Fix tensor.zeros and tensor.ones with symbolic scalar

aesara/tensor/basic.py

@@ -978,7 +978,10 @@ def zeros_like(model, dtype=None, opt=False):
 
 def zeros(shape, dtype=None):
     """Create a `TensorVariable` filled with zeros, closer to NumPy's syntax than ``alloc``."""
-    if not isinstance(shape, (np.ndarray, Sequence, TensorVariable)):
+    if not (
+        isinstance(shape, (np.ndarray, Sequence))
+        or (isinstance(shape, TensorVariable) and shape.ndim > 0)
+    ):
         shape = [shape]
     if dtype is None:
         dtype = config.floatX
@@ -987,7 +990,10 @@ def zeros(shape, dtype=None):
 
 def ones(shape, dtype=None):
     """Create a `TensorVariable` filled with ones, closer to NumPy's syntax than ``alloc``."""
-    if not isinstance(shape, (np.ndarray, Sequence, TensorVariable)):
+    if not (
+        isinstance(shape, (np.ndarray, Sequence))
+        or (isinstance(shape, TensorVariable) and shape.ndim > 0)
+    ):
         shape = [shape]
     if dtype is None:
         dtype = config.floatX
@@ -4274,6 +4280,11 @@ def empty(shape, dtype=None):
         Desired output data-type for the array, e.g, `numpy.int8`. Default is
         `numpy.float64`.
     """
+    if not (
+        isinstance(shape, (np.ndarray, Sequence))
+        or (isinstance(shape, TensorVariable) and shape.ndim > 0)
+    ):
+        shape = [shape]
     if dtype is None:
         dtype = config.floatX
     return AllocEmpty(dtype)(*shape)

tests/tensor/test_basic.py

@@ -754,6 +754,11 @@ class TestAlloc:
         for shp in [[], 1, [1], [1, 2], [1, 2, 3], np.r_[1, 2, 3]]:
             ones = aesara.function([], [at.ones(shp)], mode=self.mode)
             assert np.allclose(ones(), np.ones(shp))
+            # When shape is a TensorConstant
+            ones_const = aesara.function(
+                [], [at.ones(at.constant(shp))], mode=self.mode
+            )
+            assert np.allclose(ones_const(), np.ones(shp))
 
         # scalar doesn't have to be provided as input
         x = scalar()
@@ -771,6 +776,11 @@ class TestAlloc:
         for shp in [[], 1, [1], [1, 2], [1, 2, 3], np.r_[1, 2, 3]]:
             zeros = aesara.function([], [at.zeros(shp)], mode=self.mode)
             assert np.allclose(zeros(), np.zeros(shp))
+            # When shape is a TensorConstant
+            zeros_const = aesara.function(
+                [], [at.zeros(at.constant(shp))], mode=self.mode
+            )
+            assert np.allclose(zeros_const(), np.zeros(shp))
 
         # scalar doesn't have to be provided as input
         x = scalar()
@@ -4381,6 +4391,10 @@ def test_empty():
     assert out.shape == (2, 3)
     assert out.dtype == "float32"
 
+    empty_at = at.empty(3)
+    res = aesara.function([], empty_at)()
+    assert res.shape == (3,)
+
     empty_at = at.empty((2, 3), dtype=None)
     res = aesara.function([], empty_at)()
     assert res.shape == (2, 3)