Fix deprecated argument in 'scipy.sparse.linalg.cg' (#7897)

Fixes #7896 

### Description

- 'scipy.sparse.linalg.cg' keyword argument `tol` is deprecated in favor
of `rtol` and will be removed in SciPy v1.14.0. Until then, if set, it
will override `rtol`. So update to use `rtol` in `cg`.

- Drop python 3.8 test in packaging and premerge-gpu-test.

### 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 <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: KumoLiu

.github/workflows/pythonapp.yml

@@ -29,10 +29,10 @@ jobs:
         opt: ["codeformat", "pytype", "mypy"]
     steps:
     - uses: actions/checkout@v4
-    - name: Set up Python 3.8
+    - name: Set up Python 3.9
       uses: actions/setup-python@v5
       with:
-        python-version: '3.8'
+        python-version: '3.9'
     - name: cache weekly timestamp
       id: pip-cache
       run: |
@@ -45,6 +45,7 @@ jobs:
         key: ${{ runner.os }}-pip-${{ steps.pip-cache.outputs.datew }}
     - name: Install dependencies
       run: |
+        find  /opt/hostedtoolcache/* -maxdepth 0 ! -name 'Python' -exec rm -rf {} \;
         python -m pip install --upgrade pip wheel
         python -m pip install -r requirements-dev.txt
     - name: Lint and type check
@@ -130,10 +131,10 @@ jobs:
     - uses: actions/checkout@v4
       with:
         fetch-depth: 0
-    - name: Set up Python 3.8
+    - name: Set up Python 3.9
       uses: actions/setup-python@v5
       with:
-        python-version: '3.8'
+        python-version: '3.9'
     - name: cache weekly timestamp
       id: pip-cache
       run: |
@@ -211,10 +212,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
-    - name: Set up Python 3.8
+    - name: Set up Python 3.9
       uses: actions/setup-python@v5
       with:
-        python-version: '3.8'
+        python-version: '3.9'
     - name: cache weekly timestamp
       id: pip-cache
       run: |

docs/requirements.txt

@@ -6,7 +6,7 @@ itk>=5.2
 nibabel
 parameterized
 scikit-image>=0.19.0
-scipy>=1.7.1
+scipy>=1.12.0; python_version >= '3.9'
 tensorboard
 commonmark==0.9.1
 recommonmark==0.6.0

monai/data/ultrasound_confidence_map.py

@@ -19,10 +19,10 @@
 __all__ = ["UltrasoundConfidenceMap"]
 
 cv2, _ = optional_import("cv2")
-csc_matrix, _ = optional_import("scipy.sparse", "1.7.1", min_version, "csc_matrix")
-spsolve, _ = optional_import("scipy.sparse.linalg", "1.7.1", min_version, "spsolve")
-cg, _ = optional_import("scipy.sparse.linalg", "1.7.1", min_version, "cg")
-hilbert, _ = optional_import("scipy.signal", "1.7.1", min_version, "hilbert")
+csc_matrix, _ = optional_import("scipy.sparse", "1.12.0", min_version, "csc_matrix")
+spsolve, _ = optional_import("scipy.sparse.linalg", "1.12.0", min_version, "spsolve")
+cg, _ = optional_import("scipy.sparse.linalg", "1.12.0", min_version, "cg")
+hilbert, _ = optional_import("scipy.signal", "1.12.0", min_version, "hilbert")
 ruge_stuben_solver, _ = optional_import("pyamg", "5.0.0", min_version, "ruge_stuben_solver")
 
 
@@ -285,7 +285,7 @@ def _solve_linear_system(self, lap, rhs):
             lap_sparse = lap.tocsr()
             ml = ruge_stuben_solver(lap_sparse, coarse_solver="pinv")
             m = ml.aspreconditioner(cycle="V")
-            x, _ = cg(lap, rhs, tol=self.cg_tol, maxiter=self.cg_maxiter, M=m)
+            x, _ = cg(lap, rhs, rtol=self.cg_tol, maxiter=self.cg_maxiter, M=m)
         else:
             x = spsolve(lap, rhs)
 

monai/optimizers/lr_finder.py

@@ -524,7 +524,7 @@ def plot(
         # Plot the LR with steepest gradient
         if steepest_lr:
             lr_at_steepest_grad, loss_at_steepest_grad = self.get_steepest_gradient(skip_start, skip_end)
-            if lr_at_steepest_grad is not None:
+            if lr_at_steepest_grad is not None and loss_at_steepest_grad is not None:
                 ax.scatter(
                     lr_at_steepest_grad,
                     loss_at_steepest_grad,

requirements-dev.txt

@@ -2,7 +2,7 @@
 -r requirements-min.txt
 pytorch-ignite==0.4.11
 gdown>=4.7.3
-scipy>=1.7.1
+scipy>=1.12.0; python_version >= '3.9'
 itk>=5.2
 nibabel
 pillow!=8.3.0  # https://github.com/python-pillow/Pillow/issues/5571

requirements.txt

@@ -1,2 +1,2 @@
 torch>=1.9
-numpy>=1.20,<2.0
+numpy>=1.20,<=1.26.0

setup.cfg

@@ -49,7 +49,7 @@ all =
     nibabel
     ninja
     scikit-image>=0.14.2
-    scipy>=1.7.1
+    scipy>=1.12.0; python_version >= '3.9'
     pillow
     tensorboard
     gdown>=4.7.3
@@ -92,7 +92,7 @@ ninja =
 skimage =
     scikit-image>=0.14.2
 scipy =
-    scipy>=1.7.1
+    scipy>=1.12.0; python_version >= '3.9'
 pillow =
     pillow!=8.3.0
 tensorboard =

tests/test_ultrasound_confidence_map_transform.py

@@ -20,8 +20,11 @@
 from PIL import Image
 
 from monai.transforms import UltrasoundConfidenceMapTransform
+from monai.utils import optional_import
 from tests.utils import assert_allclose
 
+_, has_scipy = optional_import("scipy")
+
 TEST_INPUT = np.array(
     [
         [1, 2, 3, 23, 13, 22, 5, 1, 2, 3],
@@ -482,6 +485,7 @@
 )
 
 
+@unittest.skipUnless(has_scipy, "Requires scipy")
 class TestUltrasoundConfidenceMapTransform(unittest.TestCase):
 
     def setUp(self):

tests/utils.py

@@ -475,7 +475,7 @@ def run_process(self, func, local_rank, args, kwargs, results):
             if self.verbose:
                 os.environ["NCCL_DEBUG"] = "INFO"
                 os.environ["NCCL_DEBUG_SUBSYS"] = "ALL"
-            os.environ["NCCL_BLOCKING_WAIT"] = str(1)
+            os.environ["TORCH_NCCL_BLOCKING_WAIT"] = str(1)
             os.environ["OMP_NUM_THREADS"] = str(1)
             os.environ["WORLD_SIZE"] = str(self.nproc_per_node * self.nnodes)
             os.environ["RANK"] = str(self.nproc_per_node * self.node_rank + local_rank)