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vatsalashanubhagvatsalashanubhag
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test qlinear softmax
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‎src/frontends/onnx/tests/models/com.microsoft/qlinear_softmax_opset12.prototxt

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ir_version: 3
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producer_name: "OpenVINO ONNX Frontend"
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producer_version: ""
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model_version: 0
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graph {
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name: "test_qlinear_softmax_opset12"
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node {
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input: "X"
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input: "X_scale"
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input: "X_zero_point"
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input: "Y_scale"
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input: "Y_zero_point"
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output: "Y"
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op_type: "QLinearSoftmax"
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attribute {
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name: "opset"
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i: 12
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type: INT
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}
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domain: "com.microsoft"
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}
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input {
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name: "X"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 4 }
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dim { dim_value: 5 }
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}
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}
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}
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}
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input {
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name: "X_scale"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "X_zero_point"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "Y_scale"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "Y_zero_point"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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output {
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name: "Y"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 4 }
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dim { dim_value: 5 }
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}
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}
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}
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}
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}
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opset_import {
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version: 1
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}

‎src/frontends/onnx/tests/models/com.microsoft/qlinear_softmax_opset13.prototxt

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ir_version: 3
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producer_name: "OpenVINO ONNX Frontend"
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producer_version: ""
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model_version: 0
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graph {
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name: "test_qlinear_softmax"
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node {
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input: "X"
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input: "X_scale"
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input: "X_zero_point"
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input: "Y_scale"
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input: "Y_zero_point"
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output: "Y"
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op_type: "QLinearSoftmax"
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attribute {
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name: "axis"
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i: -1
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type: INT
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}
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attribute {
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name: "opset"
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i: 12
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type: INT
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}
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domain: "com.microsoft"
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}
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input {
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name: "X"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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}
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}
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}
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}
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input {
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name: "X_scale"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "X_zero_point"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "Y_scale"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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input {
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name: "Y_zero_point"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 1 }
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}
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}
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}
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}
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output {
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name: "Y"
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type {
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tensor_type {
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elem_type: 3
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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}
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}
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}
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}
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}
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opset_import {
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version: 1
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}

‎src/frontends/onnx/tests/onnx_import_com_microsoft.in.cpp

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@@ -1740,3 +1740,48 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_bias_add) {
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test_case.run();
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}
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OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearsoftmax) {
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const auto model = convert_model("com.microsoft/qlinear_softmax_opset13.onnx");
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auto test_case = ov::test::TestCase(model, s_device);
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const std::vector<int8_t> data_X{-50, -25, 0, 25, 50, 75};
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const std::vector<float> x_scale{0.1f};
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const std::vector<int8_t> x_zero_point{0};
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const std::vector<float> y_scale{0.03f};
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const std::vector<int8_t> y_zero_point{5};
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const std::vector<int8_t> expected_output{5, 7, 35, 5, 7, 35};
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test_case.add_input<int8_t>(Shape{2, 3}, data_X);
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test_case.add_input<float>(Shape{1}, x_scale);
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test_case.add_input<int8_t>(Shape{1}, x_zero_point);
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test_case.add_input<float>(Shape{1}, y_scale);
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test_case.add_input<int8_t>(Shape{1}, y_zero_point);
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test_case.add_expected_output<int8_t>(Shape{2, 3}, expected_output);
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test_case.run();
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}
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OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearsoftmax_opset12) {
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const auto model = convert_model("com.microsoft/qlinear_softmax_opset12.onnx");
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auto test_case = ov::test::TestCase(model, s_device);
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const std::vector<int8_t> data_X{-60, -40, -20, 0, 20, 40, 60, 80, 100, 120,
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-10, -5, 0, 5, 10, -80, -60, -40, -20, 0};
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const std::vector<float> x_scale{0.15f};
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const std::vector<int8_t> x_zero_point{0};
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const std::vector<float> y_scale{0.05f};
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const std::vector<int8_t> y_zero_point{3};
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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};
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test_case.add_input<int8_t>(Shape{4, 5}, data_X);
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test_case.add_input<float>(Shape{1}, x_scale);
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test_case.add_input<int8_t>(Shape{1}, x_zero_point);
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test_case.add_input<float>(Shape{1}, y_scale);
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test_case.add_input<int8_t>(Shape{1}, y_zero_point);
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test_case.add_expected_output<int8_t>(Shape{4, 5}, expected_output);
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test_case.run();
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}

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