Create an aesara.tensor.linalg module that combines nlinalg and slinalg

aesara/tensor/__init__.py

@@ -56,12 +56,18 @@ from aesara.tensor import (
     blas,
     blas_c,
     blas_scipy,
-    nlinalg,
     nnet,
     opt_uncanonicalize,
-    slinalg,
     xlogx,
 )
+
+
+# isort: off
+from aesara.tensor import linalg
+from aesara.tensor import nlinalg  # For backward compatibility
+from aesara.tensor import slinalg  # For backward compatibility
+
+# isort: on
 from aesara.tensor.basic import *
 from aesara.tensor.blas import batched_dot, batched_tensordot
 from aesara.tensor.extra_ops import (

aesara/tensor/linalg.py

+from aesara.tensor.nlinalg import *
+from aesara.tensor.slinalg import *

aesara/tensor/var.py

@@ -774,7 +774,7 @@ class _tensor_py_operators:
         return aet.math.round(self, mode)
 
     def trace(self):
-        return aet.nlinalg.trace(self)
+        return aet.linalg.trace(self)
 
     # This value is set so that Aesara arrays will trump NumPy operators.
     __array_priority__ = 1000

setup.cfg

@@ -4,6 +4,7 @@ ignore = E203,E231,E501,E741,W503,W504,C901
 max-line-length = 88
 per-file-ignores =
     **/__init__.py:F401,E402,F403
+    aesara/tensor/linalg.py:F401,F403
     aesara/scalar/basic_scipy.py:E402,F403,F401
     aesara/graph/toolbox.py:E402,F403,F401
     aesara/link/jax/jax_dispatch.py:E402,F403,F401