and and not passing

Author: Z80coder

neurallogic/hard_not.py

@@ -19,6 +19,7 @@ def soft_not(w: float, x: float) -> float:
 
 
 def hard_not(w: bool, x: bool) -> bool:
+    # ~(x ^ w)
     return jax.numpy.logical_not(jax.numpy.logical_xor(x, w))
 
 

neurallogic/symbolic_primitives.py

@@ -122,42 +122,40 @@ def unary_operator(operator: str, x: list):
 
 
 @dispatch
-def binary_infix_operator(operator: str, a: str, b: str, bracket: bool = False) -> str:
-    if bracket:
-        return f"({a} {operator} {b})"
+def binary_infix_operator(operator: str, a: str, b: str) -> str:
     return f"{a} {operator} {b}"
 
 
 @dispatch
-def binary_infix_operator(operator: str, a: numpy.ndarray, b: numpy.ndarray, bracket: bool = False):
-    return numpy.vectorize(binary_infix_operator, otypes=[object])(operator, a, b, bracket)
+def binary_infix_operator(operator: str, a: numpy.ndarray, b: numpy.ndarray):
+    return numpy.vectorize(binary_infix_operator, otypes=[object])(operator, a, b)
 
 
 @dispatch
-def binary_infix_operator(operator: str, a: list, b: numpy.ndarray, bracket: bool = False):
-    return binary_infix_operator(operator, numpy.array(a), b, bracket)
+def binary_infix_operator(operator: str, a: list, b: numpy.ndarray):
+    return binary_infix_operator(operator, numpy.array(a), b)
 
 
 @dispatch
-def binary_infix_operator(operator: str, a: numpy.ndarray, b: list, bracket: bool = False):
-    return binary_infix_operator(operator, a, numpy.array(b), bracket)
+def binary_infix_operator(operator: str, a: numpy.ndarray, b: list):
+    return binary_infix_operator(operator, a, numpy.array(b))
 
 
 @dispatch
-def binary_infix_operator(operator: str, a: str, b: int, bracket: bool = False):
-    return binary_infix_operator(operator, a, str(b), bracket)
+def binary_infix_operator(operator: str, a: str, b: int):
+    return binary_infix_operator(operator, a, str(b))
 
 @dispatch
-def binary_infix_operator(operator: str, a: numpy.ndarray, b: float, bracket: bool = False):
-    return binary_infix_operator(operator, a, str(b), bracket)
+def binary_infix_operator(operator: str, a: numpy.ndarray, b: float):
+    return binary_infix_operator(operator, a, str(b))
 
 @dispatch
-def binary_infix_operator(operator: str, a: str, b: float, bracket: bool = False):
-    return binary_infix_operator(operator, a, str(b), bracket)
+def binary_infix_operator(operator: str, a: str, b: float):
+    return binary_infix_operator(operator, a, str(b))
 
 @dispatch
-def binary_infix_operator(operator: str, a: numpy.ndarray, b: jax.numpy.ndarray, bracket: bool = False):
-    return binary_infix_operator(operator, a, numpy.array(b), bracket)
+def binary_infix_operator(operator: str, a: numpy.ndarray, b: jax.numpy.ndarray):
+    return binary_infix_operator(operator, a, numpy.array(b))
 
 
 def all_concrete_values(data):
@@ -185,7 +183,7 @@ def symbolic_ne(*args, **kwargs):
     if all_concrete_values([*args]):
         return numpy.not_equal(*args, **kwargs)
     else:
-        return binary_infix_operator("!=", *args, **kwargs)
+        return "(" + binary_infix_operator("!=", *args, **kwargs) + ")"
 
 def symbolic_gt(*args, **kwargs):
     if all_concrete_values([*args]):
@@ -204,14 +202,14 @@ def symbolic_or(*args, **kwargs):
     if all_concrete_values([*args]):
         return numpy.logical_or(*args, **kwargs)
     else:
-        return binary_infix_operator("or", *args, **kwargs, bracket=True)
+        return "(" + binary_infix_operator("or", *args, **kwargs) + ")"
 
 
 def symbolic_xor(*args, **kwargs):
     if all_concrete_values([*args]):
         return numpy.logical_xor(*args, **kwargs)
     else:
-        return binary_infix_operator("^", *args, **kwargs, bracket=False)
+        return binary_infix_operator("^", *args, **kwargs)
 
 
 

tests/test_hard_and.py

@@ -198,17 +198,17 @@ def test_net(type, x):
     symbolic_input = ['x1', 'x2']
     symbolic_output = symbolic.apply(hard_weights, symbolic_input)
     # Check the form of the symbolic expression
-    assert numpy.array_equal(symbolic_output, ['True and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True) and (True and (x1 != 0 or False) and (x2 != 0 or False) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True)',
- 'True and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or False) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True)',
- 'True and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True) and (True and (x1 != 0 or False) and (x2 != 0 or False) != 0 or True) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True)',
- 'True and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or True) and (True and (x1 != 0 or False) and (x2 != 0 or False) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False) and (True and (x1 != 0 or False) and (x2 != 0 or True) != 0 or False)'])
+    assert numpy.array_equal(symbolic_output, ['True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
+ 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
+ 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
+ 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False)'])
 
     # Compute symbolic result with symbolic inputs and symbolic weights
     symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
     # Check the form of the symbolic expression
-    assert numpy.array_equal(symbolic_output, ['True and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(True != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0))',
- 'True and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(True != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0))',
- 'True and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(True != 0)) != 0 or not(False != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0))',
- 'True and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(False != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(True != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0)) and (True and (x1 != 0 or not(True != 0)) and (x2 != 0 or not(False != 0)) != 0 or not(True != 0))'])
+    assert numpy.array_equal(symbolic_output, ['True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
+ 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
+ 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
+ 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0)))'])
 
 

tests/test_hard_not.py

@@ -170,7 +170,7 @@ def test_net(type, x):
     soft, hard, symbolic = neural_logic_net.net(test_net)
 
     # Compute soft result
-    soft_input = jax.numpy.array([0.0, 0.0])
+    soft_input = jax.numpy.array([1.0, 0.0])
     weights = soft.init(random.PRNGKey(0), soft_input)
     soft_result = soft.apply(weights, numpy.array(soft_input))
 
@@ -186,92 +186,86 @@ def test_net(type, x):
     # Check that the symbolic result is the same as the hard result
     assert numpy.array_equal(symbolic_output, hard_result)
 
+    # Compute symbolic result with symbolic inputs and symbolic weights, but where the symbols can be evaluated
+    symbolic_input = ['True', 'False']
+    symbolic_weights = symbolic_generation.make_symbolic(hard_weights)
+    symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
+    symbolic_output = symbolic_generation.eval_symbolic_expression(symbolic_output)
+    # Check that the symbolic result is the same as the hard result
+    assert numpy.array_equal(symbolic_output, hard_result)
+
     # Compute symbolic result with symbolic inputs and non-symbolic weights
     symbolic_input = ['x1', 'x2']
     symbolic_output = symbolic.apply(hard_weights, symbolic_input)
     # Check the form of the symbolic expression
-    """
-        assert numpy.array_equal(symbolic_output, ['not(not(x1 != 0 ^ True) != 0 ^ True)',
-    'not(not(x2 != 0 ^ True) != 0 ^ True)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ False)',
-    'not(not(x1 != 0 ^ True) != 0 ^ False)',
-    'not(not(x2 != 0 ^ True) != 0 ^ True)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ False)',
-    'not(not(x1 != 0 ^ True) != 0 ^ True)',
-    'not(not(x2 != 0 ^ True) != 0 ^ False)',
-    'not(not(x1 != 0 ^ False) != 0 ^ True)',
-    'not(not(x2 != 0 ^ False) != 0 ^ True)',
-    'not(not(x1 != 0 ^ True) != 0 ^ False)',
-    'not(not(x2 != 0 ^ True) != 0 ^ False)',
-    'not(not(x1 != 0 ^ False) != 0 ^ True)',
-    'not(not(x2 != 0 ^ False) != 0 ^ True)',
-    'not(not(x1 != 0 ^ True) != 0 ^ False)',
-    'not(not(x2 != 0 ^ True) != 0 ^ True)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ False)',
-    'not(not(x1 != 0 ^ True) != 0 ^ True)',
-    'not(not(x2 != 0 ^ True) != 0 ^ True)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ True)',
-    'not(not(x1 != 0 ^ True) != 0 ^ True)',
-    'not(not(x2 != 0 ^ True) != 0 ^ False)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ False)',
-    'not(not(x1 != 0 ^ True) != 0 ^ False)',
-    'not(not(x2 != 0 ^ True) != 0 ^ True)',
-    'not(not(x1 != 0 ^ False) != 0 ^ False)',
-    'not(not(x2 != 0 ^ False) != 0 ^ False)'])
-    """
+    assert numpy.array_equal(symbolic_output, ['not((not((x1 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x1 != 0) ^ True) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ True) != 0) ^ True)',
+ 'not((not((x1 != 0) ^ False) != 0) ^ False)',
+ 'not((not((x2 != 0) ^ False) != 0) ^ False)'])
 
     # Compute symbolic result with symbolic inputs and symbolic weights
-    symbolic_weights = symbolic_generation.make_symbolic(hard_weights)
     symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
     # Check the form of the symbolic expression
-    """
-        assert numpy.array_equal(symbolic_output, ['not(not(x1 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x1 != 0 ^ True != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ True != 0) != 0 ^ True != 0)',
-    'not(not(x1 != 0 ^ False != 0) != 0 ^ False != 0)',
-    'not(not(x2 != 0 ^ False != 0) != 0 ^ False != 0)'])
-    """
+    assert numpy.array_equal(symbolic_output, ['not((not((x1 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x1 != 0) ^ (True != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (True != 0)) != 0) ^ (True != 0))',
+ 'not((not((x1 != 0) ^ (False != 0)) != 0) ^ (False != 0))',
+ 'not((not((x2 != 0) ^ (False != 0)) != 0) ^ (False != 0))'])
 
-    # Compute symbolic result with symbolic inputs and symbolic weights, but where the symbols can be evaluated
-    symbolic_input = ['True', 'False']
-    symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
-    print(f'symbolic_output = {symbolic_output}')
-    symbolic_output = symbolic_generation.eval_symbolic_expression(symbolic_output)
-    # Check that the symbolic result is the same as the hard result
-    print(f'symbolic_output = {symbolic_output}')
-    print(f'hard_result = {hard_result}')
-    assert numpy.array_equal(symbolic_output, hard_result)