Align behavior of ONNX Frontend function ReduceSumSquare-11, 13, 18 w…

…ith original framework (#23798) Hello maintainers, Since my previous PR (#22993 (comment)) had diverged significantly from the master branch, and also included additional changes, I thought it would be best to create a new PR. @gkrivor, could you please take a look? This closes #20563 (comment). --------- Co-authored-by: Georgy Krivoruchko <[email protected]>
openvinotoolkit · May 23, 2024 · 9025003 · 9025003
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commit 9025003
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Showing 7 changed files with 155 additions and 10 deletions.
diff --git a/src/frontends/onnx/frontend/src/op/reduce.cpp b/src/frontends/onnx/frontend/src/op/reduce.cpp
@@ -136,6 +136,14 @@ std::shared_ptr<ov::Node> make_ov_reduction_op(const Node& node,
         return set_1::identity(node).at(0).get_node_shared_ptr();
     }
 }
+
+std::shared_ptr<ov::Node> onnx_reduce_sum_square(const ov::frontend::onnx::Node& node,
+                                                 const std::set<element::Type>& supported_types,
+                                                 const bool axes_as_attr = true) {
+    const auto input = ov::Output<ov::Node>{node.get_ov_inputs().at(0)};
+    const auto square_node = std::make_shared<v1::Multiply>(input, input);
+    return make_ov_reduction_op<v1::ReduceSum>(node, square_node, supported_types, axes_as_attr);
+}
 }  // namespace
 
 namespace set_1 {
@@ -180,9 +188,7 @@ ov::OutputVector reduce_sum(const ov::frontend::onnx::Node& node) {
 }
 
 ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node) {
-    const auto input = ov::Output<ov::Node>{node.get_ov_inputs().at(0)};
-    const auto square_node = std::make_shared<v1::Multiply>(input, input);
-    return {make_ov_reduction_op<v1::ReduceSum>(node, square_node, supported_types_v1)};
+    return {onnx_reduce_sum_square(node, supported_types_v1)};
 }
 }  // namespace set_1
 
@@ -199,16 +205,22 @@ namespace set_13 {
 ov::OutputVector reduce_sum(const ov::frontend::onnx::Node& node) {
     return {make_ov_reduction_op<v1::ReduceSum>(node, node.get_ov_inputs().at(0), supported_types_v2, false)};
 }
+
 ov::OutputVector reduce_l2(const Node& node) {
     return {make_ov_reduction_op<v4::ReduceL2>(node, node.get_ov_inputs().at(0), supported_types_v2)};
 }
+
 ov::OutputVector reduce_max(const ov::frontend::onnx::Node& node) {
     return {make_ov_reduction_op<v1::ReduceMax>(node, node.get_ov_inputs().at(0), supported_types_v3)};
 }
 
 ov::OutputVector reduce_min(const ov::frontend::onnx::Node& node) {
     return {make_ov_reduction_op<v1::ReduceMin>(node, node.get_ov_inputs().at(0), supported_types_v3)};
 }
+
+ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node) {
+    return {onnx_reduce_sum_square(node, supported_types_v2)};
+}
 }  // namespace set_13
 
 namespace set_18 {
@@ -228,6 +240,10 @@ ov::OutputVector reduce_log_sum(const ov::frontend::onnx::Node& node) {
         make_ov_reduction_op<v1::ReduceSum>(node, node.get_ov_inputs().at(0), supported_types_v2, false);
     return {std::make_shared<v0::Log>(sum_node)};
 }
+
+ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node) {
+    return {onnx_reduce_sum_square(node, supported_types_v2, false)};
+}
 }  // namespace set_18
 
 namespace set_20 {

diff --git a/src/frontends/onnx/frontend/src/op/reduce.hpp b/src/frontends/onnx/frontend/src/op/reduce.hpp
@@ -79,6 +79,12 @@ ov::OutputVector reduce_sum(const ov::frontend::onnx::Node& node);
 namespace set_1 {
 ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node);
 }  // namespace set_1
+namespace set_13 {
+ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node);
+}  // namespace set_13
+namespace set_18 {
+ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node);
+}  // namespace set_18
 
 }  // namespace op
 }  // namespace onnx

diff --git a/src/frontends/onnx/frontend/src/ops_bridge.cpp b/src/frontends/onnx/frontend/src/ops_bridge.cpp
@@ -503,6 +503,8 @@ OperatorsBridge::OperatorsBridge() {
     REGISTER_OPERATOR("ReduceSum", 1, reduce_sum);
     REGISTER_OPERATOR("ReduceSum", 13, reduce_sum);
     REGISTER_OPERATOR("ReduceSumSquare", 1, reduce_sum_square);
+    REGISTER_OPERATOR("ReduceSumSquare", 13, reduce_sum_square);
+    REGISTER_OPERATOR("ReduceSumSquare", 18, reduce_sum_square);
     REGISTER_OPERATOR("Relu", 1, relu);
     REGISTER_OPERATOR("Reshape", 1, reshape);
     REGISTER_OPERATOR("Resize", 1, resize);

diff --git a/src/frontends/onnx/tests/models/reduce_sum_square_13.prototxt b/src/frontends/onnx/tests/models/reduce_sum_square_13.prototxt
@@ -0,0 +1,48 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "A"
+    output: "B"
+    op_type: "ReduceSumSquare"
+  }
+  name: "compute_graph"
+  input {
+    name: "A"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 4
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "B"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 1
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
diff --git a/src/frontends/onnx/tests/models/reduce_sum_square_18.prototxt b/src/frontends/onnx/tests/models/reduce_sum_square_18.prototxt
@@ -0,0 +1,48 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "A"
+    output: "B"
+    op_type: "ReduceSumSquare"
+  }
+  name: "compute_graph"
+  input {
+    name: "A"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 4
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "B"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 1
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 18
+}
diff --git a/src/frontends/onnx/tests/onnx_import.in.cpp b/src/frontends/onnx/tests/onnx_import.in.cpp
@@ -1257,6 +1257,38 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_sum_square) {
     test_case.run();
 }
 
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_sum_square_13) {
+    auto model = convert_model("reduce_sum_square_13.onnx");
+
+    // input data shape (1, 1, 4, 4)
+    Inputs inputs{
+        ov::test::NDArray<float, 4>({{{{1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}}}}).get_vector()};
+
+    // output data shape (1,)
+    auto expected_output = ov::test::NDArray<float, 4>({{{{16}}}}).get_vector();
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    test_case.add_multiple_inputs(inputs);
+    test_case.add_expected_output(expected_output);
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_sum_square_18) {
+    auto model = convert_model("reduce_sum_square_18.onnx");
+
+    // input data shape (1, 1, 4, 4)
+    Inputs inputs{
+        ov::test::NDArray<float, 4>({{{{1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}}}}).get_vector()};
+
+    // output data shape (1,)
+    auto expected_output = ov::test::NDArray<float, 4>({{{{16}}}}).get_vector();
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    test_case.add_multiple_inputs(inputs);
+    test_case.add_expected_output(expected_output);
+    test_case.run();
+}
+
 OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_sum_13_axes_as_constant) {
     auto model = convert_model("reduce_sum_13_axes_as_constant.onnx");
 

diff --git a/src/frontends/onnx/tests/tests_python/test_backend.py b/src/frontends/onnx/tests/tests_python/test_backend.py
@@ -488,12 +488,6 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
         "OnnxBackendNodeModelTest.test_reduce_prod_keepdims_random_cpu",
         "OnnxBackendNodeModelTest.test_reduce_prod_negative_axes_keepdims_example_cpu",
         "OnnxBackendNodeModelTest.test_reduce_prod_negative_axes_keepdims_random_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_do_not_keepdims_example_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_do_not_keepdims_random_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_keepdims_example_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_keepdims_random_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_negative_axes_keepdims_example_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_negative_axes_keepdims_random_cpu",
     ),
     (
         xfail_issue_99969,
@@ -685,7 +679,6 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
         "OnnxBackendNodeModelTest.test_reduce_l1_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_prod_empty_set_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_sum_square_empty_set_cpu",
     ),
     (
         skip_misalignment,