[ONNX] Add ReduceLogSum-11,13,18 (#23508)

### Details: - Extended ReduceLogSum by opsets 11,13,18 ### Tickets: - Closes #20561 --------- Co-authored-by: Katarzyna Mitrus <[email protected]> Co-authored-by: Georgy Krivoruchko <[email protected]>
openvinotoolkit · Mar 28, 2024 · e4b82a5 · e4b82a5
1 parent f0ebba0
commit e4b82a5
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Showing 7 changed files with 159 additions and 5 deletions.
diff --git a/src/frontends/onnx/frontend/src/op/reduce.cpp b/src/frontends/onnx/frontend/src/op/reduce.cpp
@@ -141,7 +141,7 @@ std::shared_ptr<ov::Node> make_ov_reduction_op(const Node& node,
 namespace set_1 {
 ov::OutputVector reduce_log_sum(const ov::frontend::onnx::Node& node) {
     const ov::Output<ov::Node> sum_node =
-        make_ov_reduction_op<v1::ReduceSum>(node, node.get_ov_inputs().at(0), supported_types_v1);
+        make_ov_reduction_op<v1::ReduceSum>(node, node.get_ov_inputs().at(0), supported_types_v2);
     return {std::make_shared<v0::Log>(sum_node)};
 }
 
@@ -185,7 +185,6 @@ ov::OutputVector reduce_sum_square(const ov::frontend::onnx::Node& node) {
     return {make_ov_reduction_op<v1::ReduceSum>(node, square_node, supported_types_v1)};
 }
 }  // namespace set_1
-
 /*
     Opset 11 is skipped because there are no significant difference between opset1 and opset 11.
     Found difference is:
@@ -208,6 +207,11 @@ namespace set_18 {
 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, false)};
 }
+ov::OutputVector reduce_log_sum(const ov::frontend::onnx::Node& node) {
+    const ov::Output<ov::Node> sum_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)};
+}
 }  // 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
@@ -13,6 +13,9 @@ namespace op {
 namespace set_1 {
 ov::OutputVector reduce_log_sum(const ov::frontend::onnx::Node& node);
 }  // namespace set_1
+namespace set_18 {
+ov::OutputVector reduce_log_sum(const ov::frontend::onnx::Node& node);
+}  // namespace set_18
 
 namespace set_1 {
 ov::OutputVector reduce_log_sum_exp(const ov::frontend::onnx::Node& node);

diff --git a/src/frontends/onnx/frontend/src/ops_bridge.cpp b/src/frontends/onnx/frontend/src/ops_bridge.cpp
@@ -480,6 +480,8 @@ OperatorsBridge::OperatorsBridge() {
     REGISTER_OPERATOR("RandomUniformLike", 1, random_uniform_like);
     REGISTER_OPERATOR("Reciprocal", 1, reciprocal);
     REGISTER_OPERATOR("ReduceLogSum", 1, reduce_log_sum);
+    register_operator("ReduceLogSum", VersionRange{1, 17}, op::set_1::reduce_log_sum);
+    register_operator("ReduceLogSum", VersionRange::since(18), op::set_18::reduce_log_sum);
     REGISTER_OPERATOR("ReduceLogSumExp", 1, reduce_log_sum_exp);
     REGISTER_OPERATOR("ReduceL1", 1, reduce_l1);
     REGISTER_OPERATOR("ReduceL2", 1, reduce_l2);

diff --git a/src/frontends/onnx/tests/models/reduce_log_sum_18.prototxt b/src/frontends/onnx/tests/models/reduce_log_sum_18.prototxt
@@ -0,0 +1,48 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "A"
+    output: "B"
+    op_type: "ReduceLogSum"
+  }
+  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/models/reduce_log_sum_18_axes_as_input.prototxt b/src/frontends/onnx/tests/models/reduce_log_sum_18_axes_as_input.prototxt
@@ -0,0 +1,71 @@
+ir_version: 3
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "A"
+    input: "axes"
+    output: "B"
+    op_type: "ReduceLogSum"
+  }
+  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
+          }
+        }
+      }
+    }
+  }
+  input {
+    name: "axes"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim {
+            dim_value: 1
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "B"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 1
+          }
+          dim {
+            dim_value: 4
+          }
+          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
@@ -910,6 +910,35 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_log_sum) {
     test_case.run();
 }
 
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_log_sum_18) {
+    auto model = convert_model("reduce_log_sum_18.onnx");
+
+    // input data shape (1, 1, 4, 4)
+    Inputs inputs{
+        ov::test::NDArray<float, 4>({{{{1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}}}}).get_vector()};
+
+    // output data shape (1,)
+    auto expected_output = ov::test::NDArray<float, 4>({{{{2.77258872f}}}}).get_vector();
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    test_case.add_multiple_inputs(inputs);
+    test_case.add_expected_output(expected_output);
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_log_sum_18_axes_as_input) {
+    auto model = convert_model("reduce_log_sum_18_axes_as_input.onnx");
+    auto test_case = ov::test::TestCase(model, s_device);
+
+    test_case.add_input<float>(Shape{1, 1, 4, 4}, {2, 1, 4, 2, 3, 1, 3, 2, 4, 2, 4, 2, 2, 2, 1, 4});
+    test_case.add_input<int64_t>({3});
+
+    test_case.add_expected_output(Shape{1, 1, 4, 1},
+                                  std::vector<float>{2.19722458f, 2.19722458f, 2.48490665f, 2.19722458f});
+
+    test_case.run();
+}
+
 OPENVINO_TEST(${BACKEND_NAME}, onnx_model_reduce_log_sum_exp) {
     auto model = convert_model("reduce_log_sum_exp.onnx");
 

diff --git a/src/frontends/onnx/tests/tests_python/test_backend.py b/src/frontends/onnx/tests/tests_python/test_backend.py
@@ -492,7 +492,6 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_keepdims_example_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_keepdims_random_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_log_sum_negative_axes_cpu",
         "OnnxBackendNodeModelTest.test_reduce_mean_do_not_keepdims_example_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu",
         "OnnxBackendNodeModelTest.test_reduce_mean_do_not_keepdims_random_cpu",
@@ -708,7 +707,6 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
         xfail_issue_125493,
         "OnnxBackendNodeModelTest.test_reduce_l1_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_l2_empty_set_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_min_empty_set_cpu",
         "OnnxBackendNodeModelTest.test_reduce_prod_empty_set_cpu",
@@ -721,7 +719,6 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
     (
         skip_misalignment,
         "OnnxBackendNodeModelTest.test_gelu_default_2_expanded_cpu",
-        "OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_expanded_cpu",
         "OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_expanded_cpu",
     ),
     (