDOWS:
+                cuda_homes = glob.glob(
+                    'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*')
+                if len(cuda_homes) == 0:
+                    cuda_home = ''
+                else:
+                    cuda_home = cuda_homes[0]
+            else:
+                cuda_home = '/usr/local/cuda'
+            if not os.path.exists(cuda_home):
+                cuda_home = None
+    return cuda_home
+
+
+def _get_nvcc_info(cuda_home):
+    if cuda_home is not None and os.path.isdir(cuda_home):
+        try:
+            nvcc = os.path.join(cuda_home, 'bin/nvcc')
+            nvcc = subprocess.check_output(
+                "{} -V".format(nvcc), shell=True).decode()
+            nvcc = nvcc.strip().split('\n')[-1]
+        except subprocess.SubprocessError:
+            nvcc = "Not Available"
+    return nvcc
+
+
+def _get_gpu_info():
+    gpu_info = subprocess.check_output(['nvidia-smi', '-L']).decode().strip()
+    gpu_info = gpu_info.split('\n')
+    for i in range(len(gpu_info)):
+        gpu_info[i] = ' '.join(gpu_info[i].split(' ')[:4])
+    return gpu_info
+
+
+def get_environ_info():
+    """collect environment information"""
+    env_info = {}
+    env_info['system platform'] = sys.platform
+    if env_info['system platform'] == 'linux':
+        lsb_v = subprocess.check_output(['lsb_release', '-v']).decode().strip()
+        lsb_v = lsb_v.replace('\t', ' ')
+        lsb_d = subprocess.check_output(['lsb_release', '-d']).decode().strip()
+        lsb_d = lsb_d.replace('\t', ' ')
+        env_info['LSB'] = [lsb_v, lsb_d]
+
+    env_info['Python'] = sys.version.replace('\n', '')
+
+    compiled_with_cuda = paddle.fluid.is_compiled_with_cuda()
+    env_info['Paddle compiled with cuda'] = compiled_with_cuda
+
+    if compiled_with_cuda:
+        cuda_home = _find_cuda_home()
+        env_info['cuda home'] = cuda_home
+        env_info['nvcc'] = _get_nvcc_info(cuda_home)
+        gpu_nums = fluid.core.get_cuda_device_count()
+        env_info['GPUs used'] = gpu_nums
+        env_info['CUDA_VISIBLE_DEVICES'] = os.environ.get(
+            'CUDA_VISIBLE_DEVICES')
+        env_info['GPU'] = _get_gpu_info()
+
+    gcc = subprocess.check_output(['gcc', '--version']).decode()
+    gcc = gcc.strip().split('\n')[0]
+    env_info['gcc'] = gcc
+
+    env_info['Paddle'] = paddle.__version__
+    env_info['OpenCV'] = cv2.__version__
+
+    return env_info
+
+
+if __name__ == '__main__':
+    env_info = get_environ_info()
+    for k, v in env_info.items():
+        print('{}: {}'.format(k, v))

dygraph/val.py

@@ -72,7 +72,7 @@ def parse_args():
 def main(args):
     env_info = get_environ_info()
     places = fluid.CUDAPlace(ParallelEnv().dev_id) \
-        if env_info['place'] == 'cuda' and fluid.is_compiled_with_cuda() \
+        if env_info['Paddle compiled with cuda'] and env_info['GPUs used'] \
         else fluid.CPUPlace()
 
     if args.dataset not in DATASETS: