netrans/bin/torch/nn/modules/upsampling.pyi

28 lines
942 B
Python

from ... import Tensor
from .module import Module
from typing import Optional
from ..common_types import _size_2_t, _ratio_2_t, _size_any_t, _ratio_any_t
class Upsample(Module):
name: str = ...
size: _size_any_t = ...
scale_factor: _ratio_any_t = ...
mode: str = ...
align_corners: bool = ...
def __init__(self, size: Optional[_size_any_t] = ..., scale_factor: Optional[_ratio_any_t] = ..., mode: str = ...,
align_corners: Optional[bool] = ...) -> None: ...
def forward(self, input: Tensor) -> Tensor: ... # type: ignore
def __call__(self, input: Tensor) -> Tensor: ... # type: ignore
class UpsamplingNearest2d(Upsample):
def __init__(self, size: Optional[_size_2_t] = ..., scale_factor: Optional[_ratio_2_t] = ...) -> None: ...
class UpsamplingBilinear2d(Upsample):
def __init__(self, size: Optional[_size_2_t] = ..., scale_factor: Optional[_ratio_2_t] = ...) -> None: ...