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# 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
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