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Rand affine fix #4528

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merged 6 commits into from
Jun 20, 2022
Merged

Rand affine fix #4528

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1ffc8b2
WIP
rijobro Jun 16, 2022
d336bdf
fixes
rijobro Jun 17, 2022
e1abfb4
Merge branch 'feature/MetaTensor' into RandAffine_fix
wyli Jun 17, 2022
c20903a
fix
rijobro Jun 20, 2022
5a06741
Merge branch 'RandAffine_fix' of github.com:rijobro/MONAI into RandAf…
rijobro Jun 20, 2022
6c4b5c6
Merge branch 'feature/MetaTensor' into RandAffine_fix
rijobro Jun 20, 2022
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12 changes: 10 additions & 2 deletions monai/transforms/spatial/dictionary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -834,14 +834,22 @@ def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> Dict[Hashable, N
# do the transform
if do_resampling:
d[key] = self.rand_affine(d[key], mode=mode, padding_mode=padding_mode, grid=grid)
self.push_transform(d[key], extra_info={"do_resampling": do_resampling})
self.push_transform(
d[key],
extra_info={"do_resampling": True, "rand_affine_info": self.pop_transform(d[key], check=False)},
)
else:
self.push_transform(d[key], extra_info={"do_resampling": False})
return d

def inverse(self, data: Mapping[Hashable, NdarrayOrTensor]) -> Dict[Hashable, NdarrayOrTensor]:
d = deepcopy(dict(data))

for key in self.key_iterator(d):
if self.pop_transform(d[key])[TraceKeys.EXTRA_INFO]["do_resampling"]:
tr = self.pop_transform(d[key])
do_resampling = tr[TraceKeys.EXTRA_INFO]["do_resampling"]
if do_resampling:
d[key].applied_operations.append(tr[TraceKeys.EXTRA_INFO]["rand_affine_info"]) # type: ignore
d[key] = self.rand_affine.inverse(d[key])

return d
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1 change: 0 additions & 1 deletion runtests.sh
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Expand Up @@ -374,7 +374,6 @@ then
clang_format

echo "${green}done!${noColor}"
exit
fi

# unconditionally report on the state of monai
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3 changes: 3 additions & 0 deletions tests/test_rand_affine.py
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Expand Up @@ -15,6 +15,7 @@
import torch
from parameterized import parameterized

from monai.data.meta_tensor import MetaTensor
from monai.transforms import RandAffine
from monai.utils.type_conversion import convert_data_type
from tests.utils import TEST_NDARRAYS, assert_allclose, is_tf32_env, test_local_inversion
Expand Down Expand Up @@ -147,6 +148,8 @@ def test_rand_affine(self, input_param, input_data, expected_val):
test_local_inversion(g, result, input_data)

assert_allclose(result, expected_val, rtol=_rtol, atol=1e-4, type_test=False)
self.assertIsInstance(result, MetaTensor)
self.assertEqual(len(result.applied_operations), 1)

def test_ill_cache(self):
with self.assertWarns(UserWarning):
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