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ONNX Unique op support (#15076)

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Tomasz Dołbniak authored and GitHub committed 2023-01-16 15:12:03 +01:00
1 parent 14a7e443d0
commit f4dda48795
11 files changed
+522 -5
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src/bindings/python/tests/test_onnx/test_backend.py
-3
View File
@@ -183,11 +183,8 @@ tests_expected_to_fail = [
),
(
xfail_issue_33595,
"OnnxBackendNodeModelTest.test_unique_not_sorted_without_axis_cpu",
"OnnxBackendNodeModelTest.test_unique_sorted_with_negative_axis_cpu",
"OnnxBackendNodeModelTest.test_unique_sorted_with_axis_cpu",
"OnnxBackendNodeModelTest.test_unique_sorted_with_axis_3d_cpu",
"OnnxBackendNodeModelTest.test_unique_sorted_without_axis_cpu",
),
(
xfail_issue_33651,
src/frontends/onnx/frontend/src/default_opset.hpp
+2 -2
View File
@@ -2,10 +2,10 @@
// SPDX-License-Identifier: Apache-2.0
//
#include "ngraph/opsets/opset8.hpp"
#include "ngraph/opsets/opset10.hpp"
namespace ngraph {
namespace onnx_import {
namespace default_opset = ngraph::opset8;
namespace default_opset = ngraph::opset10;
}
} // namespace ngraph
src/frontends/onnx/frontend/src/op/unique.cpp
+27
View File
@@ -0,0 +1,27 @@
// Copyright (C) 2018-2022 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include "op/unique.hpp"
#include "default_opset.hpp"
namespace ngraph {
namespace onnx_import {
namespace op {
namespace set_1 {
OutputVector unique(const Node& node) {
const auto data = node.get_ng_inputs().at(0);
const bool sorted = node.get_attribute_value<int64_t>("sorted", 1);
if (node.has_attribute("axis")) {
const auto axis = node.get_attribute_as_constant<int64_t>("axis");
return std::make_shared<default_opset::Unique>(data, axis, sorted)->outputs();
} else {
return std::make_shared<default_opset::Unique>(data, sorted)->outputs();
}
}
} // namespace set_1
} // namespace op
} // namespace onnx_import
} // namespace ngraph
src/frontends/onnx/frontend/src/op/unique.hpp
+21
View File
@@ -0,0 +1,21 @@
// Copyright (C) 2018-2022 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#pragma once
#include "ngraph/node.hpp"
#include "onnx_import/core/node.hpp"
namespace ngraph {
namespace onnx_import {
namespace op {
namespace set_1 {
OutputVector unique(const Node& node);
} // namespace set_1
} // namespace op
} // namespace onnx_import
} // namespace ngraph
src/frontends/onnx/frontend/src/ops_bridge.cpp
+2
View File
@@ -169,6 +169,7 @@
#include "op/topk.hpp"
#include "op/transpose.hpp"
#include "op/trilu.hpp"
#include "op/unique.hpp"
#include "op/unsqueeze.hpp"
#include "op/upsample.hpp"
#include "op/where.hpp"
@@ -468,6 +469,7 @@ OperatorsBridge::OperatorsBridge() {
REGISTER_OPERATOR("TopK", 11, topk);
REGISTER_OPERATOR("Transpose", 1, transpose);
REGISTER_OPERATOR("Trilu", 1, trilu);
REGISTER_OPERATOR("Unique", 1, unique);
REGISTER_OPERATOR("Unsqueeze", 1, unsqueeze);
REGISTER_OPERATOR("Unsqueeze", 13, unsqueeze);
REGISTER_OPERATOR("Where", 1, where);
src/frontends/onnx/tests/models/unique_1d_no_duplicates.prototxt
+73
View File
@@ -0,0 +1,73 @@
ir_version: 7
graph {
node {
input: "data"
output: "unique"
output: "unique_idx"
output: "unique_rev_idx"
output: "unique_counts"
op_type: "Unique"
attribute {
name: "sorted"
i: 0
type: INT
}
}
input {
name: "data"
type {
tensor_type {
elem_type: 6
shape {
dim {
dim_value: 5
}
}
}
}
}
output {
name: "unique"
type {
tensor_type {
elem_type: 6
shape {
}
}
}
}
output {
name: "unique_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_rev_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_counts"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
}
opset_import {
domain: ""
version: 13
}
src/frontends/onnx/tests/models/unique_1d_no_duplicates_sorted.prototxt
+73
View File
@@ -0,0 +1,73 @@
ir_version: 7
graph {
node {
input: "data"
output: "unique"
output: "unique_idx"
output: "unique_rev_idx"
output: "unique_counts"
op_type: "Unique"
attribute {
name: "sorted"
i: 1
type: INT
}
}
input {
name: "data"
type {
tensor_type {
elem_type: 6
shape {
dim {
dim_value: 5
}
}
}
}
}
output {
name: "unique"
type {
tensor_type {
elem_type: 6
shape {
}
}
}
}
output {
name: "unique_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_rev_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_counts"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
}
opset_import {
domain: ""
version: 13
}
src/frontends/onnx/tests/models/unique_3d_default_attributes.prototxt
+74
View File
@@ -0,0 +1,74 @@
ir_version: 7
graph {
node {
input: "data"
output: "unique"
output: "unique_idx"
output: "unique_rev_idx"
output: "unique_counts"
op_type: "Unique"
}
input {
name: "data"
type {
tensor_type {
elem_type: 6
shape {
dim {
dim_value: 2
}
dim {
dim_value: 2
}
dim {
dim_value: 2
}
}
}
}
}
output {
name: "unique"
type {
tensor_type {
elem_type: 6
shape {
}
}
}
}
output {
name: "unique_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_rev_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_counts"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
}
opset_import {
domain: ""
version: 13
}
src/frontends/onnx/tests/models/unique_3d_with_duplicates_and_axis.prototxt
+84
View File
@@ -0,0 +1,84 @@
ir_version: 7
graph {
node {
input: "data"
output: "unique"
output: "unique_idx"
output: "unique_rev_idx"
output: "unique_counts"
op_type: "Unique"
attribute {
name: "sorted"
i: 1
type: INT
}
attribute {
name: "axis"
i: 0
type: INT
}
}
input {
name: "data"
type {
tensor_type {
elem_type: 6
shape {
dim {
dim_value: 2
}
dim {
dim_value: 2
}
dim {
dim_value: 3
}
}
}
}
}
output {
name: "unique"
type {
tensor_type {
elem_type: 6
shape {
}
}
}
}
output {
name: "unique_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_rev_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_counts"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
}
opset_import {
domain: ""
version: 13
}
src/frontends/onnx/tests/models/unique_3d_with_duplicates_and_axis_2.prototxt
+84
View File
@@ -0,0 +1,84 @@
ir_version: 7
graph {
node {
input: "data"
output: "unique"
output: "unique_idx"
output: "unique_rev_idx"
output: "unique_counts"
op_type: "Unique"
attribute {
name: "sorted"
i: 0
type: INT
}
attribute {
name: "axis"
i: 2
type: INT
}
}
input {
name: "data"
type {
tensor_type {
elem_type: 6
shape {
dim {
dim_value: 2
}
dim {
dim_value: 2
}
dim {
dim_value: 3
}
}
}
}
}
output {
name: "unique"
type {
tensor_type {
elem_type: 6
shape {
}
}
}
}
output {
name: "unique_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_rev_idx"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
output {
name: "unique_counts"
type {
tensor_type {
elem_type: 7
shape {
}
}
}
}
}
opset_import {
domain: ""
version: 13
}
src/frontends/onnx/tests/onnx_import.in.cpp
+82
View File
@@ -6267,3 +6267,85 @@ NGRAPH_TEST(${BACKEND_NAME}, DISABLED_castlike_bfloat16_to_float32) {
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_unique_3d_default_attributes) {
auto function = onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/unique_3d_default_attributes.onnx"));
auto test_case = test::TestCase(function, s_device);
test_case.add_input<int32_t>({9, 12, 3, 121, 5, 4, 10, 9});
test_case.add_expected_output<int32_t>(Shape{7}, {3, 4, 5, 9, 10, 12, 121});
test_case.add_expected_output<int64_t>(Shape{7}, {2, 5, 4, 0, 6, 1, 3});
test_case.add_expected_output<int64_t>(Shape{8}, {3, 5, 0, 6, 2, 1, 4, 3});
test_case.add_expected_output<int64_t>(Shape{7}, {1, 1, 1, 2, 1, 1, 1});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_unique_1d_no_duplicates) {
auto function = onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/unique_1d_no_duplicates.onnx"));
auto test_case = test::TestCase(function, s_device);
test_case.add_input<int32_t>({5, 4, 3, 2, 1});
test_case.add_expected_output<int32_t>(Shape{5}, {5, 4, 3, 2, 1});
test_case.add_expected_output<int64_t>(Shape{5}, {0, 1, 2, 3, 4});
test_case.add_expected_output<int64_t>(Shape{5}, {0, 1, 2, 3, 4});
test_case.add_expected_output<int64_t>(Shape{5}, {1, 1, 1, 1, 1});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_unique_1d_no_duplicates_sorted) {
auto function = onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/unique_1d_no_duplicates_sorted.onnx"));
auto test_case = test::TestCase(function, s_device);
test_case.add_input<int32_t>({5, 4, 3, 2, 1});
test_case.add_expected_output<int32_t>(Shape{5}, {1, 2, 3, 4, 5});
test_case.add_expected_output<int64_t>(Shape{5}, {4, 3, 2, 1, 0});
test_case.add_expected_output<int64_t>(Shape{5}, {4, 3, 2, 1, 0});
test_case.add_expected_output<int64_t>(Shape{5}, {1, 1, 1, 1, 1});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_unique_3d_with_duplicates_and_axis) {
auto function =
onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/unique_3d_with_duplicates_and_axis.onnx"));
auto test_case = test::TestCase(function, s_device);
test_case.add_input<int32_t>({1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6});
test_case.add_expected_output<int32_t>(Shape{1, 2, 3}, {1, 2, 3, 4, 5, 6});
test_case.add_expected_output<int64_t>(Shape{1}, {0});
test_case.add_expected_output<int64_t>(Shape{2}, {0, 0});
test_case.add_expected_output<int64_t>(Shape{1}, {2});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_unique_3d_with_duplicates_and_axis_2) {
auto function =
onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/unique_3d_with_duplicates_and_axis_2.onnx"));
auto test_case = test::TestCase(function, s_device);
test_case.add_input<int32_t>({-1, 2, -1, 5, -3, 5, 7, -8, 7, 4, 4, 4});
test_case.add_expected_output<int32_t>(Shape{2, 2, 2}, {-1, 2, 5, -3, 7, -8, 4, 4});
test_case.add_expected_output<int64_t>(Shape{2}, {0, 1});
test_case.add_expected_output<int64_t>(Shape{3}, {0, 1, 0});
test_case.add_expected_output<int64_t>(Shape{2}, {2, 1});
test_case.run();
}