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Replace debug handle with from_node to trace operator transformation #2339

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Jun 18, 2025
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Replace debug handle with from_node to trace operator transformation #2339

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75 changes: 38 additions & 37 deletions test/quantization/pt2e/test_numeric_debugger.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,6 @@
from torch.testing._internal.common_utils import IS_WINDOWS, run_tests

from torchao.quantization.pt2e import (
generate_numeric_debug_handle,
prepare_for_propagation_comparison,
)
from torchao.testing.pt2e.utils import PT2ENumericDebuggerTestCase
Expand All @@ -35,34 +34,35 @@ def test_simple(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
self._assert_each_node_has_debug_handle(ep)
debug_handle_map = self._extract_debug_handles(ep)
m = ep.module()
self._assert_each_node_has_debug_handle(m)
debug_handle_map = self._extract_debug_handles(m)

self.assertEqual(len(set(debug_handle_map.values())), len(debug_handle_map))

@unittest.skip("debug flow not working on model with conditional control flow")
def test_control_flow(self):
m = TestHelperModules.ControlFlow()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()

self._assert_each_node_has_debug_handle(ep)
debug_handle_map = self._extract_debug_handles(ep)
self._assert_each_node_has_debug_handle(m)
debug_handle_map = self._extract_debug_handles(m)

self.assertEqual(len(set(debug_handle_map.values())), len(debug_handle_map))

def test_copy_preserve_handle(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = torch.export.export(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()

self._assert_each_node_has_debug_handle(ep)
debug_handle_map_ref = self._extract_debug_handles(ep)
self._assert_each_node_has_debug_handle(m)
debug_handle_map_ref = self._extract_debug_handles(m)

ep_copy = copy.copy(ep)
debug_handle_map = self._extract_debug_handles(ep_copy)
debug_handle_map = self._extract_debug_handles(ep_copy.module())

self._assert_each_node_has_debug_handle(ep)
self.assertEqual(debug_handle_map, debug_handle_map_ref)
Expand All @@ -71,13 +71,12 @@ def test_deepcopy_preserve_handle(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = torch.export.export(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)

debug_handle_map_ref = self._extract_debug_handles(ep)
debug_handle_map_ref = self._extract_debug_handles(ep.module())
ep_copy = copy.deepcopy(ep)
debug_handle_map = self._extract_debug_handles(ep_copy)
debug_handle_map = self._extract_debug_handles(ep_copy.module())

self._assert_each_node_has_debug_handle(ep)
self._assert_each_node_has_debug_handle(ep.module())
self.assertEqual(debug_handle_map, debug_handle_map_ref)

@unittest.skip(
Expand All @@ -87,16 +86,16 @@ def test_re_export_preserve_handle(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()

self._assert_each_node_has_debug_handle(ep)
debug_handle_map_ref = self._extract_debug_handles(ep)
self._assert_each_node_has_debug_handle(m)
debug_handle_map_ref = self._extract_debug_handles(m)

ep_reexport = export_for_training(m, example_inputs, strict=True)
m_reexport = ep_reexport.module()

self._assert_each_node_has_debug_handle(ep_reexport)
debug_handle_map = self._extract_debug_handles(ep_reexport)
self._assert_each_node_has_debug_handle(m_reexport)
debug_handle_map = self._extract_debug_handles(m_reexport)

self.assertEqual(debug_handle_map, debug_handle_map_ref)

Expand All @@ -107,16 +106,17 @@ def test_run_decompositions_same_handle_id(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()

self._assert_each_node_has_debug_handle(ep)
debug_handle_map_ref = self._extract_debug_handles(ep)
self._assert_each_node_has_debug_handle(m)
debug_handle_map_ref = self._extract_debug_handles(m)

ep_copy = copy.copy(ep)
ep_copy = ep_copy.run_decompositions()
m_decomposed = ep_copy.module()

self._assert_each_node_has_debug_handle(ep_copy)
debug_handle_map = self._extract_debug_handles(ep_copy)
self._assert_each_node_has_debug_handle(m_decomposed)
debug_handle_map = self._extract_debug_handles(m_decomposed)

# checking the map still has the same ids, the node may change
self.assertEqual(
Expand All @@ -135,18 +135,19 @@ def test_run_decompositions_map_handle_to_new_nodes(self):
for m in test_models:
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()

self._assert_each_node_has_debug_handle(ep)
self._assert_each_node_has_debug_handle(m)
pre_decomp_to_debug_handle_map_ref = (
self._extract_debug_handles_with_prev_decomp_op(ep)
self._extract_debug_handles_with_prev_decomp_op(m)
)

ep_copy = copy.copy(ep)
ep_copy = ep_copy.run_decompositions()
self._assert_each_node_has_debug_handle(ep_copy)
m_decomposed = ep_copy.module()
self._assert_each_node_has_debug_handle(m_decomposed)
pre_decomp_to_debug_handle_map = (
self._extract_debug_handles_with_prev_decomp_op(ep_copy)
self._extract_debug_handles_with_prev_decomp_op(m_decomposed)
)

# checking the map still has the same ids, the node may change
Expand All @@ -158,7 +159,6 @@ def test_prepare_for_propagation_comparison(self):
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
m = ep.module()
m_logger = prepare_for_propagation_comparison(m)
ref = m(*example_inputs)
Expand All @@ -175,9 +175,10 @@ def test_added_node_gets_unique_id(self) -> None:
m = TestHelperModules.Conv2dThenConv1d()
example_inputs = m.example_inputs()
ep = export_for_training(m, example_inputs, strict=True)
generate_numeric_debug_handle(ep)
ref_handles = self._extract_debug_handles(ep)

ref_handles = self._extract_debug_handles(ep.module())
ref_counter = Counter(ref_handles.values())

for k, v in ref_counter.items():
self.assertEqual(
v,
Expand All @@ -199,10 +200,10 @@ def test_added_node_gets_unique_id(self) -> None:

# Regenerate handles, make sure only the new relu node has a new id, and
# it doesn't clash with any of the existing ids.
generate_numeric_debug_handle(ep)

self._assert_each_node_has_debug_handle(ep)
handles_after_modification = self._extract_debug_handles(ep)
m = ep.module()
self._assert_each_node_has_debug_handle(m)
handles_after_modification = self._extract_debug_handles(m)
handles_counter = Counter(handles_after_modification.values())
for name, handle in ref_handles.items():
self.assertIn(name, handles_after_modification)
Expand All @@ -219,7 +220,7 @@ def test_added_node_gets_unique_id(self) -> None:

# Check for relu specifically. Avoid hardcoding the handle id since it
# may change with future node ordering changes.
self.assertNotEqual(handles_after_modification["relu_default"], 0)
self.assertNotIn(handles_after_modification["relu_default"], ref_counter)
self.assertEqual(handles_counter[handles_after_modification["relu_default"]], 1)


Expand Down
5 changes: 3 additions & 2 deletions test/quantization/pt2e/test_quantize_pt2e.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@
)

import torchao
from torchao.quantization.pt2e import ObserverOrFakeQuantize, observer
from torchao.quantization.pt2e import FROM_NODE_KEY, ObserverOrFakeQuantize, observer
from torchao.quantization.pt2e.quantize_pt2e import (
convert_pt2e,
prepare_pt2e,
Expand Down Expand Up @@ -1499,7 +1499,8 @@ def forward(self, x):
for n in m.graph.nodes:
if n.op == "get_attr" and "frozen_param" in n.target:
for key in n.meta:
self.assertEqual(n.meta[key], weight_meta[key])
if key != FROM_NODE_KEY:
self.assertEqual(n.meta[key], weight_meta[key])

def test_save_load(self):
"""Test save/load a quantized model"""
Expand Down
2 changes: 2 additions & 0 deletions torchao/quantization/pt2e/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@

from torchao.quantization.pt2e._numeric_debugger import ( # noqa: F401
CUSTOM_KEY,
FROM_NODE_KEY,
NUMERIC_DEBUG_HANDLE_KEY,
compare_results,
extract_results_from_loggers,
Expand Down Expand Up @@ -132,6 +133,7 @@
"generate_numeric_debug_handle",
"CUSTOM_KEY",
"NUMERIC_DEBUG_HANDLE_KEY",
"FROM_NODE_KEY",
"prepare_for_propagation_comparison",
"extract_results_from_loggers",
"compare_results",
Expand Down
75 changes: 66 additions & 9 deletions torchao/quantization/pt2e/_numeric_debugger.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,10 +16,16 @@
from torch.fx import GraphModule, Node
from torch.nn import functional as F

from torchao.utils import TORCH_VERSION_AT_LEAST_2_6

if TORCH_VERSION_AT_LEAST_2_6:
from torch.fx.traceback import NodeSource

from .graph_utils import bfs_trace_with_node_process

NUMERIC_DEBUG_HANDLE_KEY = "numeric_debug_handle"
CUSTOM_KEY = "custom"
FROM_NODE_KEY = "from_node"

log = logging.getLogger(__name__)

Expand Down Expand Up @@ -78,6 +84,56 @@ def _assign_debug_handle(node: torch.fx.Node) -> None:
bfs_trace_with_node_process(ep, _assign_debug_handle)


def _get_greatest_ancestor_node_source(node: Node) -> Optional["NodeSource"]:
if (node_source := node.meta.get(FROM_NODE_KEY)) is None:
return None

node_source = node_source[-1]

while len(node_source.from_node) > 0:
node_source = node_source.from_node[-1]

return node_source


def _generate_debug_handle_from_node(node: Node) -> Optional[int]:
"""
Generate a debug handle based on node's oldest ancestor node's name
and graph id, or return None if the node does not need to be traced.

This is a temporary function for migrating node tracing infra from
using debug handle to node.meta["from_node"]. The infrastructure will
depend on node.meta["from_node"] directly in the future, without the need
of debug handle as intermediate variable.
"""

if node.op == "placeholder" or node.op == "output":
# placeholder and output nodes don't have debug handle
return None

if (
FROM_NODE_KEY not in node.meta
or node.meta[FROM_NODE_KEY] is None
or node.meta[FROM_NODE_KEY][-1].pass_name == "ExportedProgram.module().unlift()"
):
# This node is not part of the ExportedProgram.module().graph, so it doesn't have a debug handle
return None

greatest_ancestor_node_source = _get_greatest_ancestor_node_source(node)

if greatest_ancestor_node_source is None:
# This node is not part of the ExportedProgram.module().graph, so it doesn't have a debug handle
return None

if greatest_ancestor_node_source.pass_name == "ExportedProgram.module().unlift()":
# uplifted nodes don't have debug handle
return None

return hash(
greatest_ancestor_node_source.name + str(greatest_ancestor_node_source.graph_id)
)


def _detach(x: object) -> object:
detached: object = None
if isinstance(x, torch.Tensor):
Expand Down Expand Up @@ -187,23 +243,24 @@ def _insert_logger(model: GraphModule, node: Node, debug_handle: int) -> Node:


def prepare_for_propagation_comparison(model: GraphModule) -> GraphModule:
"""Add output loggers to node that has numeric_debug_handle
"""Add output loggers to unlifted node

Args:
model (GraphModule): original model
Returns:
a model with output loggers for all nodes that has numeric_debug_handle_id
a model with output loggers for all unlifted nodes
"""
if not TORCH_VERSION_AT_LEAST_2_6:
log.warning(
"prepare_for_propagation_comparison is only supported for PyTorch 2.6+"
)
return model

# don't change the original model
model = copy.deepcopy(model)
for n in model.graph.nodes:
if (
CUSTOM_KEY not in n.meta
or NUMERIC_DEBUG_HANDLE_KEY not in n.meta[CUSTOM_KEY]
):
continue
numeric_debug_handle = n.meta[CUSTOM_KEY][NUMERIC_DEBUG_HANDLE_KEY]
_insert_logger(model, n, numeric_debug_handle)
if (numeric_debug_handle := _generate_debug_handle_from_node(n)) is not None:
_insert_logger(model, n, numeric_debug_handle)

model.recompile()
return model
Expand Down
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