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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 fields, is_dataclass
from typing import Any, Union
import torch
def move_data_to_device(inputs: Any, device: Union[str, torch.device], non_blocking: bool = True) -> Any:
"""Recursively moves inputs to the specified device"""
if inputs is None:
return None
if isinstance(inputs, torch.Tensor):
return inputs.to(device, non_blocking=non_blocking)
elif isinstance(inputs, (list, tuple, set)):
return inputs.__class__([move_data_to_device(i, device, non_blocking) for i in inputs])
elif isinstance(inputs, dict):
return {k: move_data_to_device(v, device, non_blocking) for k, v in inputs.items()}
elif is_dataclass(inputs):
return type(inputs)(
**{
field.name: move_data_to_device(getattr(inputs, field.name), device, non_blocking)
for field in fields(inputs)
}
)
else:
return inputs
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