telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 4 | // |
| 5 | #include <boost/test/unit_test.hpp> |
| 6 | #include "armnnCaffeParser/ICaffeParser.hpp" |
| 7 | #include "ParserPrototxtFixture.hpp" |
| 8 | #include <sstream> |
| 9 | #include <initializer_list> |
| 10 | |
| 11 | namespace |
| 12 | { |
| 13 | |
| 14 | template <typename T> |
| 15 | std::string TaggedSequence(const std::string & tag, const std::initializer_list<T> & data) |
| 16 | { |
| 17 | bool first = true; |
| 18 | std::stringstream ss; |
| 19 | for (auto && d : data) |
| 20 | { |
| 21 | if (!first) |
| 22 | { |
| 23 | ss << " , "; |
| 24 | } |
| 25 | else |
| 26 | { |
| 27 | first = false; |
| 28 | } |
| 29 | ss << " " << tag << " : " << d << " "; |
| 30 | } |
| 31 | return ss.str(); |
| 32 | } |
| 33 | |
| 34 | template <typename T> |
| 35 | std::string TaggedSequence(const std::string & tag, T data, unsigned int n) |
| 36 | { |
| 37 | std::stringstream ss; |
| 38 | for (unsigned int i=0; i<n; ++i) |
| 39 | { |
| 40 | if (i>0) |
| 41 | { |
| 42 | ss << " , "; |
| 43 | } |
| 44 | ss << " " << tag << " : " << data << " "; |
| 45 | } |
| 46 | return ss.str(); |
| 47 | } |
| 48 | |
| 49 | } // namespace <anonymous> |
| 50 | |
| 51 | BOOST_AUTO_TEST_SUITE(CaffeParser) |
| 52 | |
| 53 | struct ConvolutionFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser> |
| 54 | { |
| 55 | ConvolutionFixture(const std::initializer_list<unsigned int> & inputDims, |
| 56 | const std::initializer_list<float> & filterData, |
| 57 | unsigned int kernelSize, |
| 58 | unsigned int numOutput=1, |
| 59 | unsigned int group=1) |
| 60 | { |
| 61 | m_Prototext = R"( |
| 62 | name: "ConvolutionTest" |
| 63 | layer { |
| 64 | name: "input1" |
| 65 | type: "Input" |
| 66 | top: "input1" |
| 67 | input_param { shape: { )" + TaggedSequence("dim", inputDims) + R"( } } |
| 68 | } |
| 69 | layer { |
| 70 | name: "conv1" |
| 71 | type: "Convolution" |
| 72 | bottom: "input1" |
| 73 | top: "conv1" |
| 74 | blobs: { )" + TaggedSequence("data", filterData) + R"( } |
| 75 | blobs: { )" + TaggedSequence("data", 0, numOutput) + R"( } |
| 76 | convolution_param { |
| 77 | num_output: )" + std::to_string(numOutput) + R"( |
| 78 | pad: 0 |
| 79 | kernel_size: )" + std::to_string(kernelSize) + R"( |
| 80 | stride: 1 |
| 81 | group: )" + std::to_string(group) + R"( |
| 82 | } |
| 83 | } |
| 84 | )"; |
| 85 | SetupSingleInputSingleOutput("input1", "conv1"); |
| 86 | } |
| 87 | }; |
| 88 | |
| 89 | struct SimpleConvolutionFixture : public ConvolutionFixture |
| 90 | { |
| 91 | SimpleConvolutionFixture() |
| 92 | : ConvolutionFixture( {1, 1, 2, 2}, {1.0f, 1.0f, 1.0f, 1.0f}, 2) |
| 93 | { |
| 94 | } |
| 95 | }; |
| 96 | |
| 97 | BOOST_FIXTURE_TEST_CASE(SimpleConvolution, SimpleConvolutionFixture) |
| 98 | { |
| 99 | RunTest<4>({ 1, 3, 5, 7 }, { 16 }); |
| 100 | } |
| 101 | |
| 102 | struct GroupConvolutionFixture : public ConvolutionFixture |
| 103 | { |
| 104 | GroupConvolutionFixture() |
| 105 | : ConvolutionFixture( |
| 106 | {1, 2, 2, 2}, |
| 107 | { |
| 108 | 1.0f, 1.0f, 1.0f, 1.0f, // filter for channel #0 |
| 109 | 2.0f, 2.0f, 2.0f, 2.0f // filter for channel #1 |
| 110 | }, |
| 111 | 2, // kernel size is 2x2 |
| 112 | 2, // number of output channels is 2 |
| 113 | 2) // number of groups (separate filters) |
| 114 | { |
| 115 | } |
| 116 | }; |
| 117 | |
| 118 | BOOST_FIXTURE_TEST_CASE(GroupConvolution, GroupConvolutionFixture) |
| 119 | { |
| 120 | RunTest<4>( |
| 121 | { |
| 122 | 1, 2, 3, 4, // input channel #0 |
| 123 | 5, 6, 7, 8, // input channel #1 |
| 124 | }, |
| 125 | { |
| 126 | 10, // convolution result for channel #0 applying filter #0 |
| 127 | 52 // same for channel #1 and filter #1 |
| 128 | } |
| 129 | ); |
| 130 | } |
| 131 | |
| 132 | |
| 133 | BOOST_AUTO_TEST_SUITE_END() |