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[air] Upgrade and unify device types with dataset.TorchDeviceType #56745

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[air] Upgrade and unify device types with dataset.TorchDeviceType #56745

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7c0d61e
Upgrade and unify device types with dataset.TorchDeviceType
Daraan Sep 19, 2025
317b06a
Use str for ForwardRef
Daraan Sep 20, 2025
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15 changes: 9 additions & 6 deletions python/ray/air/_internal/torch_utils.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
import warnings
from typing import Any, Dict, List, Optional, Sequence, Union
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Union

import numpy as np
import pandas as pd
Expand All @@ -19,6 +19,9 @@
_is_tensor_sequence_mapping,
)

if TYPE_CHECKING:
from ray.data.dataset import TorchDeviceType

# Default non-blocking transfer for tensors.
DEFAULT_TENSOR_NON_BLOCKING_TRANSFER = env_bool(
"RAY_AIR_DEFAULT_TENSOR_NON_BLOCKING_TRANSFER",
Expand Down Expand Up @@ -148,7 +151,7 @@ def get_tensor_for_columns(columns, dtype):
def convert_ndarray_to_torch_tensor(
ndarray: np.ndarray,
dtype: Optional[torch.dtype] = None,
device: Optional[Union[str, "torch.device"]] = None,
device: Optional[TorchDeviceType] = None,
pin_memory: bool = False,
) -> torch.Tensor:
"""Convert a NumPy ndarray to a Torch Tensor.
Expand Down Expand Up @@ -197,7 +200,7 @@ def convert_ndarray_to_torch_tensor(
def convert_ndarray_batch_to_torch_tensor_batch(
ndarrays: Union[np.ndarray, Dict[str, np.ndarray]],
dtypes: Optional[Union[torch.dtype, Dict[str, torch.dtype]]] = None,
device: Optional[Union[str, "torch.device"]] = None,
device: Optional[TorchDeviceType] = None,
pin_memory: bool = False,
) -> Union[torch.Tensor, Dict[str, torch.Tensor]]:
"""Convert a NumPy ndarray batch to a Torch Tensor batch.
Expand Down Expand Up @@ -333,7 +336,7 @@ def consume_prefix_in_state_dict_if_present_not_in_place(
def convert_ndarray_list_to_torch_tensor_list(
ndarrays: Dict[str, List[np.ndarray]],
dtypes: Optional[Union[torch.dtype, Dict[str, torch.dtype]]] = None,
device: Optional[Union[str, "torch.device"]] = None,
device: Optional[TorchDeviceType] = None,
pin_memory: bool = False,
) -> Dict[str, List[torch.Tensor]]:
"""Convert a dict mapping column names to lists of ndarrays to Torch Tensors.
Expand Down Expand Up @@ -411,7 +414,7 @@ def arrow_batch_to_tensors(
@torch.no_grad()
def concat_tensors_to_device(
tensor_sequence: Sequence[torch.Tensor],
device: Optional[Union[str, "torch.device"]] = None,
device: Optional[TorchDeviceType] = None,
non_blocking: bool = DEFAULT_TENSOR_NON_BLOCKING_TRANSFER,
) -> torch.Tensor:
"""Stack sequence of tensors into a contiguous GPU tensor.
Expand Down Expand Up @@ -493,7 +496,7 @@ def _get_type_str(batch: Any) -> str:
@torch.no_grad()
def move_tensors_to_device(
batch: TensorBatchType,
device: Optional[Union[str, "torch.device"]] = None,
device: Optional[TorchDeviceType] = None,
non_blocking: bool = DEFAULT_TENSOR_NON_BLOCKING_TRANSFER,
) -> TensorBatchReturnType:
"""Move tensors to the specified device.
Expand Down