Fix as_tensor_variable bug when ndim option drops all dimensions

aesara/tensor/basic.py

@@ -127,11 +127,14 @@ def _as_tensor_Variable(x, name, ndim, **kwargs):
         return x
 
     if x.type.ndim > ndim:
-        # strip off leading broadcastable dimensions
-        first_non_broadcastable = [
-            idx for idx in range(x.ndim) if not x.broadcastable[idx]
-        ][0]
-        x = x.dimshuffle(list(range(x.ndim))[first_non_broadcastable:])
+        # Strip off leading broadcastable dimensions
+        non_broadcastables = [idx for idx in range(x.ndim) if not x.broadcastable[idx]]
+
+        if non_broadcastables:
+            x = x.dimshuffle(list(range(x.ndim))[non_broadcastables[0] :])
+        else:
+            x = x.dimshuffle()
+
         if x.ndim > ndim:
             raise ValueError(
                 f"Tensor of type {x.type} could not be cast to have {ndim} dimensions"

tests/tensor/test_basic.py

@@ -447,14 +447,20 @@ class TestAsTensorVariable:
         with pytest.raises(ValueError):
             as_tensor_variable(bad_apply_var)
 
-    def test_strip_leading_broadcastable(self):
+    def test_ndim_strip_leading_broadcastable(self):
         x = TensorType(config.floatX, (True, False))("x")
         x = as_tensor_variable(x, ndim=1)
         assert x.ndim == 1
 
-        x = matrix("x", dtype=config.floatX)
-        with pytest.raises(ValueError):
-            as_tensor_variable(x, ndim=1)
+    def test_ndim_all_broadcastable(self):
+        x = TensorType(config.floatX, (True, True))("x")
+        res = as_tensor_variable(x, ndim=0)
+        assert res.ndim == 0
+
+    def test_ndim_incompatible(self):
+        x = TensorType(config.floatX, (True, False))("x")
+        with pytest.raises(ValueError, match="^Tensor of type.*"):
+            as_tensor_variable(x, ndim=0)
 
     def test_bool(self):
         # We should not allow `as_tensor_variable` to accept `True` or `False`,