Add env dir for segmentation

paddlers/models/ppseg/utils/env/__init__.py

@@ -0,0 +1,16 @@
+# 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.
+
+from . import seg_env
+from .sys_env import get_sys_env

paddlers/models/ppseg/utils/env/seg_env.py

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+# 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.
+"""
+This module is used to store environmental parameters in PaddleSeg.
+
+SEG_HOME : Root directory for storing PaddleSeg related data. Default to ~/.paddleseg.
+           Users can change the default value through the SEG_HOME environment variable.
+DATA_HOME : The directory to store the automatically downloaded dataset, e.g ADE20K.
+PRETRAINED_MODEL_HOME : The directory to store the automatically downloaded pretrained model.
+"""
+
+import os
+
+from paddlers.models.ppseg.utils import logger
+
+
+def _get_user_home():
+    return os.path.expanduser('~')
+
+
+def _get_seg_home():
+    if 'SEG_HOME' in os.environ:
+        home_path = os.environ['SEG_HOME']
+        if os.path.exists(home_path):
+            if os.path.isdir(home_path):
+                return home_path
+            else:
+                logger.warning('SEG_HOME {} is a file!'.format(home_path))
+        else:
+            return home_path
+    return os.path.join(_get_user_home(), '.paddleseg')
+
+
+def _get_sub_home(directory):
+    home = os.path.join(_get_seg_home(), directory)
+    if not os.path.exists(home):
+        os.makedirs(home, exist_ok=True)
+    return home
+
+
+USER_HOME = _get_user_home()
+SEG_HOME = _get_seg_home()
+DATA_HOME = _get_sub_home('dataset')
+TMP_HOME = _get_sub_home('tmp')
+PRETRAINED_MODEL_HOME = _get_sub_home('pretrained_model')

paddlers/models/ppseg/utils/env/sys_env.py

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+# 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 glob
+import os
+import platform
+import subprocess
+import sys
+
+import cv2
+import paddle
+
+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"
+    else:
+        nvcc = "Not Available"
+    return nvcc
+
+
+def _get_gpu_info():
+    try:
+        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])
+    except:
+        gpu_info = ' Can not get GPU information. Please make sure CUDA have been installed successfully.'
+    return gpu_info
+
+
+def get_sys_env():
+    """collect environment information"""
+    env_info = {}
+    env_info['platform'] = platform.platform()
+
+    env_info['Python'] = sys.version.replace('\n', '')
+
+    # TODO is_compiled_with_cuda() has not been moved
+    compiled_with_cuda = paddle.is_compiled_with_cuda()
+    env_info['Paddle compiled with cuda'] = compiled_with_cuda
+
+    if compiled_with_cuda:
+        cuda_home = _find_cuda_home()
+        env_info['NVCC'] = _get_nvcc_info(cuda_home)
+        # refer to https://github.com/PaddlePaddle/Paddle/blob/release/2.0-rc/paddle/fluid/platform/device_context.cc#L327
+        v = paddle.get_cudnn_version()
+        v = str(v // 1000) + '.' + str(v % 1000 // 100)
+        env_info['cudnn'] = v
+        if 'gpu' in paddle.get_device():
+            gpu_nums = paddle.distributed.ParallelEnv().nranks
+        else:
+            gpu_nums = 0
+        env_info['GPUs used'] = gpu_nums
+
+        env_info['CUDA_VISIBLE_DEVICES'] = os.environ.get(
+            'CUDA_VISIBLE_DEVICES')
+        if gpu_nums == 0:
+            os.environ['CUDA_VISIBLE_DEVICES'] = ''
+        env_info['GPU'] = _get_gpu_info()
+
+    try:
+        gcc = subprocess.check_output(['gcc', '--version']).decode()
+        gcc = gcc.strip().split('\n')[0]
+        env_info['GCC'] = gcc
+    except:
+        pass
+
+    env_info['PaddlePaddle'] = paddle.__version__
+    env_info['OpenCV'] = cv2.__version__
+
+    return env_info