diff --git a/candle-core/tests/tensor_tests.rs b/candle-core/tests/tensor_tests.rs
index 95eadc24..a4548d56 100644
--- a/candle-core/tests/tensor_tests.rs
+++ b/candle-core/tests/tensor_tests.rs
@@ -1,4 +1,4 @@
-use candle_core::{test_device, test_utils, D, DType, Device, IndexOp, Result, Tensor};
+use candle_core::{test_device, test_utils, DType, Device, IndexOp, Result, Tensor, D};
 
 fn zeros(device: &Device) -> Result<()> {
     let tensor = Tensor::zeros((5, 2), DType::F32, device)?;
@@ -1224,25 +1224,23 @@ fn cumsum() -> Result<()> {
 
 /// A helper function for floating point comparison. Both a and b must be 1D Tensor and contains the same amount of data.
 /// Assertion passes if the difference of all pairs of a and b is smaller than epsilon.
-fn assert_close(a: &Tensor, b: &Tensor, epsilon: f64) {
-    let a_vec: Vec<f64> = a.to_vec1().unwrap();
-    let b_vec: Vec<f64> = b.to_vec1().unwrap();
+fn assert_close(a: &Tensor, b: &Tensor, epsilon: f64) -> Result<()> {
+    let a_vec: Vec<f64> = a.to_vec1()?;
+    let b_vec: Vec<f64> = b.to_vec1()?;
 
     assert_eq!(a_vec.len(), b_vec.len());
     for (a, b) in a_vec.iter().zip(b_vec.iter()) {
         assert!((a - b).abs() < epsilon);
     }
+    Ok(())
 }
 
 #[test]
 fn logsumexp() -> Result<()> {
-    let input = Tensor::new(&[[1f32, 2., 3.], [4., 5., 6.]], &Device::Cpu)?;
+    let input = Tensor::new(&[[1f64, 2., 3.], [4., 5., 6.]], &Device::Cpu)?;
     let output = input.logsumexp(D::Minus1)?;
-
-    // Expectation get from pytorch.
+    // The expectations obtained from pytorch.
     let expected = Tensor::new(&[3.4076, 6.4076], &Device::Cpu)?;
-
-    assert_close(&output, &expected, 0.00001);
-
+    assert_close(&output, &expected, 0.00001)?;
     Ok(())
-}
\ No newline at end of file
+}