//***************************************************************************** // Copyright 2017-2020 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_control.hpp" #include "util/test_tools.hpp" using namespace std; using namespace ngraph; static string s_manifest = "${MANIFEST}"; #if 0 NGRAPH_TEST(${BACKEND_NAME}, scatter_add_4d_indices) { Shape ref_shape{3, 3, 3}; Shape indices_shape{2, 3, 4, 2}; Shape updates_shape{2, 3, 4, 2, 3, 3}; Shape out_shape{3, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f( (vector<float>{0, 17, 34, 51, 68, 85, 102, 119, 136, 17, 34, 51, 68, 85, 102, 119, 136, 153, 0, 17, 34, 51, 68, 85, 102, 119, 136}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } #endif NGRAPH_TEST(${BACKEND_NAME}, scatter_add_3d_indices) { Shape ref_shape{2, 3, 3}; Shape indices_shape{2, 2, 2}; Shape updates_shape{2, 2, 2, 3, 3}; Shape out_shape{2, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 0, 0, 1, 1, 0}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f( (vector<float>{0, 5, 10, 15, 20, 25, 30, 35, 40, 5, 10, 15, 20, 25, 30, 35, 40, 45}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, scatter_add_2d_indices) { Shape ref_shape{3}; Shape indices_shape{2, 2}; Shape updates_shape{2, 2}; Shape out_shape{3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{0, 1, 2}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 1, 1, 0}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{1, 2, 3, 4}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f( (vector<float>{5, 6, 2}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, scatter_add_1d_indices) { Shape ref_shape{2, 3, 3}; Shape indices_shape{2}; Shape updates_shape{2, 3, 3}; Shape out_shape{2, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1, 0}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f( (vector<float>{0, 2, 4, 6, 8, 10, 12, 14, 16, 2, 4, 6, 8, 10, 12, 14, 16, 18}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, scatter_add_scalar_indices) { Shape ref_shape{2, 3, 3}; Shape indices_shape{}; Shape updates_shape{3, 3}; Shape out_shape{2, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{1}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f( (vector<float>{0, 1, 2, 3, 4, 5, 6, 7, 8, 2, 4, 6, 8, 10, 12, 14, 16, 18}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, scatter_nd_add_batch_2d_to_3d) { Shape ref_shape{3, 3, 3}; Shape indices_shape{2, 1}; Shape updates_shape{2, 3, 3}; Shape out_shape{3, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterNDAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0, 2}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{1, 1, 1, 2, 2, 2, 3, 3, 3, 7, 7, 7, 8, 8, 8, 9, 9, 9}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f((vector<float>{2, 2, 2, 4, 4, 4, 6, 6, 6, 4, 4, 4, 5, 5, 5, 6, 6, 6, 14, 14, 14, 16, 16, 16, 18, 18, 18}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); } NGRAPH_TEST(${BACKEND_NAME}, scatter_nd_add_2d_to_3d) { Shape ref_shape{3, 3, 3}; Shape indices_shape{1}; Shape updates_shape{3, 3}; Shape out_shape{3, 3, 3}; auto R = make_shared<op::Parameter>(element::f32, ref_shape); auto I = make_shared<op::Parameter>(element::i32, indices_shape); auto U = make_shared<op::Parameter>(element::f32, updates_shape); auto G = make_shared<op::ScatterNDAdd>(R, I, U); auto f = make_shared<Function>(make_shared<op::GetOutputElement>(G, 0), ParameterVector{R, I, U}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto r = backend->create_tensor(element::f32, ref_shape); copy_data(r, vector<float>{1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9}); auto i = backend->create_tensor(element::i32, indices_shape); copy_data(i, vector<int32_t>{0}); auto u = backend->create_tensor(element::f32, updates_shape); copy_data(u, vector<float>{1, 1, 1, 2, 2, 2, 3, 3, 3}); auto result = backend->create_tensor(element::f32, out_shape); auto c = backend->compile(f); c->call_with_validate({result}, {r, i, u}); EXPECT_TRUE(test::all_close_f((vector<float>{2, 2, 2, 4, 4, 4, 6, 6, 6, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS)); }