Try to fix lint issue (#199)

* try to fix lint

* upgrade yapf version

* use another way to bypass yapf

* update docstring

.circleci/config.yml

@@ -63,7 +63,7 @@ jobs:
 
   build_cu102:
     machine:
-      image: ubuntu-1604-cuda-10.1:201909-23  # the actual version of cuda is 10.2
+      image: ubuntu-1604-cuda-10.1:201909-23 # the actual version of cuda is 10.2
     resource_class: gpu.nvidia.small
     steps:
       - checkout

mmengine/utils/parrots_wrapper.py

@@ -8,6 +8,7 @@ TORCH_VERSION = torch.__version__
 
 
 def is_rocm_pytorch() -> bool:
+    """Check whether the PyTorch is compiled on ROCm."""
     is_rocm = False
     if TORCH_VERSION != 'parrots':
         try:
@@ -20,6 +21,7 @@ def is_rocm_pytorch() -> bool:
 
 
 def _get_cuda_home() -> Optional[str]:
+    """Obtain the path of CUDA home."""
     if TORCH_VERSION == 'parrots':
         from parrots.utils.build_extension import CUDA_HOME
     else:
@@ -32,6 +34,7 @@ def _get_cuda_home() -> Optional[str]:
 
 
 def get_build_config():
+    """Obtain the build information of PyTorch or Parrots."""
     if TORCH_VERSION == 'parrots':
         from parrots.config import get_build_info
         return get_build_info()
@@ -40,6 +43,8 @@ def get_build_config():
 
 
 def _get_conv() -> tuple:
+    """A wrapper to obtain base classes of Conv layers from PyTorch or
+    Parrots."""
     if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.conv import _ConvNd, _ConvTransposeMixin
     else:
@@ -48,6 +53,7 @@ def _get_conv() -> tuple:
 
 
 def _get_dataloader() -> tuple:
+    """A wrapper to obtain DataLoader class from PyTorch or Parrots."""
     if TORCH_VERSION == 'parrots':
         from torch.utils.data import DataLoader, PoolDataLoader
     else:
@@ -57,6 +63,7 @@ def _get_dataloader() -> tuple:
 
 
 def _get_extension():
+    """A wrapper to obtain extension class from PyTorch or Parrots."""
     if TORCH_VERSION == 'parrots':
         from parrots.utils.build_extension import BuildExtension, Extension
         CppExtension = partial(Extension, cuda=False)
@@ -68,6 +75,8 @@ def _get_extension():
 
 
 def _get_pool() -> tuple:
+    """A wrapper to obtain base classes of pooling layers from PyTorch or
+    Parrots."""
     if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.pool import (_AdaptiveAvgPoolNd,
                                              _AdaptiveMaxPoolNd, _AvgPoolNd,
@@ -80,6 +89,8 @@ def _get_pool() -> tuple:
 
 
 def _get_norm() -> tuple:
+    """A wrapper to obtain base classes of normalization layers from PyTorch or
+    Parrots."""
     if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.batchnorm import _BatchNorm, _InstanceNorm
         SyncBatchNorm_ = torch.nn.SyncBatchNorm2d

mmengine/version.py

@@ -4,6 +4,14 @@ __version__ = '0.0.1'
 
 
 def parse_version_info(version_str):
+    """Parse the version information.
+
+    Args:
+        version_str (str): version string like '0.0.1'.
+
+    Returns:
+        tuple: version information contains major, minor, micro version.
+    """
     version_info = []
     for x in version_str.split('.'):
         if x.isdigit():

tests/test_runner/test_runner.py

@@ -36,8 +36,11 @@ class ToyModel(nn.Module):
         self.linear = nn.Linear(2, 1)
 
     def forward(self, data_batch, return_loss=False):
-        inputs, labels = zip(
-            *map(lambda x: (x['inputs'], x['data_sample']), data_batch))
+        inputs, labels = [], []
+        for x in data_batch:
+            inputs.append(x['inputs'])
+            labels.append(x['data_sample'])
+
         device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
         inputs = torch.stack(inputs).to(device)
         labels = torch.stack(labels).to(device)