//***************************************************************************** // 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. //***************************************************************************** // 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 ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS #endif // clang-format on #include "gtest/gtest.h" #include "ngraph/ngraph.hpp" #include "util/all_close.hpp" #include "util/all_close_f.hpp" #include "util/known_element_types.hpp" #include "util/ndarray.hpp" #include "util/test_control.hpp" #include "util/test_tools.hpp" using namespace std; using namespace ngraph; static string s_manifest = "${MANIFEST}"; NGRAPH_TEST(${BACKEND_NAME}, sigmoid_n1c1h2w2) { auto input = make_shared<op::Parameter>(element::f32, Shape{1, 1, 2, 2}); auto sigmoid_node = make_shared<op::Sigmoid>(input); auto func = make_shared<Function>(sigmoid_node, ParameterVector{input}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, input->get_shape()); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, input->get_shape()); float x1 = 1.0f; float x2 = 4.0f; float sigma1 = 1.0f / (1.0f + std::exp(-x1)); float sigma2 = 1.0f / (1.0f + std::exp(-x2)); vector<float> dataA{x1, x2, x1, x2}; copy_data(a, dataA); auto handle = backend->compile(func); handle->call_with_validate({result}, {a}); vector<float> expected{sigma1, sigma2, sigma1, sigma2}; EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected)); } NGRAPH_TEST(${BACKEND_NAME}, sigmoid_n1c1h4) { auto input = make_shared<op::Parameter>(element::f32, Shape{1, 1, 4}); auto sigmoid_node = make_shared<op::Sigmoid>(input); auto func = make_shared<Function>(sigmoid_node, ParameterVector{input}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, input->get_shape()); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, input->get_shape()); float x1 = 1.0f; float x2 = 4.0f; float sigma1 = 1.0f / (1.0f + std::exp(-x1)); float sigma2 = 1.0f / (1.0f + std::exp(-x2)); vector<float> dataA{x1, x2, x1, x2}; copy_data(a, dataA); auto handle = backend->compile(func); handle->call_with_validate({result}, {a}); vector<float> expected{sigma1, sigma2, sigma1, sigma2}; EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected)); } NGRAPH_TEST(${BACKEND_NAME}, sigmoid_bprop_n1c1h4) { auto input = make_shared<op::Parameter>(element::f32, Shape{1, 1, 4}); auto delta = make_shared<op::Parameter>(element::f32, Shape{1, 1, 4}); auto sigmoid_node = make_shared<op::SigmoidBackprop>(input, delta); auto func = make_shared<Function>(sigmoid_node, ParameterVector{input, delta}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, input->get_shape()); shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, delta->get_shape()); shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, input->get_shape()); float x1 = 1.0f; float x2 = 4.0f; float dt = 1.0f; float sigma1 = 1.0f / (1.0f + std::exp(-x1)); float sigma2 = 1.0f / (1.0f + std::exp(-x2)); float bprop1 = sigma1 * (1 - sigma1) * dt; float bprop2 = sigma2 * (1 - sigma2) * dt; vector<float> dataA{x1, x2, x1, x2}; vector<float> dataB{dt, dt, dt, dt}; copy_data(a, dataA); copy_data(b, dataB); auto handle = backend->compile(func); handle->call_with_validate({result}, {a, b}); vector<float> expected{bprop1, bprop2, bprop1, bprop2}; EXPECT_TRUE(test::all_close_f(expected, read_vector<float>(result))); }