Solving issue #20221 (#20237)

* added validation checks and raised error if an invalid input shape is passed to compute_output_shape func in UnitNormalization Layer

* updated my change to check if the input is int or an iterable before iterating

* Update unit_normalization.py

---------

Co-authored-by: François Chollet <francois.chollet@gmail.com>

keras/src/layers/normalization/unit_normalization.py

@@ -43,6 +43,18 @@ def call(self, inputs):
         return ops.normalize(inputs, axis=self.axis, order=2, epsilon=1e-12)
 
     def compute_output_shape(self, input_shape):
+        # Ensure axis is always treated as a list
+        if isinstance(self.axis, int):
+            axes = [self.axis]
+        else:
+            axes = self.axis
+
+        for axis in axes:
+            if axis >= len(input_shape) or axis < -len(input_shape):
+                raise ValueError(
+                    f"Axis {self.axis} is out of bounds for "
+                    f"input shape {input_shape}."
+                )
         return input_shape
 
     def get_config(self):