test qlinear sigmoid

openvinotoolkit · Jan 7, 2025 · 1c45690 · 1c45690
1 parent 5ac27a9
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diff --git a/src/frontends/onnx/tests/models/com.microsoft/q_linear_leaky_relu.prototxt b/src/frontends/onnx/tests/models/com.microsoft/q_linear_leaky_relu.prototxt
@@ -0,0 +1,101 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+producer_version: ""
+model_version: 0
+graph {
+  name: "test_qlinear_leakyrelu"
+
+  node {
+    input: "X"
+    input: "X_scale"
+    input: "X_zero_point"
+    input: "Y_scale"
+    input: "Y_zero_point"
+    output: "Y"
+    op_type: "QLinearLeakyRelu"
+    attribute {
+     name: "alpha"
+     f: 0.1
+     type: FLOAT
+    }
+    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  # float
+        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
+}
diff --git a/src/frontends/onnx/tests/models/com.microsoft/q_linear_sigmoid.prototxt b/src/frontends/onnx/tests/models/com.microsoft/q_linear_sigmoid.prototxt
@@ -0,0 +1,112 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+producer_version: ""
+model_version: 0
+graph {
+  name: "test_qlinear_sigmoid"
+
+  node {
+    input: "X"
+    input: "X_scale"
+    input: "X_zero_point"
+    input: "Y_scale"
+    input: "Y_zero_point"
+    output: "Y"
+    op_type: "QLinearSigmoid"
+    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
+}
diff --git a/src/frontends/onnx/tests/onnx_import_com_microsoft.in.cpp b/src/frontends/onnx/tests/onnx_import_com_microsoft.in.cpp
@@ -1488,3 +1488,50 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_matmul_integer_to_float) {
 
     test_case.run();
 }
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearsigmoid) {
+    const auto model = convert_model("com.microsoft/q_linear_sigmoid.onnx");
+    auto test_case = ov::test::TestCase(model, s_device);
+
+    const std::vector<int8_t> data_X{-50, -25, 0, 25, 50, 75};
+
+    const std::vector<float> x_scale{0.1f};
+    const std::vector<int8_t> x_zero_point{0};
+    const std::vector<float> y_scale{0.2f};
+    const std::vector<int8_t> y_zero_point{0};
+
+    const std::vector<int8_t> expected_output{0, 0, 2, 4, 4, 4};
+
+    test_case.add_input<int8_t>(Shape{2, 3}, data_X);
+    test_case.add_input<float>(Shape{1}, x_scale);
+    test_case.add_input<int8_t>(Shape{1}, x_zero_point);
+    test_case.add_input<float>(Shape{1}, y_scale);
+    test_case.add_input<int8_t>(Shape{1}, y_zero_point);
+    test_case.add_expected_output<int8_t>(Shape{2, 3}, expected_output);
+
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_com_microsoft_qlinearleakyrelu) {
+    const auto model = convert_model("com.microsoft/q_linear_leaky_relu.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{0.2f};
+    const std::vector<int8_t> y_zero_point{0};
+
+    const std::vector<int8_t> expected_output{-2, -1, 0, 12, 25, 37};
+
+    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();
+}