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Fix TransposeOptimizer type error on zero-point-less DequantizeLinear (#28716) #29192

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Merged
tianleiwu merged 3 commits into from
Jun 20, 2026
Merged

Fix TransposeOptimizer type error on zero-point-less DequantizeLinear (#28716) #29192

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d4a1073
Fix transpose optimizer type error for zero-point-less DQ (#28716)
tairenpiao Jun 20, 2026
0b89da1
Fix test build: pass opset as int to avoid -Wbraced-scalar-init
tairenpiao Jun 20, 2026
ec6e7b4
Skip transpose push-through when output_dtype can't pin the Q type
tairenpiao Jun 20, 2026
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11 changes: 10 additions & 1 deletion onnxruntime/core/optimizer/transpose_optimization/onnx_transpose_optimization.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -528,9 +528,18 @@ static bool MakeQDQNodeUnit(api::GraphRef& graph, const api::NodeRef& dq_node) {
inputs.push_back(zp_input.value());
}

// No zero-point: pin output_dtype to the DQ's type so the new Q doesn't default to uint8.
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std::optional<int64_t> q_output_dtype;
if (!zp_input.has_value() && IsOnnxDomain(dq_domain)) {
api::DataType dq_input_dtype = graph.GetValueInfo(dq_inputs[0])->DType();
if (dq_input_dtype != api::DataType::UNDEFINED && dq_input_dtype != api::DataType::UINT8) {
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q_output_dtype = static_cast<int64_t>(dq_input_dtype);
}
}

// Add Q
auto new_q_node = MakeQuantizeOp(graph, dq_domain, inputs, axis, dq_node.GetAttributeInt("block_size"),
dq_node.GetAttributeInt("output_dtype"), dq_node.GetAttributeInt("saturate"));
q_output_dtype, dq_node.GetAttributeInt("saturate"));
new_q_node->SetLayeringAnnotation(dq_node.GetLayeringAnnotation());
auto q_node_outputs = new_q_node->Outputs();

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26 changes: 26 additions & 0 deletions onnxruntime/test/optimizer/transpose_optimizer_test.cc
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Expand Up @@ -3773,6 +3773,32 @@ TEST(TransposeOptimizerTests, TestDequantizeLinearNoAxis) {
#endif
}

// Regression test for #28716: pushing a Transpose through a zero-point-less int8 DequantizeLinear
// inserts a QuantizeLinear that must set output_dtype, else it defaults to uint8 and Resolve() fails.
TEST(TransposeOptimizerTests, TestDequantizeLinearNoZeroPoint) {
auto build_test_case = [&](ModelTestBuilder& builder) {
auto* input0_arg = MakeInput<int8_t>(builder, {{2, -1, 6, 3}}, {2, 4, 6, 3}, -128, 127);
auto* scale_arg = MakeInput<float>(builder, std::vector<int64_t>{}, std::vector<int64_t>{}, {0.05f});
auto* transpose_1_out_0 = builder.MakeIntermediate();
auto* dq_out_0 = builder.MakeIntermediate();
auto* transpose_2_out_0 = builder.MakeOutput();

auto& transpose_1 = builder.AddNode("Transpose", {input0_arg}, {transpose_1_out_0});
transpose_1.AddAttribute("perm", std::vector<int64_t>{0, 3, 1, 2});
builder.AddNode("DequantizeLinear", {transpose_1_out_0, scale_arg}, {dq_out_0}); // no zero-point
auto& transpose_2 = builder.AddNode("Transpose", {dq_out_0}, {transpose_2_out_0});
transpose_2.AddAttribute("perm", std::vector<int64_t>{0, 2, 3, 1});
};

auto check_optimized_graph = [](InferenceSessionWrapper& session) {
EXPECT_EQ(EstimateTransposeCost(session.GetGraph()), 0);
};

// output_dtype requires ONNX opset 21.
TransformerTester(build_test_case, check_optimized_graph, TransformerLevel::Default,
TransformerLevel::Level1, /*opsets*/ {21});
}

TEST(TransposeOptimizerTests, TestCast) {
auto build_test_case_1 = [&](ModelTestBuilder& builder) {
auto* input0_arg = MakeInput<int32_t>(builder, {{-1, 4, -1, 5}}, {2, 4, 6, 5}, -1, 5);
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