Use `collect_env` from mmcv (#149)

docs/install.md

@@ -7,7 +7,7 @@
 - PyTorch 1.3+
 - CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
 - GCC 5+
-- [mmcv](https://github.com/open-mmlab/mmcv) 0.5.7+
+- [mmcv](https://github.com/open-mmlab/mmcv) 1.1.1+
 - Numpy
 - ffmpeg (4.2 is preferred)
 - [decord](https://github.com/dmlc/decord) (optional): Install CPU version by `pip install decord` and install GPU version from source

mmaction/utils/collect_env.py

-import os.path as osp
-import subprocess
-import sys
-from collections import defaultdict
-
-import cv2
-import mmcv
-import torch
-import torchvision
-from mmcv.utils import CUDA_HOME, get_build_config
+from mmcv.utils import collect_env as collect_basic_env
 
 import mmaction
 
 
 def collect_env():
-    """Collect environment variables."""
-    env_info = {}
-    env_info['sys.platform'] = sys.platform
-    env_info['Python'] = sys.version.replace('\n', '')
-
-    cuda_available = torch.cuda.is_available()
-    env_info['CUDA available'] = cuda_available
-
-    if cuda_available:
-        env_info['CUDA_HOME'] = CUDA_HOME
-
-        if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
-            try:
-                nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
-                nvcc = subprocess.check_output(
-                    '"{}" -V | tail -n1'.format(nvcc), shell=True)
-                nvcc = nvcc.decode('utf-8').strip()
-            except subprocess.SubprocessError:
-                nvcc = 'Not Available'
-            env_info['NVCC'] = nvcc
-
-        devices = defaultdict(list)
-        for k in range(torch.cuda.device_count()):
-            devices[torch.cuda.get_device_name(k)].append(str(k))
-        for name, devids in devices.items():
-            env_info['GPU ' + ','.join(devids)] = name
-
-    gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
-    gcc = gcc.decode('utf-8').strip()
-    env_info['GCC'] = gcc
-
-    env_info['PyTorch'] = torch.__version__
-    env_info['PyTorch compiling details'] = get_build_config()
-    env_info['TorchVision'] = torchvision.__version__
-
-    env_info['OpenCV'] = cv2.__version__
-
-    env_info['MMCV'] = mmcv.__version__
+    env_info = collect_basic_env()
     env_info['MMAction2'] = mmaction.__version__
     return env_info
 

requirements/runtime.txt

 matplotlib
-mmcv
+mmcv>=1.1.1
 numpy
 opencv-contrib-python
 Pillow

setup.cfg

@@ -19,6 +19,6 @@ line_length = 79
 multi_line_output = 0
 known_standard_library = pkg_resources,setuptools
 known_first_party = mmaction
-known_third_party = cv2,joblib,matplotlib,mmcv,numpy,pandas,pytest,scipy,seaborn,torch,torchvision
+known_third_party = cv2,joblib,matplotlib,mmcv,numpy,pandas,pytest,scipy,seaborn,torch
 no_lines_before = STDLIB,LOCALFOLDER
 default_section = THIRDPARTY

tests/test_utils.py

-import os.path as osp
-import subprocess
-import sys
-from collections import defaultdict
-
-import cv2
-import mmcv
-import torch
-import torchvision
-from mmcv.utils import CUDA_HOME, get_build_config
-
-import mmaction
-from mmaction.utils import collect_env
-
-
-def test_collect_env():
-    env_info = collect_env()
-    target_keys = [
-        'sys.platform', 'Python', 'CUDA available', 'GCC', 'PyTorch',
-        'PyTorch compiling details', 'TorchVision', 'OpenCV', 'MMCV',
-        'MMAction2'
-    ]
-    cuda_available = torch.cuda.is_available()
-    if cuda_available:
-        cuda_keys = ['CUDA_HOME', 'NVCC']
-        devices = defaultdict(list)
-        devices_dict = dict()
-        for k in range(torch.cuda.device_count()):
-            devices[torch.cuda.get_device_name(k)].append(str(k))
-        for name, devids in devices.items():
-            devices_dict['GPU ' + ','.join(devids)] = name
-            cuda_keys.append('GPU ' + ','.join(devids))
-        target_keys.extend(cuda_keys)
-
-    assert set(env_info.keys()) == set(target_keys)
-    assert env_info['sys.platform'] == sys.platform
-    assert env_info['Python'] == sys.version.replace('\n', '')
-    assert env_info['CUDA available'] == cuda_available
-    if cuda_available:
-        assert env_info['CUDA_HOME'] == CUDA_HOME
-        if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
-            try:
-                nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
-                nvcc = subprocess.check_output(
-                    '"{}" -V | tail -n1'.format(nvcc), shell=True)
-                nvcc = nvcc.decode('utf-8').strip()
-            except subprocess.SubprocessError:
-                nvcc = 'Not Available'
-            assert env_info['NVCC'] == nvcc
-
-        for k, v in devices_dict.items():
-            assert env_info[k] == v
-
-    gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
-    gcc = gcc.decode('utf-8').strip()
-    assert env_info['GCC'] == gcc
-
-    assert env_info['PyTorch'] == torch.__version__
-    assert env_info['PyTorch compiling details'] == get_build_config()
-
-    assert env_info['TorchVision'] == torchvision.__version__
-
-    assert env_info['OpenCV'] == cv2.__version__
-
-    assert env_info['MMCV'] == mmcv.__version__
-    assert env_info['MMAction2'] == mmaction.__version__