| # Copyright (c) MONAI Consortium | |
| # 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 __future__ import annotations | |
| from collections.abc import Callable, Sized | |
| import torch | |
| import torch.nn.functional as F | |
| from monai.utils import InterpolateMode | |
| __all__ = ["default_upsampler"] | |
| def default_upsampler(spatial_size: Sized, align_corners: bool = False) -> Callable[[torch.Tensor], torch.Tensor]: | |
| """ | |
| A linear interpolation method for upsampling the feature map. | |
| The output of this function is a callable `func`, | |
| such that `func(x)` returns an upsampled tensor. | |
| """ | |
| def up(x): | |
| linear_mode = [InterpolateMode.LINEAR, InterpolateMode.BILINEAR, InterpolateMode.TRILINEAR] | |
| interp_mode = linear_mode[len(spatial_size) - 1] | |
| return F.interpolate(x, size=spatial_size, mode=str(interp_mode.value), align_corners=align_corners) | |
| return up | |