fixes tests

Signed-off-by: Wenqi Li <wenqil@nvidia.com>

monai/networks/layers/simplelayers.py

@@ -295,10 +295,11 @@ def apply_filter(x: torch.Tensor, kernel: torch.Tensor, **kwargs) -> torch.Tenso
     conv = [F.conv1d, F.conv2d, F.conv3d][n_spatial - 1]
     if "padding" not in kwargs:
         if pytorch_after(1, 10):
+            kwargs["padding"] = "same"
+        else:
             # even-sized kernels are not supported
             kwargs["padding"] = [(k - 1) // 2 for k in kernel.shape[2:]]
-        else:
-            kwargs["padding"] = "same"
+
     if "stride" not in kwargs:
         kwargs["stride"] = 1
     output = conv(x, kernel, groups=kernel.shape[0], bias=None, **kwargs)

monai/utils/module.py

@@ -8,7 +8,10 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 import enum
+import os
+import re
 import sys
 import warnings
 from functools import wraps
@@ -453,6 +456,8 @@ def _try_cast(val: str):
 def pytorch_after(major, minor, patch=0, current_ver_string=None) -> bool:
     """
     Compute whether the current pytorch version is after or equal to the specified version.
+    The current system pytorch version is determined by `torch.__version__` or
+    via system environment variable `PYTORCH_VER`.
 
     Args:
         major: major version number to be compared with
@@ -465,23 +470,30 @@ def pytorch_after(major, minor, patch=0, current_ver_string=None) -> bool:
     """
     try:
         if current_ver_string is None:
-            current_ver_string = torch.__version__
-        c_major, c_minor, c_patch = current_ver_string.split("+", 1)[0].split(".", 3)
+            _env_var = os.environ.get("PYTORCH_VER", "")
+            current_ver_string = _env_var if _env_var else torch.__version__
+        parts = f"{current_ver_string}".split("+", 1)[0].split(".", 3)
+        while len(parts) < 3:
+            parts += ["0"]
+        c_major, c_minor, c_patch = parts[:3]
     except (AttributeError, ValueError, TypeError):
         c_major, c_minor = get_torch_version_tuple()
-        c_patch = 0
+        c_patch = "0"
     c_mn = int(c_major), int(c_minor)
     mn = int(major), int(minor)
     if c_mn != mn:
         return c_mn > mn
-    is_prerelease = "a" in c_patch
+    is_prerelease = ("a" in f"{c_patch}".lower()) or ("rc" in f"{c_patch}".lower())
+    c_p = 0
     try:
-        c_patch = int(c_patch) if not is_prerelease else int(c_patch.split("a", 1)[0])
+        p_reg = re.search(r"\d+", f"{c_patch}")
+        if p_reg:
+            c_p = int(p_reg.group())
     except (AttributeError, TypeError, ValueError):
-        c_patch = 0
         is_prerelease = True
-    if c_patch != patch:
-        return c_patch > patch
+    patch = int(patch)
+    if c_p != patch:
+        return c_p > patch  # type: ignore
     if is_prerelease:
         return False
     return True

tests/test_pytorch_version_after.py

@@ -30,7 +30,7 @@
     (1, 6, 0, "1.6.0-rc0+3fd9dcf", False),  # defaults to prerelease
     (1, 6, 0, "1.6.0rc0", False),
     (1, 6, 0, "1.6", True),
-    (1, 6, 0, "1", True),
+    (1, 6, 0, "1", False),
     (1, 6, 0, "1.6.0+cpu", True),
     (1, 6, 1, "1.6.0+cpu", False),
 )

tests/utils.py

@@ -36,7 +36,6 @@
 from monai.data import create_test_image_2d, create_test_image_3d
 from monai.networks import convert_to_torchscript
 from monai.utils import optional_import
-from monai.utils.misc import is_module_ver_at_least
 from monai.utils.module import pytorch_after, version_leq
 from monai.utils.type_conversion import convert_data_type