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[ONNX] Add ReduceLogSum-11,13,18 (openvinotoolkit#23508)
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### Details:
 - Extended ReduceLogSum by opsets 11,13,18


### Tickets:
 - Closes openvinotoolkit#20561

---------

Co-authored-by: Katarzyna Mitrus <[email protected]>
Co-authored-by: Georgy Krivoruchko <[email protected]>
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3 people authored Mar 28, 2024
1 parent f0ebba0 commit e4b82a5
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Showing 7 changed files with 159 additions and 5 deletions.
8 changes: 6 additions & 2 deletions src/frontends/onnx/frontend/src/op/reduce.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -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)};
}

Expand Down Expand Up @@ -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:
Expand All @@ -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 {
Expand Down
3 changes: 3 additions & 0 deletions src/frontends/onnx/frontend/src/op/reduce.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -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);
Expand Down
2 changes: 2 additions & 0 deletions src/frontends/onnx/frontend/src/ops_bridge.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -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);
Expand Down
48 changes: 48 additions & 0 deletions src/frontends/onnx/tests/models/reduce_log_sum_18.prototxt
Original file line number Diff line number Diff line change
@@ -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
}
Original file line number Diff line number Diff line change
@@ -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
}
29 changes: 29 additions & 0 deletions src/frontends/onnx/tests/onnx_import.in.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -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");

Expand Down
3 changes: 0 additions & 3 deletions src/frontends/onnx/tests/tests_python/test_backend.py
Original file line number Diff line number Diff line change
Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand All @@ -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",
),
(
Expand Down

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