chore: import upstream snapshot with attribution

tests/collections/common/test_data_utils.py

@@ -0,0 +1,52 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from dataclasses import dataclass
+
+import pytest
+import torch
+
+from nemo.collections.common.data.utils import move_data_to_device
+
+
+@dataclass
+class _Batch:
+    data: torch.Tensor
+
+
+@pytest.mark.skipif(not torch.cuda.is_available(), reason="This test requires GPUs.")
+@pytest.mark.parametrize(
+    "batch",
+    [
+        torch.tensor([0]),
+        (torch.tensor([0]),),
+        [torch.tensor([0])],
+        {"data": torch.tensor([0])},
+        _Batch(torch.tensor([0])),
+        "not a tensor",
+    ],
+)
+def test_move_data_to_device(batch):
+    cuda_batch = move_data_to_device(batch, device="cuda")
+    assert type(batch) == type(cuda_batch)
+    if isinstance(batch, _Batch):
+        assert cuda_batch.data.is_cuda
+    elif isinstance(batch, dict):
+        assert cuda_batch["data"].is_cuda
+    elif isinstance(batch, (list, tuple)):
+        assert cuda_batch[0].is_cuda
+    elif isinstance(batch, torch.Tensor):
+        assert cuda_batch.is_cuda
+    else:
+        assert cuda_batch == batch