Arm backend: Use dbg_fail when node visitors raise exceptions (#9391)

Adds a try-expect around the node_visitor call to be able to call
dbg_fail() when an error/exception is raised.

Signed-off-by: Oscar Andersson <oscar.andersson@arm.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>

Author: oscarandersson8218

backends/arm/ethosu_backend.py

@@ -23,7 +23,6 @@
 
 # debug functionality
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.WARNING)
 
 
 @final

backends/arm/process_node.py

@@ -14,11 +14,7 @@
 from executorch.backends.arm.operators.node_visitor import NodeVisitor
 from executorch.backends.arm.tosa_mapping import TosaArg
 from executorch.backends.arm.tosa_specification import TosaSpecification
-from executorch.backends.arm.tosa_utils import (
-    get_node_debug_info,
-    getNodeArgs,
-    tosa_shape,
-)
+from executorch.backends.arm.tosa_utils import getNodeArgs, tosa_shape
 from torch.export.exported_program import ExportedProgram
 
 
@@ -36,7 +32,7 @@ def process_call_function(
         output = TosaArg(node)
     except ValueError as e:
         raise ValueError(
-            f"Failed processing call_function:\n{get_node_debug_info(node)}"
+            f"Failed processing call_function: {node.name}. "
             "Is the original torch function supported?"
         ) from e
     tosa_graph.currRegion.currBasicBlock.addTensor(
@@ -74,7 +70,7 @@ def process_inputs(
         tosa_arg = TosaArg(node)
     except ValueError as e:
         raise ValueError(
-            f"Failed processing input placeholder:\n{get_node_debug_info(node)}"
+            f"Failed processing input placeholder: {node.name}. "
             "Is the original torch function supported?"
         ) from e
     input_shape = tosa_arg.shape
@@ -100,7 +96,7 @@ def process_inputs_to_parameters(
         tosa_arg = TosaArg(node)
     except ValueError as e:
         raise ValueError(
-            f"Failed processing parameter placeholder:\n{get_node_debug_info(node)}"
+            f"Failed processing parameter placeholder: {node.name}. "
             "Is the original torch function supported?"
         ) from e
     parameter_name = edge_program.graph_signature.inputs_to_parameters[tosa_arg.name]
@@ -129,7 +125,7 @@ def process_inputs_to_buffers(
         tosa_arg = TosaArg(node)
     except ValueError as e:
         raise ValueError(
-            f"Failed processing buffer placeholder:\n{get_node_debug_info(node)}"
+            f"Failed processing buffer placeholder: {node.name}. "
             "Is the original torch function supported?"
         ) from e
     buffer_name = edge_program.graph_signature.inputs_to_buffers[node.name]
@@ -157,7 +153,7 @@ def process_inputs_to_lifted_tensor_constants(
         tosa_arg = TosaArg(node)
     except ValueError as e:
         raise ValueError(
-            f"Failed processing lifted tensor constant placeholder:\n{get_node_debug_info(node)}"
+            f"Failed processing lifted tensor constant placeholder: {node.name}. "
             "Is the original torch function supported?"
         ) from e
     tensor_name = edge_program.graph_signature.inputs_to_lifted_tensor_constants[

backends/arm/tosa_backend.py

@@ -34,7 +34,6 @@
 
 # TOSA backend debug functionality
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.WARNING)
 TOSA_DBG_VERBOSE = os.environ.get("TOSA_DBG_VERBOSE") == "1"
 if TOSA_DBG_VERBOSE:
     logging.basicConfig(level=logging.INFO)
@@ -101,18 +100,22 @@ def preprocess(  # noqa: C901
         input_count = 0
         for node in graph_module.graph.nodes:
             node = cast(Node, node)
-            if node.op == "call_function":
-                process_call_function(node, tosa_graph, node_visitors, tosa_spec)
-            elif node.op == "placeholder":
-                process_placeholder(node, tosa_graph, edge_program, tosa_spec)
-                if node.name in edge_program.graph_signature.user_inputs:
-                    input_count += 1
-            elif node.op == "output":
-                process_output(node, tosa_graph)
-            else:
-                # This will only happen if an unpartitioned graph is passed without
-                # any checking of compatibility.
-                dbg_fail(node, tosa_graph, artifact_path)
+            try:
+                if node.op == "call_function":
+                    process_call_function(node, tosa_graph, node_visitors, tosa_spec)
+                elif node.op == "placeholder":
+                    process_placeholder(node, tosa_graph, edge_program, tosa_spec)
+                    if node.name in edge_program.graph_signature.user_inputs:
+                        input_count += 1
+                elif node.op == "output":
+                    process_output(node, tosa_graph)
+                else:
+                    # This will only happen if an unpartitioned graph is passed without
+                    # any checking of compatibility.
+                    raise RuntimeError(f"{node.name} is unsupported op {node.op}")
+            except (AssertionError, RuntimeError, ValueError):
+                dbg_fail(node, graph_module, tosa_graph, artifact_path)
+                raise
 
         if len(input_order) > 0:
             if input_count != len(input_order):

backends/arm/tosa_utils.py

@@ -7,31 +7,32 @@
 
 import logging
 import os
-from typing import Any, Tuple
+from typing import Any, Optional, Tuple
 
 import serializer.tosa_serializer as ts  # type: ignore
 import torch
 from executorch.backends.arm.tosa_mapping import TosaArg
 
 from executorch.exir.dialects._ops import ops as exir_ops
+from executorch.exir.print_program import inspect_node
 from serializer.tosa_serializer import TosaOp
 from torch.fx import Node
 
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.WARNING)
 TOSA_DBG_VERBOSE = os.environ.get("TOSA_DBG_VERBOSE") == "1"
 if TOSA_DBG_VERBOSE:
     logging.basicConfig(level=logging.INFO)
     logger.setLevel(logging.INFO)
 
 
-def dbg_node(node: torch.fx.Node):
+def dbg_node(node: torch.fx.Node, graph_module: torch.fx.GraphModule):
     # Debug output of node information
-    logger.info(get_node_debug_info(node))
+    logger.info(get_node_debug_info(node, graph_module))
 
 
-def get_node_debug_info(node: torch.fx.Node) -> str:
+def get_node_debug_info(node: torch.fx.Node, graph_module: torch.fx.GraphModule) -> str:
     output = (
+        f"  {inspect_node(graph=graph_module.graph, node=node)}\n"
         "-- NODE DEBUG INFO --\n"
         f"  Op is {node.op}\n"
         f"  Name is {node.name}\n"
@@ -71,21 +72,24 @@ def dbg_tosa_dump(tosa_graph: ts.TosaSerializer, path: str, suffix: str = ""):
     assert os.path.exists(filepath_desc_json), "Failed to write TOSA JSON"
 
 
-def dbg_fail(node, tosa_graph, path):
-    dbg_tosa_dump(tosa_graph, path)
+def dbg_fail(
+    node,
+    graph_module,
+    tosa_graph: Optional[ts.TosaSerializer] = None,
+    path: Optional[str] = None,
+):
     logger.warning("Internal error due to poorly handled node:")
-    dbg_node(node)
-    logger.warning(f"Debug output captured in '{path}'.")
-    raise RuntimeError("TOSA Internal Error on node, enable logging for further info.")
+    if tosa_graph is not None and path is not None:
+        dbg_tosa_dump(tosa_graph, path)
+        logger.warning(f"Debug output captured in '{path}'.")
+    dbg_node(node, graph_module)
 
 
 def getNodeArgs(node: Node) -> list[TosaArg]:
     try:
         return [TosaArg(arg) for arg in node.args]
     except ValueError as e:
-        raise ValueError(
-            f"Failed processing args to op:\n{get_node_debug_info(node)}"
-        ) from e
+        raise ValueError(f"Failed processing args to op:\n{node}") from e
 
 
 def get_output_node(node: Node) -> Node: