Fix test load image issue (#8297)

Fixes #8274 .

### Description

The new test has already tested with the same 24.08 + A100 env.

I did some tests but cannot reproduce the original test case error
(there are NaN values or significant small/large data). Since only 24.08
base image has the issue (24.10 does not have), I decided to use a
different test case for 24.08 and prepared this PR

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: Yiheng Wang <vennw@nvidia.com>

Author: yiheng-wang-nv

tests/test_load_image.py

@@ -217,7 +217,12 @@ def test_nibabel_reader(self, input_param, filenames, expected_shape):
     @SkipIfNoModule("kvikio")
     @parameterized.expand([TEST_CASE_GPU_1, TEST_CASE_GPU_2, TEST_CASE_GPU_3, TEST_CASE_GPU_4])
     def test_nibabel_reader_gpu(self, input_param, filenames, expected_shape):
-        test_image = np.random.rand(128, 128, 128)
+        if torch.__version__.endswith("nv24.8"):
+            # related issue: https://github.com/Project-MONAI/MONAI/issues/8274
+            # for this version, use randint test case to avoid the issue
+            test_image = torch.randint(0, 256, (128, 128, 128), dtype=torch.uint8).numpy()
+        else:
+            test_image = np.random.rand(128, 128, 128)
         with tempfile.TemporaryDirectory() as tempdir:
             for i, name in enumerate(filenames):
                 filenames[i] = os.path.join(tempdir, name)