0.4.1

.coveragerc

 [report]
 exclude_lines =
     pragma: no cover
-    def backward
-    def bw
+    cuda
+    backward

.travis.yml

@@ -7,12 +7,11 @@ matrix:
     - python: 3.5
     - python: 3.6
 install:
-  - if [[ $TRAVIS_PYTHON_VERSION == 2.7 ]]; then pip install http://download.pytorch.org/whl/cpu/torch-0.4.0-cp27-cp27mu-linux_x86_64.whl; fi
-  - if [[ $TRAVIS_PYTHON_VERSION == 3.5 ]]; then pip install http://download.pytorch.org/whl/cpu/torch-0.4.0-cp35-cp35m-linux_x86_64.whl; fi
-  - if [[ $TRAVIS_PYTHON_VERSION == 3.6 ]]; then pip install http://download.pytorch.org/whl/cpu/torch-0.4.0-cp36-cp36m-linux_x86_64.whl; fi
+  - if [[ $TRAVIS_PYTHON_VERSION == 2.7 ]]; then pip install http://download.pytorch.org/whl/cpu/torch-0.4.1-cp27-cp27mu-linux_x86_64.whl; fi
+  - if [[ $TRAVIS_PYTHON_VERSION == 3.5 ]]; then pip install  http://download.pytorch.org/whl/cpu/torch-0.4.1-cp35-cp35m-linux_x86_64.whl; fi
+  - if [[ $TRAVIS_PYTHON_VERSION == 3.6 ]]; then pip install http://download.pytorch.org/whl/cpu/torch-0.4.1-cp36-cp36m-linux_x86_64.whl; fi
   - pip install pycodestyle
   - pip install flake8
-  - pip install cffi
   - pip install codecov
 script:
   - pycodestyle .

test/utils.py

@@ -3,7 +3,7 @@ import torch
 dtypes = [torch.float, torch.double]
 
 devices = [torch.device('cpu')]
-if torch.cuda.is_available():  # pragma: no cover
+if torch.cuda.is_available():
     devices += [torch.device('cuda:{}'.format(torch.cuda.current_device()))]
 
 

torch_spline_conv/weighting.py

@@ -35,7 +35,7 @@ class SplineWeighting(Function):
         return fw(src, weight, basis, weight_index)
 
     @staticmethod
-    def backward(ctx, grad_out):  # pragma: no cover
+    def backward(ctx, grad_out):
         grad_src = grad_weight = grad_basis = None
         src, weight, basis, weight_index = ctx.saved_tensors