//***************************************************************************** // 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> // clang-format off #ifdef ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS #define DEFAULT_FLOAT_TOLERANCE_BITS ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS #endif #ifdef ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS #define DEFAULT_DOUBLE_TOLERANCE_BITS ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS #endif // clang-format on #include "gtest/gtest.h" #include "ngraph/ngraph.hpp" #include "util/all_close.hpp" #include "util/all_close_f.hpp" #include "util/ndarray.hpp" #include "util/test_control.hpp" #include "util/test_tools.hpp" using namespace std; using namespace ngraph; static string s_manifest = "${MANIFEST}"; NGRAPH_TEST(${BACKEND_NAME}, divide) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${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(${BACKEND_NAME}, divide_cpp_rounding_int32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto B = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B, false), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{-10, -10, 10, 10}); auto b = backend->create_tensor(element::i32, shape); copy_data(b, vector<int32_t>{-3, 3, -3, 3}); 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>{3, -3, -3, 3}), read_vector<int32_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, divide_python_rounding_int32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto B = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Divide>(A, B), ParameterVector{A, B}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{-10, -10, 10, 10}); auto b = backend->create_tensor(element::i32, shape); copy_data(b, vector<int32_t>{-3, 3, -3, 3}); 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>{3, -4, -4, 3}), 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->output(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(OutputVector{Y_out}, OutputVector{C}); std::vector<Output<Node>> dYdXs(Xs.size()); transform( Xs.begin(), Xs.end(), dYdXs.begin(), [C, &adjoints](const std::shared_ptr<Node>& X) { return adjoints.backprop_output(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)); }