//***************************************************************************** // Copyright 2017-2019 Intel Corporation // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. //***************************************************************************** #include <algorithm> #include <cinttypes> #include <cmath> #include <cstdlib> #include <random> #include <string> #include "gtest/gtest.h" #include "ngraph/ngraph.hpp" #include "util/all_close.hpp" #include "util/all_close_f.hpp" #include "util/ndarray.hpp" #include "util/random.hpp" #include "util/test_case.hpp" #include "util/test_control.hpp" #include "util/test_tools.hpp" using namespace std; using namespace ngraph; static string s_manifest = "${MANIFEST}"; NGRAPH_TEST(${BACKEND_NAME}, gather_4d_indices_no_axis_uint8) { Shape params_shape{3, 2}; Shape indices_shape{2, 2, 3, 4}; Shape out_shape{2, 2, 3, 4, 2}; auto P = make_shared<op::Parameter>(element::u8, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::u8, params_shape); copy_data(p, vector<uint8_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}); auto result = backend->create_tensor(element::u8, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close( (vector<uint8_t>{10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31}), read_vector<uint8_t>(result))); } NGRAPH_TEST(${BACKEND_NAME}, gather_4d_indices_no_axis_2d_input) { Shape params_shape{3, 2}; Shape indices_shape{2, 2, 3, 4}; Shape out_shape{2, 2, 3, 4, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_3d_indices_no_axis_2d_input) { Shape params_shape{3, 2}; Shape indices_shape{2, 3, 4}; Shape out_shape{2, 3, 4, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data( i, vector<int32_t>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f, 1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_2d_indices_no_axis_2d_input) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_1d_indices_no_axis_1d_input) { Shape params_shape{3}; Shape indices_shape{2}; Shape out_shape{2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 2.0f, 3.0f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{2.0f, 1.0f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_scalar_indices_no_axis_2d_input) { Shape params_shape{3, 2}; Shape indices_shape{}; Shape out_shape{2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{2.0f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_2d_indices_axis_1_2d_input) { Shape params_shape{3, 3}; Shape indices_shape{1, 2}; Shape out_shape{3, 1, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I, 1); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.0f, 1.2f, 2.0f, 2.2f, 3.0f, 3.2f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_1d_indices_axis_2_4d_input) { Shape params_shape{2, 2, 3, 3}; Shape indices_shape{2}; Shape out_shape{2, 2, 2, 3}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I, 2); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 1.1f, 1.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 3.0f, 3.1f, 3.2f, 1.0f, 1.1f, 1.2f, 3.0f, 3.1f, 3.2f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_scalar_indices_axis_1_2d_input) { Shape params_shape{3, 3}; Shape indices_shape{}; Shape out_shape{3}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I, 1); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 2.0f, 3.0f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_single_indices) { Shape params_shape{3, 3}; Shape indices_shape{2}; Shape out_shape{}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 1.4f, 1.5f, 1.6f, 1.7f, 1.8f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 2}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.5f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_2d) { Shape params_shape{2, 2}; Shape indices_shape{2, 2}; Shape out_shape{2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 0, 1, 1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 1.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_2d) { Shape params_shape{2, 2}; Shape indices_shape{2, 1}; Shape out_shape{2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_scalar_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{2, 3}; Shape out_shape{2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.1f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_1d_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_2d_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{1, 1}; Shape out_shape{1, 2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_2d) { Shape params_shape{2, 2}; Shape indices_shape{2, 1, 2}; Shape out_shape{2, 1}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 0, 0, 1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_2d) { Shape params_shape{2, 2}; Shape indices_shape{2, 1, 1}; Shape out_shape{2, 1, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 1.0f, 1.1f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_scalar_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{2, 2, 3}; Shape out_shape{2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.1f, 2.1f, 1.3f, 2.2f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_1d_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{2, 2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{1.2f, 1.3f, 2.0f, 2.1f, 1.0f, 1.1f, 2.2f, 2.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_nd_batch_2d_from_3d) { Shape params_shape{2, 2, 2}; Shape indices_shape{2, 1, 1}; Shape out_shape{2, 1, 2, 2}; auto P = make_shared<op::Parameter>(element::f32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::GatherND>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::f32, params_shape); copy_data(p, vector<float>{1.0f, 1.1f, 1.2f, 1.3f, 2.0f, 2.1f, 2.2f, 2.3f}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 0}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close_f((vector<float>{2.0f, 2.1f, 2.2f, 2.3f, 1.0f, 1.1f, 1.2f, 1.3f}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_int8) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::i8, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::i8, params_shape); copy_data(p, vector<int8_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::i8, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<int8_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<int8_t>(result), static_cast<int8_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_int16) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::i16, params_shape); auto I = make_shared<op::Parameter>(element::i64, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::i16, params_shape); copy_data(p, vector<int16_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i64, indices_shape); copy_data(i, vector<int64_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::i16, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<int16_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<int16_t>(result), static_cast<int16_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_int32) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::i32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::i32, params_shape); copy_data(p, vector<int32_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::i32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<int32_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<int32_t>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_int64) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::i64, params_shape); auto I = make_shared<op::Parameter>(element::i64, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::i64, params_shape); copy_data(p, vector<int64_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i64, indices_shape); copy_data(i, vector<int64_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::i64, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<int64_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<int64_t>(result), static_cast<int64_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_uint8) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::u8, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::u8, params_shape); copy_data(p, vector<uint8_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::u8, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<uint8_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<uint8_t>(result), static_cast<uint8_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_uint16) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::u16, params_shape); auto I = make_shared<op::Parameter>(element::i64, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::u16, params_shape); copy_data(p, vector<uint16_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i64, indices_shape); copy_data(i, vector<int64_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::u16, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<uint16_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<uint16_t>(result), static_cast<uint16_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_uint32) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::u32, params_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::u32, params_shape); copy_data(p, vector<uint32_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::u32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<uint32_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<uint32_t>(result), static_cast<uint32_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_uint64) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::u64, params_shape); auto I = make_shared<op::Parameter>(element::i64, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::u64, params_shape); copy_data(p, vector<uint64_t>{10, 11, 20, 21, 30, 31}); auto i = backend->create_tensor(element::i64, indices_shape); copy_data(i, vector<int64_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::u64, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<uint64_t>{10, 11, 20, 21, 20, 21, 30, 31}), read_vector<uint64_t>(result), static_cast<uint64_t> MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, gather_no_axis_bool) { Shape params_shape{3, 2}; Shape indices_shape{2, 2}; Shape out_shape{2, 2, 2}; auto P = make_shared<op::Parameter>(element::boolean, params_shape); auto I = make_shared<op::Parameter>(element::i64, indices_shape); auto G = make_shared<op::Gather>(P, I); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{P, I}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto p = backend->create_tensor(element::boolean, params_shape); copy_data(p, vector<char>{1, 1, 1, 0, 0, 1}); auto i = backend->create_tensor(element::i64, indices_shape); copy_data(i, vector<int64_t>{0, 1, 1, 2}); auto result = backend->create_tensor(element::boolean, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {p, i}); EXPECT_TRUE(test::all_close((vector<char>{1, 1, 1, 0, 1, 0, 0, 1}), read_vector<char>(result), static_cast<char> MIN_FLOAT_TOLERANCE_BITS)); }