ngraph/test/backend/quantized_dot.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.hpp"
  22 #include "util/all_close_f.hpp"
  23 #include "util/known_element_types.hpp"
  24 #include "util/ndarray.hpp"
  25 #include "util/test_control.hpp"
  26 #include "util/test_tools.hpp"
  27
  28 NGRAPH_SUPPRESS_DEPRECATED_START
  29
  30 using namespace std;
  31 using namespace ngraph;
  32
  33 static string s_manifest = "${MANIFEST}";
  34
  35 NGRAPH_TEST(${BACKEND_NAME}, quantized_dot_u8u8)
  36 {
  37     Shape shape_a{1, 2}; // input shape
  38     vector<uint8_t> a_data = {2, 3};
  39     Shape shape_b{2, 3}; // filter shape
  40     vector<uint8_t> b_data = {0, 2, 4, 1, 3, 5};
  41     auto A = make_shared<op::Parameter>(element::u8, shape_a);
  42     auto B = make_shared<op::Parameter>(element::u8, shape_b);
  43     auto input_scale = op::Constant::create(element::f32, Shape{}, {2});
  44     auto input_zero_point = op::Constant::create(element::u8, Shape{}, {0});
  45     auto filter_scale = op::Constant::create(element::f32, Shape{}, {1});
  46     auto filter_zero_point = op::Constant::create(element::u8, Shape{}, {0});
  47     auto output_scale = op::Constant::create(element::f32, Shape{}, {2});
  48     auto output_zero_point = op::Constant::create(element::u8, Shape{}, {0});
  49     AxisSet axes{};
  50
  51     Shape shape_r{1, 3}; // output shape
  52     auto QD = make_shared<op::QuantizedDot>(A,
  53                                             B,
  54                                             1,
  55                                             input_scale,
  56                                             input_zero_point,
  57                                             filter_scale,
  58                                             filter_zero_point,
  59                                             output_scale,
  60                                             output_zero_point,
  61                                             element::u8,
  62                                             axes,
  63                                             axes,
  64                                             axes);
  65     auto f = make_shared<Function>(NodeVector{QD}, ParameterVector{A, B});
  66     auto backend = runtime::Backend::create("${BACKEND_NAME}");
  67     // Create some tensors for input/output
  68     auto a = backend->create_tensor(element::u8, shape_a);
  69     copy_data(a, a_data);
  70     auto b = backend->create_tensor(element::u8, shape_b);
  71     copy_data(b, b_data);
  72     auto result = backend->create_tensor(element::u8, shape_r);
  73     auto handle = backend->compile(f);
  74     handle->call_with_validate({result}, {a, b});
  75     EXPECT_EQ((vector<uint8_t>{3, 13, 23}), read_vector<uint8_t>(result));
  76 }
  77
  78 NGRAPH_TEST(${BACKEND_NAME}, quantized_dot_int32_output)
  79 {
  80     Shape shape_a{1, 2}; // input shape
  81     vector<uint8_t> a_data = {2, 3};
  82     Shape shape_b{2, 3}; // filter shape
  83     vector<int8_t> b_data = {0, 1, 2, 3, 4, 5};
  84     auto A = make_shared<op::Parameter>(element::u8, shape_a);
  85     auto B = make_shared<op::Parameter>(element::i8, shape_b);
  86     auto input_scale = op::Constant::create(element::f32, Shape{}, {1});
  87     auto input_zero_point = op::Constant::create(element::u8, Shape{}, {0});
  88     auto filter_scale = op::Constant::create(element::f32, Shape{}, {1});
  89     auto filter_zero_point = op::Constant::create(element::i8, Shape{}, {0});
  90     auto output_scale = op::Constant::create(element::f32, Shape{}, {1});
  91     auto output_zero_point = op::Constant::create(element::i32, Shape{}, {0});
  92     AxisSet axes{};
  93
  94     Shape shape_r{1, 3}; // output shape
  95     auto QD = make_shared<op::QuantizedDot>(A,
  96                                             B,
  97                                             1,
  98                                             input_scale,
  99                                             input_zero_point,
 100                                             filter_scale,
 101                                             filter_zero_point,
 102                                             output_scale,
 103                                             output_zero_point,
 104                                             element::i32,
 105                                             axes,
 106                                             axes,
 107                                             axes);
 108     auto f = make_shared<Function>(NodeVector{QD}, ParameterVector{A, B});
 109     auto backend = runtime::Backend::create("${BACKEND_NAME}");
 110     // Create some tensors for input/output
 111     auto a = backend->create_tensor(element::u8, shape_a);
 112     copy_data(a, a_data);
 113     auto b = backend->create_tensor(element::i8, shape_b);
 114     copy_data(b, b_data);
 115     auto result = backend->create_tensor(element::i32, shape_r);
 116     auto handle = backend->compile(f);
 117     handle->call_with_validate({result}, {a, b});
 118     EXPECT_EQ((vector<int32_t>{9, 14, 19}), read_vector<int32_t>(result));
 119 }