From 36b9bc75fce94fad80b743426d4292ce29576629 Mon Sep 17 00:00:00 2001 From: Yiheng Wang Date: Thu, 24 Mar 2022 22:43:22 +0800 Subject: [PATCH] remove ambiguous or ops for optional args Signed-off-by: Yiheng Wang --- monai/transforms/croppad/array.py | 2 +- monai/transforms/spatial/array.py | 10 +++++----- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/monai/transforms/croppad/array.py b/monai/transforms/croppad/array.py index b05917a46c..55718117b4 100644 --- a/monai/transforms/croppad/array.py +++ b/monai/transforms/croppad/array.py @@ -205,7 +205,7 @@ def __call__( # all zeros, skip padding return img - padder = Pad(all_pad_width, mode or self.mode, **self.kwargs) + padder = Pad(to_pad=all_pad_width, mode=mode or self.mode, **self.kwargs) return padder(img) diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index f7327aa07b..d80024954b 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -1281,7 +1281,7 @@ def __call__( keep_size=self.keep_size, mode=look_up_option(mode or self.mode, InterpolateMode), padding_mode=padding_mode or self.padding_mode, - align_corners=align_corners or self.align_corners, + align_corners=self.align_corners if align_corners is None else align_corners, **self.kwargs, )(img) @@ -1796,7 +1796,7 @@ def __call__( Padding mode for outside grid values. Defaults to ``self.padding_mode``. See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html """ - sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:]) + sp_size = fall_back_tuple(self.spatial_size if spatial_size is None else spatial_size, img.shape[1:]) grid, affine = self.affine_grid(spatial_size=sp_size) ret = self.resampler(img, grid=grid, mode=mode or self.mode, padding_mode=padding_mode or self.padding_mode) @@ -1978,7 +1978,7 @@ def __call__( # if not doing transform and spatial size doesn't change, nothing to do # except convert to float and device - sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:]) + sp_size = fall_back_tuple(self.spatial_size if spatial_size is None else spatial_size, img.shape[1:]) do_resampling = self._do_transform or (sp_size != ensure_tuple(img.shape[1:])) if not do_resampling: img, *_ = convert_data_type(img, dtype=torch.float32, device=self.resampler.device) @@ -2120,7 +2120,7 @@ def __call__( See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html randomize: whether to execute `randomize()` function first, default to True. """ - sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:]) + sp_size = fall_back_tuple(self.spatial_size if spatial_size is None else spatial_size, img.shape[1:]) if randomize: self.randomize(spatial_size=sp_size) @@ -2280,7 +2280,7 @@ def __call__( See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html randomize: whether to execute `randomize()` function first, default to True. """ - sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:]) + sp_size = fall_back_tuple(self.spatial_size if spatial_size is None else spatial_size, img.shape[1:]) if randomize: self.randomize(grid_size=sp_size)