fixing mindspore.norm and paddle-openssl compatibility

Author: rogerwwww

.github/workflows/python-package.yml

@@ -30,6 +30,8 @@ jobs:
         python -m pip install flake8 pytest-cov
         if [ -f tests/requirements.txt ]; then pip install -r tests/requirements.txt; fi
         if [ "${{ matrix.python-version }}" != "3.10" ]; then pip install mindspore==2.0.0; fi
+        wget http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb
+        dpkg -i libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb
     - name: Generate astar.so
       run: |
         python pygmtools/c_astar_src/build_c_astar.py
@@ -46,7 +48,7 @@ jobs:
         pytest --cov=pygmtools --cov-report=xml --cov-append
     - name: Upload to codecov
       uses: codecov/codecov-action@v3
-      if: matrix.python-version == 3.8
+      if: matrix.python-version == 3.9
 
   macos:
 

pygmtools/mindspore_backend.py

@@ -30,6 +30,19 @@ def _ms_max(*args, keep_dims=False, **kwargs):
                      'working with a new Mindspore version which breaks backward compatibility. Please report your '
                      'Mindspore version to GitHub issues.')
 
+_norm_signature = inspect.signature(mindspore.ops.norm)
+if 'axis' in _norm_signature.parameters:
+    def _ms_norm(*args, axis=None, **kwargs):
+        return mindspore.ops.norm(*args, axis=axis, **kwargs)
+elif 'dim' in _norm_signature.parameters:
+    def _ms_norm(*args, axis=None, **kwargs):
+        return mindspore.ops.norm(*args, dim=axis, **kwargs)
+else:
+    raise ValueError('Mindspore function mindspore.ops.norm has unsupported signature. It is likely you are '
+                     'working with a new Mindspore version which breaks backward compatibility. Please report your '
+                     'Mindspore version to GitHub issues.')
+
+
 #############################################
 #     Linear Assignment Problem Solvers     #
 #############################################
@@ -261,15 +274,15 @@ def rrwm(K: mindspore.Tensor, n1: mindspore.Tensor, n2: mindspore.Tensor, n1max,
         # random walk
         v = mindspore.ops.BatchMatMul()(K, v)
         last_v = v
-        n = mindspore.ops.norm(v, axis=1, p=1, keep_dims=True)
+        n = _ms_norm(v, axis=1, p=1, keep_dims=True)
         v = v / n
 
         # reweighted jump
         s = v.view(batch_num, int(n2max), int(n1max)).swapaxes(1, 2)
         s = beta * s / s.max(axis=1, keepdims=True).max(axis=2, keepdims=True)
         v = alpha * sinkhorn(s, n1, n2, max_iter=sk_iter, batched_operation=True).swapaxes(1, 2).reshape(batch_num, n1n2, 1) + \
             (1 - alpha) * v
-        n = mindspore.ops.norm(v, axis=1, p=1, keep_dims=True)
+        n = _ms_norm(v, axis=1, p=1, keep_dims=True)
         v = mindspore.ops.matmul(v, 1 / n)
 
         if (v - last_v).sum().sqrt() < 1e-5:
@@ -287,7 +300,7 @@ def sm(K: mindspore.Tensor, n1: mindspore.Tensor, n2: mindspore.Tensor, n1max, n
     v = vlast = v0
     for i in range(max_iter):
         v = mindspore.ops.BatchMatMul()(K, v)
-        n = mindspore.ops.norm(v, axis=1, p=2)
+        n = _ms_norm(v, axis=1, p=2)
         v = mindspore.ops.matmul(v, (1 / n).view(batch_num, 1, 1))
         if (v - vlast).sum().sqrt() < 1e-5:
             break