diff --git a/chainer_pytorch_migration/tensor.py b/chainer_pytorch_migration/tensor.py
index 2438b53..56fa105 100644
--- a/chainer_pytorch_migration/tensor.py
+++ b/chainer_pytorch_migration/tensor.py
@@ -72,7 +72,11 @@ def astensor(array):
         # If the array is not allocated (empty)
         # we just create a new one
         if array.data.ptr == 0:
-            return torch.empty(array.shape, dtype=to_torch_dtype(array.dtype))
+            return torch.empty(
+                array.shape,
+                dtype=to_torch_dtype(array.dtype),
+                device=array.device.id
+            )
         return torch.as_tensor(
             _ArrayWithCudaArrayInterfaceHavingStrides(array),
             device=array.device.id,
diff --git a/tests/test_tensor.py b/tests/test_tensor.py
index fb33757..3a6c4be 100644
--- a/tests/test_tensor.py
+++ b/tests/test_tensor.py
@@ -59,22 +59,26 @@ def test_astensor_negative_stride():
 def test_asarray_empty_cpu():
     t = torch.tensor([], dtype=torch.float32)
     a = tensor.asarray(t)
+    assert isinstance(a, numpy.ndarray)
 
 
 def test_asarray_empty_gpu():
     t = torch.tensor([], dtype=torch.float32, device='cuda')
     a = tensor.asarray(t)
+    assert isinstance(a, cupy.ndarray)
 
 
 def test_astensor_empty_cpu():
     a = numpy.array([], dtype=numpy.float32)
     t = tensor.astensor(a)
+    assert t.device.type == 'cpu'
 
 
 def test_astensor_empty_gpu():
     a = cupy.array([], dtype=cupy.float32)
     t = tensor.astensor(a)
     assert isinstance(t, torch.Tensor)
+    assert t.device.type == 'cuda'
     t += 1
     numpy.testing.assert_array_equal(a.get(), t.cpu().numpy())