Handle same tensor appearing multiple times in the cat input

Summary: GenerateCatNopConstraints pass in memory planning was crashing when the same tensor appeared multiple times in a single cat operation's input list at different positions.

Differential Revision: D88439174

Author: ethansfng

backends/cadence/aot/memory_constraints.py

@@ -417,6 +417,10 @@ def is_slice_view(self, node: torch.fx.Node) -> bool:
             return not self.constraint.is_alias_of(source_info.source, node)
         return False
 
+    def has_relative_placement_constraint(self, node: torch.fx.Node) -> bool:
+        """Return if `node` already has any relative placement constraint."""
+        return self.constraint.get_relative_placement_source(node) is not None
+
     # Return true if the cat node performs concatenation along outermost dimension
     def is_cat_along_outermost_dim(
         self, graph_module: torch.fx.GraphModule, cat_node: torch.fx.Node
@@ -481,6 +485,17 @@ def is_removable_cat_op(
         if any(self.is_slice_view(arg) for arg in cat_tensors):
             return False
 
+        # If any of the tensors already has a relative placement constraint,
+        # we cannot add a new constraint for this cat without conflicting.
+        # This can happen when a tensor is used in multiple cat operations.
+        if any(self.has_relative_placement_constraint(arg) for arg in cat_tensors):
+            return False
+
+        # If the same tensor appears multiple times in the cat inputs,
+        # we cannot place it at multiple different offsets relative to the output.
+        if len(cat_tensors) != len(set(cat_tensors)):
+            return False
+
         # Many ops in HiFi require the input to be aligned to 8-byte boundary.
         # If the cat is not the graph's output, then ensure that the relative
         # offset of any concatenated non-placeholder tensor is a multiple of