Remove duplicated utilities in cadence backend

Summary: Remove duplicated utilities between pass_utils and utils.py

Reviewed By: zonglinpeng

Differential Revision: D67184440

Author: Eashan Garg

backends/cadence/aot/memory_constraints.py

@@ -15,7 +15,7 @@
     create_cadence_pass_filter,
     register_cadence_pass,
 )
-from executorch.backends.cadence.aot.utils import get_shape, is_node_in_flattened_output
+from executorch.backends.cadence.aot.compiler_utils import get_shape, is_node_in_flattened_output
 from executorch.exir import memory
 from executorch.exir.pass_manager import PassManager
 from executorch.exir.tensor import num_bytes_from_shape_and_dtype, TensorSpec

backends/cadence/aot/utils.py

@@ -124,49 +124,6 @@ def get_ops_count(graph_module: torch.fx.GraphModule) -> Dict[str, int]:
     return freq
 
 
-# Return the output node of the graph
-def get_output_node(graph: torch.fx.Graph) -> torch.fx.Node:
-    assert graph is not None, "Cannot get output of an empty graph"
-    output_node = next(iter(reversed(graph.nodes)))
-    assert (
-        output_node and output_node.op == "output" and len(output_node.args) == 1
-    ), "Failed to find output node"
-    return output_node
-
-
-# Return true if the node is part of the flattened output
-def is_node_in_flattened_output(graph: torch.fx.Graph, node: torch.fx.Node) -> bool:
-    output_node = get_output_node(graph)
-    return node in tree_flatten(output_node.args[0])[0]
-
-
-# Return the shape of the incoming node.
-def get_shape(
-    graph_module: torch.fx.GraphModule, node: torch.fx.Node
-) -> Union[torch.Size, None]:
-    """
-    Return the shape of the tensor correspnding to node. If the node has a
-    tensor spec, return the shape from the metadata. If the node is a param,
-    return it shape. Otherwise return None.
-    """
-    try:
-        # Case 1. node is a scalar
-        if isinstance(node, (float, int, bool)):
-            return torch.Size([1])
-        # Case 2. node has TensorSpec metadata
-        fake_tensor = node.meta.get("val")
-        if fake_tensor is not None:
-            return fake_tensor.shape
-        # Case 3. node holds a param
-        if node.op == "get_attr":
-            attr_node = getattr(graph_module, node.target)
-            return attr_node.shape
-        # Default: return None
-        return None
-    except RuntimeError:
-        return None
-
-
 # Print the ops and how many times they occur multiple graph modules:
 # from export, from to_edge, and from final. Print the available
 # implementations for each op, and error out if the op is not supported.