Merge branch 'dev' into 8185-test-refactor-2

Author: garciadias

.github/workflows/pythonapp-min.yml

@@ -124,7 +124,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        pytorch-version: ['2.4.1', '2.5.1', '2.6.0']  # FIXME: add 'latest' back once PyTorch 2.7 issues are resolved
+        pytorch-version: ['2.4.1', '2.5.1', '2.6.0', '2.7.1']
     timeout-minutes: 40
     steps:
     - uses: actions/checkout@v4
@@ -151,11 +151,7 @@ jobs:
     - name: Install the dependencies
       run: |
         # min. requirements
-        if [ ${{ matrix.pytorch-version }} == "latest" ]; then
-          python -m pip install torch
-        else
-          python -m pip install torch==${{ matrix.pytorch-version }}
-        fi
+        python -m pip install torch==${{ matrix.pytorch-version }}
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions

docs/requirements.txt

@@ -1,5 +1,5 @@
 -f https://download.pytorch.org/whl/cpu/torch-2.4.1%2Bcpu-cp39-cp39-linux_x86_64.whl
-torch>=2.4.1, <2.7.0
+torch>=2.4.1
 pytorch-ignite==0.4.11
 numpy>=1.20
 itk>=5.2

monai/apps/generation/maisi/networks/autoencoderkl_maisi.py

@@ -232,7 +232,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         if self.print_info:
             logger.info(f"Number of splits: {self.num_splits}")
 
-        if self.dim_split <= 1 and self.num_splits <= 1:
+        if self.num_splits <= 1:
             x = self.conv(x)
             return x
 

pyproject.toml

@@ -2,7 +2,7 @@
 requires = [
   "wheel",
   "setuptools",
-  "torch>=2.4.1, <2.7.0",
+  "torch>=2.4.1",
   "ninja",
   "packaging"
 ]

requirements-dev.txt

@@ -20,7 +20,7 @@ pyflakes
 black>=25.1.0
 isort>=5.1, <6.0
 ruff
-pytype>=2020.6.1; platform_system != "Windows"
+pytype>=2020.6.1, <=2024.4.11; platform_system != "Windows"
 types-setuptools
 mypy>=1.5.0, <1.12.0
 ninja

requirements.txt

@@ -1,2 +1,3 @@
-torch>=2.4.1, <2.7.0
+torch>=2.4.1; platform_system != "Windows"
+torch>=2.4.1, !=2.7.0; platform_system == "Windows"
 numpy>=1.24,<3.0

setup.cfg

@@ -42,7 +42,7 @@ setup_requires =
     ninja
     packaging
 install_requires =
-    torch>=2.4.1, <2.7.0
+    torch>=2.4.1
     numpy>=1.24,<3.0
 
 [options.extras_require]

tests/integration/test_pad_collation.py

@@ -11,8 +11,10 @@
 
 from __future__ import annotations
 
+import os
 import random
 import unittest
+from contextlib import redirect_stderr
 from functools import wraps
 
 import numpy as np
@@ -35,7 +37,7 @@
     RandZoomd,
     ToTensor,
 )
-from monai.utils import set_determinism
+from monai.utils import first, set_determinism
 
 
 @wraps(pad_list_data_collate)
@@ -97,8 +99,9 @@ def test_pad_collation(self, t_type, collate_method, transform):
         # Default collation should raise an error
         loader_fail = DataLoader(dataset, batch_size=10)
         with self.assertRaises(RuntimeError):
-            for _ in loader_fail:
-                pass
+            # stifle PyTorch error reporting, we expect failure so don't need to look at it
+            with open(os.devnull) as f, redirect_stderr(f):
+                _ = first(loader_fail)
 
         # Padded collation shouldn't
         loader = DataLoader(dataset, batch_size=10, collate_fn=collate_method)