Add version requirement for mlflow (#7659)

Fixes #7658.

### Description
set mlflow>=1.28.0,<=2.11.3
mlflow/mlflow#11740

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>

Author: KumoLiu

docs/requirements.txt

@@ -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"

requirements-dev.txt

@@ -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

setup.cfg

@@ -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
@@ -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 =

tests/test_clip_intensity_percentiles.py

@@ -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
 
 
@@ -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])

tests/test_clip_intensity_percentilesd.py

@@ -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
 
 
@@ -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])