//***************************************************************************** // 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 <memory> #include "gtest/gtest.h" #include "ngraph/log.hpp" #include "ngraph/ngraph.hpp" #include "ngraph/op/get_output_element.hpp" #include "ngraph/pass/manager.hpp" #include "ngraph/pass/visualize_tree.hpp" #include "ngraph/runtime/backend.hpp" #include "ngraph/runtime/backend_manager.hpp" #include "ngraph/runtime/hybrid/hybrid_backend.hpp" #include "ngraph/runtime/hybrid/hybrid_util.hpp" #include "ngraph/runtime/hybrid/op/function_call.hpp" #include "ngraph/runtime/interpreter/int_backend.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 runtime::BackendConstructor* hybrid_creator() { class HybridBackendConstructor : public runtime::BackendConstructor { public: std::shared_ptr<runtime::Backend> create(const std::string& config) override { vector<string> unsupported_0 = {"Add", "Max"}; vector<string> unsupported_1 = {"Multiply"}; vector<shared_ptr<runtime::Backend>> backend_list = { make_shared<runtime::interpreter::INTBackend>(unsupported_0), runtime::Backend::create("CPU")}; return make_shared<runtime::hybrid::HybridBackend>(backend_list); } }; static unique_ptr<runtime::BackendConstructor> s_backend_constructor( new HybridBackendConstructor()); return s_backend_constructor.get(); } TEST(HYBRID, function_call) { vector<shared_ptr<runtime::Backend>> backend_list = { make_shared<runtime::interpreter::INTBackend>()}; auto backend = make_shared<runtime::hybrid::HybridBackend>(backend_list); Shape shape{}; shared_ptr<Function> inner_function; auto inner_A = make_shared<op::Parameter>(element::f32, shape); auto inner_B = make_shared<op::Parameter>(element::f32, shape); auto inner_C = make_shared<op::Parameter>(element::f32, shape); auto inner_R1 = (inner_A + inner_B) * inner_C; auto inner_R2 = (inner_A + inner_C) * inner_C; NodeVector inner_Result{inner_R1, inner_R2}; inner_function = make_shared<Function>(inner_Result, ParameterVector{inner_A, inner_B, inner_C}); auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto C = make_shared<op::Parameter>(element::f32, shape); NodeVector fcall_args{A, B, C}; auto H = make_shared<runtime::hybrid::op::FunctionCall>( inner_Result, fcall_args, *inner_function, backend_list[0]); auto G0 = make_shared<ngraph::op::GetOutputElement>(H, 0); auto G1 = make_shared<ngraph::op::GetOutputElement>(H, 1); NodeVector out{G0, G1}; auto J = G0 + G1; auto f = make_shared<Function>(out, ParameterVector{A, B, C}); 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> c = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> r0 = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> r1 = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{2}); copy_data(b, vector<float>{3}); copy_data(c, vector<float>{4}); auto exec = backend->compile(f); exec->call({r0, r1}, {a, b, c}); ngraph::pass::Manager pass_manager; pass_manager.register_pass<ngraph::pass::VisualizeTree>("test.png"); pass_manager.run_passes(f); } TEST(HYBRID, abc) { const string backend_name = "H1"; runtime::BackendManager::register_backend(backend_name, hybrid_creator()); Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto B = make_shared<op::Parameter>(element::f32, shape); auto C = make_shared<op::Parameter>(element::f32, shape); auto D = make_shared<op::Parameter>(element::f32, shape); auto t1 = A * B; auto t2 = t1 * D; auto t3 = (t2 + C); auto t4 = (t3 + A) * t1; NodeVector result({t3, t4}); auto f = make_shared<Function>(result, ParameterVector{A, B, C, D}); shared_ptr<runtime::Backend> backend = runtime::Backend::create("H1"); static_pointer_cast<runtime::hybrid::HybridBackend>(backend)->set_debug_enabled(true); // 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> c = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> d = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result1 = backend->create_tensor(element::f32, shape); shared_ptr<runtime::Tensor> result2 = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 2, 3, 4}); copy_data(b, vector<float>{5, 6, 7, 8}); copy_data(c, vector<float>{9, 10, 11, 12}); copy_data(d, vector<float>{4, 3, 2, 1}); auto handle = backend->compile(f); handle->call_with_validate({result1, result2}, {a, b, c, d}); EXPECT_TRUE( test::all_close_f(read_vector<float>(result2), (vector<float>{150, 576, 1176, 1536}))); } TEST(HYBRID, simple) { const string backend_name = "H1"; runtime::BackendManager::register_backend(backend_name, hybrid_creator()); Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i8, shape); auto f = make_shared<Function>(make_shared<op::Max>(A, AxisSet{0, 1}), ParameterVector{A}); shared_ptr<runtime::Backend> backend = runtime::Backend::create("H1"); static_pointer_cast<runtime::hybrid::HybridBackend>(backend)->set_debug_enabled(true); // Create some tensors for input/output auto a = backend->create_tensor(element::i8, shape); copy_data(a, vector<int8_t>{1, 2, 3, 4}); auto result = backend->create_tensor(element::i8, Shape{}); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_EQ((vector<int8_t>{4}), read_vector<int8_t>(result)); }