//***************************************************************************** // 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/test_control.hpp" #include "util/test_tools.hpp" using namespace std; using namespace ngraph; static string s_manifest = "${MANIFEST}"; NGRAPH_TEST(${BACKEND_NAME}, add) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Add>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape); copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector()); copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector()); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f(read_vector<float>(result), (test::NDArray<float, 2>({{6, 8}, {10, 12}})).get_vector())); } NGRAPH_TEST(${BACKEND_NAME}, add_overload) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(A + B, ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape); copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector()); copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector()); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f(read_vector<float>(result), (test::NDArray<float, 2>({{6, 8}, {10, 12}})).get_vector())); } NGRAPH_TEST(${BACKEND_NAME}, multiply) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Multiply>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape); copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector()); copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector()); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f(read_vector<float>(result), (test::NDArray<float, 2>({{5, 12}, {21, 32}})).get_vector())); } NGRAPH_TEST(${BACKEND_NAME}, multiply_overload) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(A * B, ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape); copy_data(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector()); copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector()); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f(read_vector<float>(result), (test::NDArray<float, 2>({{5, 12}, {21, 32}})).get_vector())); } NGRAPH_TEST(${BACKEND_NAME}, divide) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2, 4, 8, 16}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f((vector<float>{2, 2, 2, 2}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, divide_int32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto B = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{0x40000140, 0x40000001, 8, 16}); auto b = backend->create_tensor(element::i32, shape); copy_data(b, vector<int32_t>{2, 5, 4, 8}); auto result = backend->create_tensor(element::i32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<int32_t>{536871072, 214748365, 2, 2}), read_vector<int32_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, divide_overload) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(A / B, ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2, 4, 8, 16}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f((vector<float>{2, 2, 2, 2}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, divide_adjoint_stability) { auto backend = runtime::Backend::create("${BACKEND_NAME}"); Shape shape{2, 2}; auto make_external = [&]() { auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto Y_out = f->get_output_op(0); auto Xs = f->get_parameters(); auto C = std::make_shared<op::Parameter>(Y_out->get_element_type(), Y_out->get_shape()); ngraph::autodiff::Adjoints adjoints(NodeVector{Y_out}, NodeVector{C}); std::vector<std::shared_ptr<Node>> dYdXs(Xs.size()); transform( Xs.begin(), Xs.end(), dYdXs.begin(), [C, &adjoints](const std::shared_ptr<Node>& X) { return adjoints.backprop_node(X); }); std::vector<std::shared_ptr<op::Parameter>> params(Xs); params.push_back(C); auto bf = std::make_shared<Function>(dYdXs, params); return bf; }; auto bf = make_external(); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{0, 0, 1, 1}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{2, 2, 2, 2}); auto c = backend->create_tensor(element::f32, shape); copy_data(c, vector<float>{1, 1, 1, 1}); auto resulta = backend->create_tensor(element::f32, shape); auto resultb = backend->create_tensor(element::f32, shape); auto handle = backend->compile(bf); handle->call_with_validate({resulta, resultb}, {a, b, c}); EXPECT_TRUE( test::all_close_f((vector<float>{0.5, 0.5, 0.5, 0.5}), read_vector<float>(resulta))); EXPECT_TRUE( test::all_close_f((vector<float>{-0.0, -0.0, -0.25, -0.25}), read_vector<float>(resultb))); } NGRAPH_TEST(${BACKEND_NAME}, divide_by_zero_float32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2, 4, 8, 16}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{0, 0, 0, 0}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<float>{std::numeric_limits<float>::infinity(), std::numeric_limits<float>::infinity(), std::numeric_limits<float>::infinity(), std::numeric_limits<float>::infinity()}), read_vector<float>(result)); } NGRAPH_TEST(${BACKEND_NAME}, maximum) { Shape shape{2, 2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Maximum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 8, -8, 17, -0.5, 0.5, 2, 1}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8, 0, 0, 1, 1.5}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 8, 4, 17, 0, 0.5, 2, 1.5}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, minimum) { Shape shape{2, 2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Minimum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 8, -8, 17, -0.5, 0.5, 2, 1}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8, 0, 0, 1, 1.5}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE( test::all_close_f((vector<float>{1, 2, -8, 8, -.5, 0, 1, 1}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, minimum_int32) { Shape shape{2, 2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto B = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Minimum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{1, 8, -8, 17, -5, 67635216, 2, 1}); auto b = backend->create_tensor(element::i32, shape); copy_data(b, vector<int32_t>{1, 2, 4, 8, 0, 18448, 1, 6}); auto result = backend->create_tensor(element::i32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<int32_t>{1, 2, -8, 8, -5, 18448, 1, 1}), read_vector<int32_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, minimum_int64) { Shape shape{2, 2, 2}; auto A = make_shared<op::Parameter>(element::i64, shape); auto B = make_shared<op::Parameter>(element::i64, shape); auto f = make_shared<Function>(make_shared<op::Minimum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i64, shape); copy_data(a, vector<int64_t>{1, 8, -8, 17, -5, 67635216, 2, 17179887632}); auto b = backend->create_tensor(element::i64, shape); copy_data(b, vector<int64_t>{1, 2, 4, 8, 0, 18448, 1, 280592}); auto result = backend->create_tensor(element::i64, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<int64_t>{1, 2, -8, 8, -5, 18448, 1, 280592}), read_vector<int64_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, maximum_int32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto B = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Maximum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{0x40000140, 0x40000001, -8, 17}); auto b = backend->create_tensor(element::i32, shape); copy_data(b, vector<int32_t>{0x40000170, 0x40000000, 4, 8}); auto result = backend->create_tensor(element::i32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<int32_t>{0x40000170, 0x40000001, 4, 17}), read_vector<int32_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, maximum_int64) { Shape shape{2, 2, 2}; auto A = make_shared<op::Parameter>(element::i64, shape); auto B = make_shared<op::Parameter>(element::i64, shape); auto f = make_shared<Function>(make_shared<op::Maximum>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i64, shape); copy_data(a, vector<int64_t>{1, 8, -8, 17, -5, 67635216, 2, 17179887632}); auto b = backend->create_tensor(element::i64, shape); copy_data(b, vector<int64_t>{1, 2, 4, 8, 0, 18448, 1, 280592}); auto result = backend->create_tensor(element::i64, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_EQ((vector<int64_t>{1, 8, 4, 17, 0, 67635216, 2, 17179887632}), read_vector<int64_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, power) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Power>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 2, 3, 5}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{2, 0, 6, 3}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f(vector<float>{1, 1, 729, 125}, read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, subtract) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Subtract>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2, 4, 8, 16}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 4, 8}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, subtract_overload) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(A - B, ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2, 4, 8, 16}); auto b = backend->create_tensor(element::f32, shape); copy_data(b, vector<float>{1, 2, 4, 8}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 4, 8}), read_vector<float>(result))); }