Add test for Tensor creation from NumPy on CPU and CUDA

Author: lantiga

test/test_torch.py

@@ -135,8 +135,20 @@ def test_has_storage(self):
 
  @unittest.skipIf(not TEST_NUMPY, "Numpy not found")
  def test_has_storage_numpy(self):
- arr = np.array([], dtype=np.float32)
- self.assertIsNotNone(torch.Tensor(arr).storage())
+ for dtype in [np.float32, np.float64, np.int64,
+ np.int32, np.int16, np.uint8]:
+ arr = np.array([1], dtype=dtype)
+ self.assertIsNotNone(torch.FloatTensor(arr).storage())
+ self.assertIsNotNone(torch.DoubleTensor(arr).storage())
+ self.assertIsNotNone(torch.IntTensor(arr).storage())
+ self.assertIsNotNone(torch.LongTensor(arr).storage())
+ self.assertIsNotNone(torch.ByteTensor(arr).storage())
+ if torch.cuda.is_available():
+ self.assertIsNotNone(torch.cuda.FloatTensor(arr).storage())
+ self.assertIsNotNone(torch.cuda.DoubleTensor(arr).storage())
+ self.assertIsNotNone(torch.cuda.IntTensor(arr).storage())
+ self.assertIsNotNone(torch.cuda.LongTensor(arr).storage())
+ self.assertIsNotNone(torch.cuda.ByteTensor(arr).storage())
 
  def _testSelection(self, torchfn, mathfn):
  # contiguous