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# ${generated_comment}
# mypy: disable-error-code="type-arg"
from typing import List, Literal, Optional, overload, Sequence, Tuple, Union
from torch import memory_format, Tensor
from torch.types import _bool, _device, _dtype, _int, _size
# Defined in tools/autograd/templates/python_nn_functions.cpp
${c_nn_function_hints}
# Defined in aten/src/ATen/native/mkldnn/Linear.cpp
def mkldnn_linear(input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor: ...
# Defined at aten/src/ATen/native/mkldnn/MKLDNNConversions.cpp
def mkldnn_reorder_conv2d_weight(
self: Tensor,
padding: List,
stride: List,
dilatation: List,
groups: int,
) -> Tensor: ...
def mkldnn_reorder_conv3d_weight(
self: Tensor,
padding: List,
stride: List,
dilatation: List,
groups: int,
) -> Tensor: ...
# Defined in aten/src/ATen/native/mkldnn/Prelu.cpp
def mkldnn_prelu(input: Tensor, weight: Tensor) -> Tensor: ...
# Defined at tools/autograd/templates/python_nn_functions.cpp
@overload
def _parse_to(
device: _device,
dtype: _dtype,
non_blocking: _bool,
copy: _bool,
*,
memory_format: memory_format,
) -> Tuple[_device, _dtype, _bool, memory_format]: ...
@overload
def _parse_to(
dtype: _dtype,
non_blocking: _bool,
copy: _bool,
*,
memory_format: memory_format,
) -> Tuple[_device, _dtype, _bool, memory_format]: ...
@overload
def _parse_to(
tensor: Tensor,
non_blocking: _bool,
copy: _bool,
*,
memory_format: memory_format,
) -> Tuple[_device, _dtype, _bool, memory_format]: ...
# Defined in aten/src/ATen/native/PackedSequence.cpp
def pad_sequence(
sequences: Union[List[Tensor], Tuple[Tensor, ...]],
batch_first: bool = False,
padding_value: float = 0.0,
padding_side: Union[Literal["left", "right"], str] = "right",
) -> Tensor: ...
def flatten_dense_tensors(tensors: List[Tensor]) -> Tensor: ...
def unflatten_dense_tensors(flat: Tensor, tensors: List[Tensor]) -> List[Tensor]: ...
|
