Fix passing M=None to function in Eye test

Author: ricardoV94

pytensor/tensor/basic.py

@@ -1453,8 +1453,7 @@ def eye(n, m=None, k=0, dtype=None):
         dtype = config.floatX
     if m is None:
         m = n
-    localop = Eye(dtype)
-    return localop(n, m, k)
+    return Eye(dtype)(n, m, k)
 
 
 def identity_like(x, dtype: str | np.generic | np.dtype | None = None):

tests/tensor/test_basic.py

@@ -934,22 +934,18 @@ def test_infer_static_shape():
 class TestEye:
     # This is slow for the ('int8', 3) version.
     def test_basic(self):
-        def check(dtype, N, M_=None, k=0):
-            # PyTensor does not accept None as a tensor.
-            # So we must use a real value.
-            M = M_
-            # Currently DebugMode does not support None as inputs even if this is
-            # allowed.
-            if M is None and config.mode in ["DebugMode", "DEBUG_MODE"]:
-                M = N
+        def check(dtype, N, M=None, k=0):
             N_symb = iscalar()
             M_symb = iscalar()
             k_symb = iscalar()
+            test_inputs = [N, k] if M is None else [N, M, k]
+            inputs = [N_symb, k_symb] if M is None else [N_symb, M_symb, k_symb]
             f = function(
-                [N_symb, M_symb, k_symb], eye(N_symb, M_symb, k_symb, dtype=dtype)
+                inputs,
+                eye(N_symb, None if (M is None) else M_symb, k_symb, dtype=dtype),
             )
-            result = f(N, M, k)
-            assert np.allclose(result, np.eye(N, M_, k, dtype=dtype))
+            result = f(*test_inputs)
+            assert np.allclose(result, np.eye(N, M, k, dtype=dtype))
             assert result.dtype == np.dtype(dtype)
 
         for dtype in ALL_DTYPES:
@@ -1755,7 +1751,7 @@ def test_join_matrixV_negative_axis(self):
         got = f(-2)
         assert np.allclose(got, want)
 
-        with pytest.raises(ValueError):
+        with pytest.raises((ValueError, IndexError)):
             f(-3)
 
     @pytest.mark.parametrize("py_impl", (False, True))