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[5597849] Fix for 'SymbolicShapeInference' error #453

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Merged
merged 4 commits into from
Oct 21, 2025
Merged

[5597849] Fix for 'SymbolicShapeInference' error #453

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57b24fa
Fix for 'SymbolicShapeInference' error
gcunhase Oct 20, 2025
543c2ca
Replaced onnx.shape_inferend.infer_shapes with utils function
gcunhase Oct 20, 2025
a534933
Fix: add output info to value_info_map
gcunhase Oct 21, 2025
663d9f0
Ensure calibration_shapes is populated if calibrate_per_node is enabled
gcunhase Oct 21, 2025
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23 changes: 12 additions & 11 deletions modelopt/onnx/quantization/graph_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,6 @@
from onnx_graphsurgeon.ir.node import Node
from onnx_graphsurgeon.ir.tensor import Constant, Tensor, Variable
from onnxruntime.quantization.calibrate import CalibrationDataReader
from onnxruntime.tools.symbolic_shape_infer import SymbolicShapeInference

from modelopt.onnx.logging_config import logger
from modelopt.onnx.op_types import is_copy_op, is_linear_op
Expand All @@ -36,6 +35,7 @@
find_lowest_common_ancestor,
get_child_nodes,
get_parent_nodes,
infer_shapes,
parse_shapes_spec,
save_onnx,
)
Expand Down Expand Up @@ -966,7 +966,7 @@ def find_nodes_from_matmul_to_exclude(
logger.debug(f"Found {len(matmul_nodes)} MatMul nodes to analyze")

if calibration_shapes:
nodes_to_exclude = _exclude_matmuls_by_symbolic_inference(
nodes_to_exclude = _exclude_matmuls_by_shape_inference(
model, matmul_nodes, calibration_shapes
)
else:
Expand Down Expand Up @@ -1058,10 +1058,10 @@ def find_nodes_from_convs_to_exclude(graph: Graph, quantize_mode: str = "int8"):
return unsupported_conv_nodes


def _exclude_matmuls_by_symbolic_inference(
def _exclude_matmuls_by_shape_inference(
model: onnx.ModelProto, matmul_nodes: list, calibration_shapes: str | dict | None = None
) -> list[str]:
"""Use symbolic shape inference to find MatMuls with dimension 1."""
"""Use shape inference to find MatMuls with dimension 1."""
# Prepare model for symbolic inference
for graph_input in model.graph.input:
for dim in graph_input.type.tensor_type.shape.dim:
Expand All @@ -1070,11 +1070,13 @@ def _exclude_matmuls_by_symbolic_inference(
dim.dim_value = 1

# Apply calibration shapes if provided
input_shapes = (
parse_shapes_spec(calibration_shapes)
if (calibration_shapes and isinstance(calibration_shapes, str))
else {}
)
input_shapes = {}
if calibration_shapes:
input_shapes = (
parse_shapes_spec(calibration_shapes)
if isinstance(calibration_shapes, str)
else calibration_shapes
)
for graph_input in model.graph.input:
if graph_input.name in input_shapes:
input_shape = input_shapes[graph_input.name]
Expand All @@ -1087,8 +1089,7 @@ def _exclude_matmuls_by_symbolic_inference(
for dim, new_dim_value in zip(tensor_shape, input_shape):
dim.dim_value = new_dim_value

model.graph.ClearField("value_info")
model = SymbolicShapeInference.infer_shapes(model)
model = infer_shapes(model)
value_info_map = {vi.name: vi for vi in model.graph.value_info}

nodes_to_exclude = []
Expand Down
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