Add support for com.microsoft.BiasGelu operator (#7480)

ngraph/frontend/onnx/frontend/src/op/com.microsoft/bias_gelu.cpp

@@ -0,0 +1,21 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "op/com.microsoft/bias_gelu.hpp"
+
+#include "default_opset.hpp"
+
+namespace ngraph {
+namespace onnx_import {
+namespace op {
+namespace set_1 {
+OutputVector bias_gelu(const Node& node) {
+    auto nodes = node.get_ng_inputs();
+    NGRAPH_CHECK(nodes.size() == 2, "BiasGelu takes 2 inputs. Provided " + std::to_string(nodes.size()));
+    return {std::make_shared<default_opset::Gelu>(std::make_shared<default_opset::Add>(nodes.at(0), nodes.at(1)))};
+}
+}  // namespace set_1
+}  // namespace op
+}  // namespace onnx_import
+}  // namespace ngraph

ngraph/frontend/onnx/frontend/src/op/com.microsoft/bias_gelu.hpp

@@ -0,0 +1,17 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "onnx_import/core/node.hpp"
+
+namespace ngraph {
+namespace onnx_import {
+namespace op {
+namespace set_1 {
+OutputVector bias_gelu(const Node& node);
+}  // namespace set_1
+}  // namespace op
+}  // namespace onnx_import
+}  // namespace ngraph

ngraph/frontend/onnx/frontend/src/ops_bridge.cpp

@@ -29,6 +29,7 @@
 #include "op/cast_like.hpp"
 #include "op/ceil.hpp"
 #include "op/clip.hpp"
+#include "op/com.microsoft/bias_gelu.hpp"
 #include "op/compress.hpp"
 #include "op/concat.hpp"
 #include "op/constant.hpp"
@@ -261,6 +262,8 @@ bool OperatorsBridge::_is_operator_registered(const std::string& name,
     }
 }
 
+static const char* const MICROSOFT_DOMAIN = "com.microsoft";
+
 #define REGISTER_OPERATOR(name_, ver_, fn_) \
     m_map[""][name_].emplace(ver_, std::bind(op::set_##ver_::fn_, std::placeholders::_1))
 
@@ -472,6 +475,8 @@ OperatorsBridge::OperatorsBridge() {
     REGISTER_OPERATOR_WITH_DOMAIN(OPENVINO_ONNX_DOMAIN, "PriorBox", 1, prior_box);
     REGISTER_OPERATOR_WITH_DOMAIN(OPENVINO_ONNX_DOMAIN, "PriorBoxClustered", 1, prior_box_clustered);
     REGISTER_OPERATOR_WITH_DOMAIN(OPENVINO_ONNX_DOMAIN, "Swish", 1, swish);
+
+    REGISTER_OPERATOR_WITH_DOMAIN(MICROSOFT_DOMAIN, "BiasGelu", 1, bias_gelu);
 }
 
 #undef REGISTER_OPERATOR

ngraph/test/models/onnx/bias_gelu.prototxt

@@ -0,0 +1,61 @@
+ir_version: 3
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "X"
+    input: "Y"
+    output: "out"
+    name: "Gelu_AddBias_1"
+    op_type: "BiasGelu"
+    domain: "com.microsoft"
+  }
+  name: "test_graph"
+  input {
+    name: "X"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 5
+          }
+        }
+      }
+    }
+  }
+  input {
+    name: "Y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 5
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "out"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 5
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}

ngraph/test/onnx/onnx_import.in.cpp

@@ -4150,3 +4150,23 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_model_random_uniform_like) {
     test_case.add_input<ngraph::float16>(Shape{2, 2}, {41, 42, 43, 44});
     test_case.run();
 }
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_bias_gelu) {
+    const auto function = onnx_import::import_onnx_model(file_util::path_join(SERIALIZED_ZOO, "onnx/bias_gelu.onnx"));
+
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>({0.5488135,
+                                0.71518934,
+                                0.60276335,
+                                0.5448832,
+                                0.4236548,
+                                0.6458941,
+                                0.4375872,
+                                0.891773,
+                                0.96366274,
+                                0.3834415});
+    test_case.add_input<float>({0.79172504, 0.5288949, 0.56804454, 0.92559665, 0.07103606});
+    test_case.add_expected_output<float>(
+        {1.2198428, 1.1112978, 1.0293297, 1.366493, 0.3411342, 1.329408, 0.8051748, 1.354462, 1.8336612, 0.3068893});
+    test_case.run();
+}