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Clamp Shape slice bounds before eliminating Shape #351

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Merged
take-cheeze merged 4 commits into from
Oct 2, 2026
Merged

Clamp Shape slice bounds before eliminating Shape #351

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591407f
Clamp Shape slice bounds before eliminating Shape
Yuhx141 Oct 1, 2026
b8efc3b
Make sequence type test self-contained
Yuhx141 Oct 1, 2026
6c4a1ea
Remove unrelated sequence test change
Yuhx141 Oct 1, 2026
d1ad847
Merge branch 'main' into fix-shape-slice-bounds
take-cheeze Oct 2, 2026
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14 changes: 9 additions & 5 deletions onnxoptimizer/passes/pass_util.h
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Original file line number Diff line number Diff line change
Expand Up @@ -320,11 +320,15 @@ inline std::pair<int64_t, int64_t> FetchStartAndEndAttrOfShape(
const Node* shape, const int64_t rank) {
ONNX_ASSERT(CheckKind(shape, "Shape"));

const int64_t start = AddYIfNegative<int64_t>(
GetValueFromAttrWithDefault(shape, "start", 0), rank);
const int64_t end = AddYIfNegative<int64_t>(
GetValueFromAttrWithDefault(shape, "end", rank), rank);
return {start, end};
const int64_t start = std::clamp<int64_t>(
AddYIfNegative<int64_t>(
GetValueFromAttrWithDefault(shape, "start", 0), rank),
0, rank);
const int64_t end = std::clamp<int64_t>(
AddYIfNegative<int64_t>(
GetValueFromAttrWithDefault(shape, "end", rank), rank),
0, rank);
return {start, std::max(start, end)};
}

inline std::pair<int64_t, int64_t> FetchStartAndEndAttrOfShape(
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25 changes: 25 additions & 0 deletions onnxoptimizer/test/optimizer_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3652,6 +3652,31 @@ def test_eliminate_shape_op(self): # type: () -> None
assert len(optimized_model.graph.node) == 1
assert optimized_model.graph.node[0].op_type == "Relu"

def test_eliminate_shape_op_clamps_start_beyond_rank(self): # type: () -> None
X = helper.make_tensor_value_info("X", TensorProto.FLOAT, [3, 2])
X2 = helper.make_tensor_value_info("X2", TensorProto.INT64, [0])
Y = helper.make_tensor_value_info("Y", TensorProto.INT64, [0])
graph = helper.make_graph(
[
helper.make_node("Shape", ["X"], ["X2"], start=5),
helper.make_node("Identity", ["X2"], ["Y"]),
],
"test",
[X],
[Y],
value_info=[X2],
)
optimized_model = self._optimized(
graph,
["eliminate_shape_op"],
False,
opset_imports=[helper.make_opsetid("", 15)],
)

assert len(optimized_model.graph.node) == 1
assert optimized_model.graph.node[0].op_type == "Identity"
assert numpy_helper.to_array(optimized_model.graph.initializer[0]).tolist() == []

# Some exporters use negative dim to represent dynamic shapes.
def test_not_eliminate_shape_op_with_negative_dim(self): # type: () -> None
X = helper.make_tensor_value_info("X", TensorProto.FLOAT, [3, -1])
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