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Add version requirement for mlflow #7659

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Apr 19, 2024
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2 changes: 1 addition & 1 deletion docs/requirements.txt
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ sphinx-autodoc-typehints==1.11.1
pandas
einops
transformers<4.22; python_version <= '3.10' # https://github.com/Project-MONAI/MONAI/issues/5157
mlflow>=1.28.0
mlflow>=1.28.0, <=2.11.3
clearml>=1.10.0rc0
tensorboardX
imagecodecs; platform_system == "Linux" or platform_system == "Darwin"
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2 changes: 1 addition & 1 deletion requirements-dev.txt
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ pandas
requests
einops
transformers>=4.36.0
mlflow>=1.28.0
mlflow>=1.28.0, <=2.11.3
clearml>=1.10.0rc0
matplotlib!=3.5.0
tensorboardX
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4 changes: 2 additions & 2 deletions setup.cfg
Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,7 @@ all =
pandas
einops
transformers<4.22; python_version <= '3.10'
mlflow>=1.28.0
mlflow>=1.28.0, <=2.11.3
clearml>=1.10.0rc0
matplotlib
tensorboardX
Expand Down Expand Up @@ -125,7 +125,7 @@ einops =
transformers =
transformers<4.22; python_version <= '3.10'
mlflow =
mlflow
mlflow>=1.28.0, <=2.11.3
matplotlib =
matplotlib
clearml =
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3 changes: 2 additions & 1 deletion tests/test_clip_intensity_percentiles.py
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@
from monai.transforms import ClipIntensityPercentiles
from monai.transforms.utils import soft_clip
from monai.transforms.utils_pytorch_numpy_unification import clip, percentile
from monai.utils.type_conversion import convert_to_tensor
from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, NumpyImageTestCase3D, assert_allclose


Expand All @@ -29,7 +30,7 @@ def test_hard_clipping_two_sided(self, p):
im = p(self.imt)
result = hard_clipper(im)
lower, upper = percentile(im, (5, 95))
expected = clip(im, lower, upper)
expected = clip(convert_to_tensor(im), lower, upper)
assert_allclose(result, p(expected), type_test="tensor", rtol=1e-7, atol=0)

@parameterized.expand([[p] for p in TEST_NDARRAYS])
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3 changes: 2 additions & 1 deletion tests/test_clip_intensity_percentilesd.py
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
from monai.transforms import ClipIntensityPercentilesd
from monai.transforms.utils import soft_clip
from monai.transforms.utils_pytorch_numpy_unification import clip, percentile
from monai.utils.type_conversion import convert_to_tensor
from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, NumpyImageTestCase3D, assert_allclose


Expand All @@ -31,7 +32,7 @@ def test_hard_clipping_two_sided(self, p):
im = p(self.imt)
result = hard_clipper({key: im})
lower, upper = percentile(im, (5, 95))
expected = clip(im, lower, upper)
expected = clip(convert_to_tensor(im), lower, upper)
assert_allclose(result[key], p(expected), type_test="tensor", rtol=1e-7, atol=0)

@parameterized.expand([[p] for p in TEST_NDARRAYS])
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