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3983 Remove ambiguous or ops for optional args #3997

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Merged
wyli merged 2 commits into from
Mar 24, 2022
Merged

3983 Remove ambiguous or ops for optional args #3997

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36b9bc7
remove ambiguous or ops for optional args
yiheng-wang-nv Mar 24, 2022
9366a55
Merge branch 'dev' into 3983-remove-ambiguous-or-operations
yiheng-wang-nv Mar 24, 2022
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2 changes: 1 addition & 1 deletion monai/transforms/croppad/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)


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10 changes: 5 additions & 5 deletions monai/transforms/spatial/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)

Expand Down Expand Up @@ -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)

Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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)

Expand Down Expand Up @@ -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)

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