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[ONNX] Added QLinearSoftmax from com.microsoft domain #29531

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[ONNX] Added QLinearSoftmax from com.microsoft domain #29531

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f04f1d8
implement qlinear softmax
vatsalashanubhag Mar 18, 2025
aa22bfa
test qlinear softmax
vatsalashanubhag Mar 18, 2025
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26 changes: 26 additions & 0 deletions src/frontends/onnx/frontend/src/op/com.microsoft/qlinear_activation.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -12,9 +12,13 @@
#include "openvino/op/divide.hpp"
#include "openvino/op/maximum.hpp"
#include "openvino/op/multiply.hpp"
#include "openvino/op/reshape.hpp"
#include "openvino/op/shape_of.hpp"
#include "openvino/op/sigmoid.hpp"
#include "openvino/op/softmax.hpp"
#include "openvino/op/subtract.hpp"
#include "utils/common.hpp"
#include "utils/reshape.hpp"

using namespace ov::op;

Expand Down Expand Up @@ -102,10 +106,32 @@ ov::OutputVector qlinear_avg_pool(const ov::frontend::onnx::Node& node) {
});
}

ov::OutputVector qlinear_softmax(const ov::frontend::onnx::Node& node) {
return qlinear_activation(node, [&](const std::shared_ptr<ov::Node>& input_dequantized) {
auto axis = node.get_attribute_value<int64_t>("axis", -1);
auto opset = node.get_attribute_value<int64_t>("opset");

auto shape = std::make_shared<v3::ShapeOf>(input_dequantized);

std::shared_ptr<ov::Node> softmax_result;
if (opset <= 12) {
const auto coerced_data = ov::op::util::flatten(input_dequantized, static_cast<int>(axis));
softmax_result = std::make_shared<v8::Softmax>(coerced_data, 1);
softmax_result = std::make_shared<v1::Reshape>(softmax_result, shape, false);
} else {
softmax_result = std::make_shared<v8::Softmax>(input_dequantized, axis);
}

return softmax_result;
});
}

bool register_multiple_operators(void) {
ONNX_OP_M("QLinearSigmoid", OPSET_SINCE(1), com_microsoft::opset_1::qlinear_sigmoid, MICROSOFT_DOMAIN);
ONNX_OP_M("QLinearLeakyRelu", OPSET_SINCE(1), com_microsoft::opset_1::qlinear_leaky_relu, MICROSOFT_DOMAIN);
ONNX_OP_M("QLinearAveragePool", OPSET_SINCE(1), com_microsoft::opset_1::qlinear_avg_pool, MICROSOFT_DOMAIN);
ONNX_OP_M("QLinearSoftmax", OPSET_SINCE(1), com_microsoft::opset_1::qlinear_softmax, MICROSOFT_DOMAIN);

return true;
}

Expand Down
101 changes: 101 additions & 0 deletions src/frontends/onnx/tests/models/com.microsoft/qlinear_softmax_opset12.prototxt
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@@ -0,0 +1,101 @@
ir_version: 3
producer_name: "OpenVINO ONNX Frontend"
producer_version: ""
model_version: 0
graph {
name: "test_qlinear_softmax_opset12"

node {
input: "X"
input: "X_scale"
input: "X_zero_point"
input: "Y_scale"
input: "Y_zero_point"
output: "Y"
op_type: "QLinearSoftmax"
attribute {
name: "opset"
i: 12
type: INT
}
domain: "com.microsoft"
}

input {
name: "X"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 4 }
dim { dim_value: 5 }
}
}
}
}

input {
name: "X_scale"
type {
tensor_type {
elem_type: 1
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "X_zero_point"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "Y_scale"
type {
tensor_type {
elem_type: 1
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "Y_zero_point"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 1 }
}
}
}
}

output {
name: "Y"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 4 }
dim { dim_value: 5 }
}
}
}
}
}

opset_import {
version: 1
}
106 changes: 106 additions & 0 deletions src/frontends/onnx/tests/models/com.microsoft/qlinear_softmax_opset13.prototxt
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@@ -0,0 +1,106 @@
ir_version: 3
producer_name: "OpenVINO ONNX Frontend"
producer_version: ""
model_version: 0
graph {
name: "test_qlinear_softmax"

node {
input: "X"
input: "X_scale"
input: "X_zero_point"
input: "Y_scale"
input: "Y_zero_point"
output: "Y"
op_type: "QLinearSoftmax"
attribute {
name: "axis"
i: -1
type: INT
}
attribute {
name: "opset"
i: 12
type: INT
}
domain: "com.microsoft"
}

input {
name: "X"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 2 }
dim { dim_value: 3 }
}
}
}
}

input {
name: "X_scale"
type {
tensor_type {
elem_type: 1
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "X_zero_point"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "Y_scale"
type {
tensor_type {
elem_type: 1
shape {
dim { dim_value: 1 }
}
}
}
}

input {
name: "Y_zero_point"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 1 }
}
}
}
}

output {
name: "Y"
type {
tensor_type {
elem_type: 3
shape {
dim { dim_value: 2 }
dim { dim_value: 3 }
}
}
}
}
}

opset_import {
version: 1
}
45 changes: 45 additions & 0 deletions src/frontends/onnx/tests/onnx_import_com_microsoft.in.cpp
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Expand Up @@ -1740,3 +1740,48 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_bias_add) {

test_case.run();
}

OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearsoftmax) {
const auto model = convert_model("com.microsoft/qlinear_softmax_opset13.onnx");
auto test_case = ov::test::TestCase(model, s_device);

const std::vector<int8_t> data_X{-50, -25, 0, 25, 50, 75};
const std::vector<float> x_scale{0.1f};
const std::vector<int8_t> x_zero_point{0};
const std::vector<float> y_scale{0.03f};
const std::vector<int8_t> y_zero_point{5};

const std::vector<int8_t> expected_output{5, 7, 35, 5, 7, 35};

test_case.add_input<int8_t>(Shape{2, 3}, data_X);
test_case.add_input<float>(Shape{1}, x_scale);
test_case.add_input<int8_t>(Shape{1}, x_zero_point);
test_case.add_input<float>(Shape{1}, y_scale);
test_case.add_input<int8_t>(Shape{1}, y_zero_point);

test_case.add_expected_output<int8_t>(Shape{2, 3}, expected_output);
test_case.run();
}

OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearsoftmax_opset12) {
const auto model = convert_model("com.microsoft/qlinear_softmax_opset12.onnx");
auto test_case = ov::test::TestCase(model, s_device);

const std::vector<int8_t> data_X{-60, -40, -20, 0, 20, 40, 60, 80, 100, 120,
-10, -5, 0, 5, 10, -80, -60, -40, -20, 0};
const std::vector<float> x_scale{0.15f};
const std::vector<int8_t> x_zero_point{0};
const std::vector<float> y_scale{0.05f};
const std::vector<int8_t> y_zero_point{3};

const std::vector<int8_t> expected_output{3, 3, 3, 3, 22, 3, 3, 3, 3, 22, 3, 4, 5, 8, 13, 3, 3, 3, 3, 22};

test_case.add_input<int8_t>(Shape{4, 5}, data_X);
test_case.add_input<float>(Shape{1}, x_scale);
test_case.add_input<int8_t>(Shape{1}, x_zero_point);
test_case.add_input<float>(Shape{1}, y_scale);
test_case.add_input<int8_t>(Shape{1}, y_zero_point);

test_case.add_expected_output<int8_t>(Shape{4, 5}, expected_output);
test_case.run();
}