ngraph/test/backend/dynamic.in.cpp

   1 //*****************************************************************************
   2 // Copyright 2017-2020 Intel Corporation
   3 //
   4 // Licensed under the Apache License, Version 2.0 (the "License");
   5 // you may not use this file except in compliance with the License.
   6 // You may obtain a copy of the License at
   7 //
   8 //     http://www.apache.org/licenses/LICENSE-2.0
   9 //
  10 // Unless required by applicable law or agreed to in writing, software
  11 // distributed under the License is distributed on an "AS IS" BASIS,
  12 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13 // See the License for the specific language governing permissions and
  14 // limitations under the License.
  15 //*****************************************************************************
  16
  17 #include "gtest/gtest.h"
  18 #include "ngraph/ngraph.hpp"
  19 #include "ngraph/runtime/tensor.hpp"
  20 #include "runtime/backend.hpp"
  21 #include "util/all_close_f.hpp"
  22 #include "util/test_control.hpp"
  23 #include "util/test_tools.hpp"
  24
  25 NGRAPH_SUPPRESS_DEPRECATED_START
  26
  27 using namespace std;
  28 using namespace ngraph;
  29
  30 static string s_manifest = "${MANIFEST}";
  31
  32 NGRAPH_TEST(${BACKEND_NAME}, create_dynamic_backend)
  33 {
  34     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
  35     ASSERT_NE(backend, nullptr);
  36     ASSERT_TRUE(backend->supports_dynamic_tensors());
  37 }
  38
  39 NGRAPH_TEST(${BACKEND_NAME}, create_dynamic_tensor)
  40 {
  41     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
  42     auto t = backend->create_dynamic_tensor(element::f32, PartialShape{2, Dimension::dynamic(), 3});
  43     ASSERT_TRUE(t->get_partial_shape().same_scheme(PartialShape{2, Dimension::dynamic(), 3}));
  44 }
  45
  46 NGRAPH_TEST(${BACKEND_NAME}, dynamic_abc)
  47 {
  48     //
  49     // Create a graph for f(a,b,c) = (a+b)*c, where a, b, c all have shape {2,?,3}.
  50     //
  51     auto a = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
  52     auto b = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
  53     auto c = make_shared<op::Parameter>(element::f32, PartialShape{2, Dimension::dynamic(), 3});
  54
  55     auto a_plus_b_times_c = (a + b) * c;
  56
  57     auto f = make_shared<Function>(NodeVector{a_plus_b_times_c}, ParameterVector{a, b, c});
  58
  59     //
  60     // Get a backend with dynamic support, and compile f.
  61     //
  62     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
  63
  64     auto ex = backend->compile(f);
  65
  66     //
  67     // Create a dynamic output tensor with shape {2,?,3}.
  68     //
  69     auto t_r =
  70         backend->create_dynamic_tensor(element::f32, PartialShape{2, Dimension::dynamic(), 3});
  71
  72     //
  73     // For each of n=[0,...,5), run the compiled executable against a test vector of shape
  74     // {2,n,3}, and check the results.
  75     //
  76     for (size_t middle_dim = 0; middle_dim < 5; middle_dim++)
  77     {
  78         // Fill in some test input values, which we'll use for a, b, and c.
  79         vector<float> inputs(2 * middle_dim * 3);
  80         for (size_t i = 0; i < 2 * middle_dim * 3; i++)
  81         {
  82             inputs[i] = i;
  83         }
  84
  85         // Create static tensors for the inputs and copy data.
  86         auto t_a = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
  87         auto t_b = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
  88         auto t_c = backend->create_tensor(element::f32, Shape{2, middle_dim, 3});
  89
  90         copy_data(t_a, inputs);
  91         copy_data(t_b, inputs);
  92         copy_data(t_c, inputs);
  93
  94         // Call ex, writing result into t_r (note we're using the same t_r from outside the loop.)
  95         ex->call_with_validate({t_r}, {t_a, t_b, t_c});
  96
  97         // After call, t_r should have a shape of {2,n,3}.
  98         ASSERT_EQ(t_r->get_shape(), (Shape{2, middle_dim, 3}));
  99
 100         // Read out the results, and compare them against expected values.
 101         auto results = read_vector<float>(t_r);
 102
 103         vector<float> expected_values(2 * middle_dim * 3);
 104         for (size_t i = 0; i < 2 * middle_dim * 3; i++)
 105         {
 106             expected_values[i] = (i + i) * i;
 107         }
 108
 109         EXPECT_TRUE(test::all_close_f(results, expected_values));
 110     }
 111 }
 112
 113 static void axpy_test(const PartialShape& input_pshape, const std::vector<Shape>& input_shapes)
 114 {
 115     auto a = make_shared<op::Parameter>(element::f32, input_pshape);
 116     auto x = make_shared<op::Parameter>(element::f32, input_pshape);
 117     auto y = make_shared<op::Parameter>(element::f32, input_pshape);
 118
 119     auto axpy = a * x + y;
 120
 121     auto f = make_shared<Function>(NodeVector{axpy}, ParameterVector{a, x, y});
 122     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
 123     auto ex = backend->compile(f);
 124
 125     auto t_r = backend->create_dynamic_tensor(element::f32, input_pshape);
 126
 127     for (auto& shape : input_shapes)
 128     {
 129         vector<float> inputs(shape_size(shape));
 130         for (size_t i = 0; i < shape_size(shape); i++)
 131         {
 132             inputs[i] = i;
 133         }
 134
 135         auto t_a = backend->create_tensor(element::f32, shape);
 136         auto t_x = backend->create_tensor(element::f32, shape);
 137         auto t_y = backend->create_tensor(element::f32, shape);
 138
 139         copy_data(t_a, inputs);
 140         copy_data(t_x, inputs);
 141         copy_data(t_y, inputs);
 142
 143         ex->call_with_validate({t_r}, {t_a, t_x, t_y});
 144
 145         ASSERT_EQ(t_r->get_shape(), shape);
 146
 147         auto results = read_vector<float>(t_r);
 148
 149         vector<float> expected_values(shape_size(shape));
 150         for (size_t i = 0; i < shape_size(shape); i++)
 151         {
 152             expected_values[i] = (i * i) + i;
 153         }
 154
 155         EXPECT_TRUE(test::all_close_f(results, expected_values));
 156     }
 157 }
 158
 159 NGRAPH_TEST(${BACKEND_NAME}, dynamic_axpy)
 160 {
 161     // Test with shape {?, 3, 3}.
 162     axpy_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
 163
 164     // Test with shape {?, ?, ?}.
 165     axpy_test(PartialShape::dynamic(3),
 166               {Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
 167
 168     // Test with shape ?. (Rank unknown.)
 169     axpy_test(PartialShape::dynamic(),
 170               {Shape{2, 3, 3},
 171                Shape{5, 3, 3},
 172                Shape{2, 5, 2},
 173                Shape{8, 1, 8},
 174                Shape{5},
 175                Shape{8, 2},
 176                Shape{8, 2, 8, 2},
 177                Shape{2, 3, 4, 5, 2}});
 178 }
 179
 180 static void to_vector_test(const PartialShape& input_pshape, const std::vector<Shape>& input_shapes)
 181 {
 182     auto x = make_shared<op::Parameter>(element::f32, input_pshape);
 183
 184     shared_ptr<Node> x_new_shape = make_shared<op::v0::ShapeOf>(x);
 185     x_new_shape = make_shared<op::Product>(x_new_shape, AxisSet{0});
 186     x_new_shape = make_shared<op::Reshape>(x_new_shape, AxisVector{}, Shape{1});
 187
 188     auto x_reshaped = make_shared<op::v1::Reshape>(x, x_new_shape, true);
 189
 190     auto f = make_shared<Function>(NodeVector{x_reshaped}, ParameterVector{x});
 191     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
 192     auto ex = backend->compile(f);
 193
 194     auto t_r = backend->create_dynamic_tensor(element::f32, PartialShape::dynamic(1));
 195
 196     for (auto& shape : input_shapes)
 197     {
 198         vector<float> inputs(shape_size(shape));
 199         for (size_t i = 0; i < shape_size(shape); i++)
 200         {
 201             inputs[i] = i;
 202         }
 203
 204         auto t_x = backend->create_tensor(element::f32, shape);
 205
 206         copy_data(t_x, inputs);
 207
 208         ex->call_with_validate({t_r}, {t_x});
 209
 210         ASSERT_EQ(t_r->get_shape(), (Shape{shape_size(shape)}));
 211
 212         auto results = read_vector<float>(t_r);
 213
 214         EXPECT_TRUE(test::all_close_f(results, inputs));
 215     }
 216 }
 217
 218 NGRAPH_TEST(${BACKEND_NAME}, dynamic_to_vector)
 219 {
 220     // Test with shape {?, 3, 3}.
 221     to_vector_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
 222
 223     // Test with shape {?, ?, ?}.
 224     to_vector_test(PartialShape::dynamic(3),
 225                    {Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
 226
 227     // Test with shape ?. (Rank unknown.)
 228     to_vector_test(PartialShape::dynamic(),
 229                    {Shape{2, 3, 3},
 230                     Shape{5, 3, 3},
 231                     Shape{2, 5, 2},
 232                     Shape{8, 1, 8},
 233                     Shape{5},
 234                     Shape{8, 2},
 235                     Shape{8, 2, 8, 2},
 236                     Shape{2, 3, 4, 5, 2}});
 237 }
 238
 239 static void reverse_shape_test(const PartialShape& input_pshape,
 240                                const std::vector<Shape>& input_shapes)
 241 {
 242     auto x = make_shared<op::Parameter>(element::f32, input_pshape);
 243
 244     shared_ptr<Node> x_new_shape = make_shared<op::v0::ShapeOf>(x);
 245     x_new_shape = make_shared<op::Reverse>(x_new_shape, AxisSet{0});
 246
 247     auto x_reshaped = make_shared<op::v1::Reshape>(x, x_new_shape, true);
 248
 249     auto f = make_shared<Function>(NodeVector{x_reshaped}, ParameterVector{x});
 250     auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
 251     auto ex = backend->compile(f);
 252
 253     auto t_r = backend->create_dynamic_tensor(element::f32, PartialShape::dynamic());
 254
 255     for (auto& shape : input_shapes)
 256     {
 257         vector<float> inputs(shape_size(shape));
 258         for (size_t i = 0; i < shape_size(shape); i++)
 259         {
 260             inputs[i] = i;
 261         }
 262
 263         auto t_x = backend->create_tensor(element::f32, shape);
 264
 265         copy_data(t_x, inputs);
 266
 267         ex->call_with_validate({t_r}, {t_x});
 268
 269         Shape expected_shape = shape;
 270         std::reverse(expected_shape.begin(), expected_shape.end());
 271         ASSERT_EQ(t_r->get_shape(), expected_shape);
 272
 273         auto results = read_vector<float>(t_r);
 274
 275         EXPECT_TRUE(test::all_close_f(results, inputs));
 276     }
 277 }
 278
 279 NGRAPH_TEST(${BACKEND_NAME}, dynamic_reverse_shape)
 280 {
 281     // Test with shape {?, 3, 3}.
 282     reverse_shape_test(PartialShape{Dimension::dynamic(), 3, 3}, {Shape{2, 3, 3}, Shape{5, 3, 3}});
 283
 284     // Test with shape {?, ?, ?}.
 285     reverse_shape_test(PartialShape::dynamic(3),
 286                        {Shape{2, 3, 3}, Shape{5, 3, 3}, Shape{2, 5, 2}, Shape{8, 1, 8}});
 287
 288     // Test with shape ?. (Rank unknown.)
 289     reverse_shape_test(PartialShape::dynamic(),
 290                        {Shape{2, 3, 3},
 291                         Shape{5, 3, 3},
 292                         Shape{2, 5, 2},
 293                         Shape{8, 1, 8},
 294                         Shape{5},
 295                         Shape{8, 2},
 296                         Shape{8, 2, 8, 2},
 297                         Shape{2, 3, 4, 5, 2}});
 298 }