//***************************************************************************** // 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 "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 = "${MANIFEST}"; // Trivial case with no reduced axes. NGRAPH_TEST(${BACKEND_NAME}, product_trivial) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 2, 3, 4}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 3, 4}), read_vector<float>(result))); } // Failure has been reported at 5D for some reason NGRAPH_TEST(${BACKEND_NAME}, product_trivial_5d) { Shape shape{2, 2, 2, 2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}); auto result = backend->create_tensor(element::f32, shape); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_to_scalar) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::f32, shape); auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape); copy_data(a, vector<float>{1, 2, 3, 4}); auto result = backend->create_tensor(element::f32, Shape{}); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{24}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 3, 4}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_matrix_columns) { Shape shape_a{3, 2}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{2}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{15, 48}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 3, 4, 5, 6}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_matrix_rows) { Shape shape_a{3, 2}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{2, 12, 30}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{1, 2, 3, 4, 5, 6}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_matrix_rows_zero) { Shape shape_a{3, 0}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{}); auto result = backend->create_tensor(element::f32, shape_rt); copy_data(result, vector<float>({3, 3, 3})); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 1, 1}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_matrix_cols_zero) { // Now the reduction (g(x:float32[2,2],y:float32[]) = reduce(x,y,f,axes={})). Shape shape_a{0, 2}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{2}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{}); auto result = backend->create_tensor(element::f32, shape_rt); copy_data(result, vector<float>({3, 3})); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 1}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_vector_zero) { Shape shape_a{0}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{}); auto result = backend->create_tensor(element::f32, shape_rt); copy_data(result, vector<float>({3})); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_matrix_to_scalar_zero_by_zero) { Shape shape_a{0, 0}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{}); auto result = backend->create_tensor(element::f32, shape_rt); copy_data(result, vector<float>({3})); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1}), read_vector<float>(result))); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_TRUE(test::all_close_f((vector<float>{}), read_vector<float>(a))); } NGRAPH_TEST(${BACKEND_NAME}, product_3d_to_matrix_most_sig) { Shape shape_a{3, 3, 3}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3, 3}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1 * 10 * 19, 2 * 11 * 20, 3 * 12 * 21, 4 * 13 * 22, 5 * 14 * 23, 6 * 15 * 24, 7 * 16 * 25, 8 * 17 * 26, 9 * 18 * 27}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_3d_to_matrix_least_sig) { Shape shape_a{3, 3, 3}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3, 3}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{2}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1 * 2 * 3, 4 * 5 * 6, 7 * 8 * 9, 10 * 11 * 12, 13 * 14 * 15, 16 * 17 * 18, 19 * 20 * 21, 22 * 23 * 24, 25 * 26 * 27}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_3d_to_vector) { Shape shape_a{3, 3, 3}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f( (vector<float>{1.0f * 10.0f * 19.0f * 4.0f * 13.0f * 22.0f * 7.0f * 16.0f * 25.0f, 2.0f * 11.0f * 20.0f * 5.0f * 14.0f * 23.0f * 8.0f * 17.0f * 26.0f, 3.0f * 12.0f * 21.0f * 6.0f * 15.0f * 24.0f * 9.0f * 18.0f * 27.0f}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_3d_to_scalar) { Shape shape_a{3, 3, 3}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1, 2}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1}); auto result = backend->create_tensor(element::f32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f(vector<float>{1.0f * 10.0f * 9.0f * 4.0f * 13.0f * 6.0f * 7.0f * 12.0f * 3.0f * 2.0f * 11.0f * 8.0f * 5.0f * 14.0f * 5.0f * 8.0f * 11.0f * 2.0f * 3.0f * 12.0f * 7.0f * 6.0f * 13.0f * 4.0f * 9.0f * 10.0f * 1.0f}, read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_3d_eliminate_zero_dim) { Shape shape_a{3, 0, 2}; auto A = make_shared<op::Parameter>(element::f32, shape_a); Shape shape_rt{3, 2}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::f32, shape_a); copy_data(a, vector<float>{}); auto result = backend->create_tensor(element::f32, shape_rt); // Overwrite the initial result vector to make sure we're not just coincidentally getting the right value. copy_data(result, vector<float>{2112, 2112, 2112, 2112, 2112, 2112}); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_TRUE(test::all_close_f((vector<float>{1, 1, 1, 1, 1, 1}), read_vector<float>(result))); } NGRAPH_TEST(${BACKEND_NAME}, product_2d_to_scalar_int32) { Shape shape_a{3, 3}; auto A = make_shared<op::Parameter>(element::i32, shape_a); Shape shape_rt{}; auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape_a); copy_data(a, vector<int32_t>{1, 2, 3, 4, 5, 6, 7, 8, 9}); auto result = backend->create_tensor(element::i32, shape_rt); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_EQ(vector<int32_t>{1 * 2 * 3 * 4 * 5 * 6 * 7 * 8 * 9}, read_vector<int32_t>(result)); } NGRAPH_TEST(${BACKEND_NAME}, product_to_scalar_int32) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i32, shape); auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // Create some tensors for input/output auto a = backend->create_tensor(element::i32, shape); copy_data(a, vector<int32_t>{1, 2, 3, 4}); auto result = backend->create_tensor(element::i32, Shape{}); auto handle = backend->compile(f); handle->call_with_validate({result}, {a}); EXPECT_EQ((vector<int32_t>{24}), read_vector<int32_t>(result)); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_EQ((vector<int32_t>{1, 2, 3, 4}), read_vector<int32_t>(a)); } NGRAPH_TEST(${BACKEND_NAME}, product_to_scalar_int8) { Shape shape{2, 2}; auto A = make_shared<op::Parameter>(element::i8, shape); auto f = make_shared<Function>(make_shared<op::Product>(A, AxisSet{0, 1}), ParameterVector{A}); auto backend = runtime::Backend::create("${BACKEND_NAME}"); // 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>{24}), read_vector<int8_t>(result)); // For some reason I'm feeling extra paranoid about making sure reduction doesn't clobber the // input tensors, so let's do this too. EXPECT_EQ((vector<int8_t>{1, 2, 3, 4}), read_vector<int8_t>(a)); }