+++ /dev/null
-//*****************************************************************************
-// 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 "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"
-
-NGRAPH_SUPPRESS_DEPRECATED_START
-
-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));
-}
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