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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <boost/test/unit_test.hpp>
#include "armnnCaffeParser/ICaffeParser.hpp"
#include "ParserPrototxtFixture.hpp"
#include <sstream>
#include <initializer_list>
namespace
{
template <typename T>
std::string TaggedSequence(const std::string & tag, const std::initializer_list<T> & data)
{
bool first = true;
std::stringstream ss;
for (auto && d : data)
{
if (!first)
{
ss << " , ";
}
else
{
first = false;
}
ss << " " << tag << " : " << d << " ";
}
return ss.str();
}
template <typename T>
std::string TaggedSequence(const std::string & tag, T data, unsigned int n)
{
std::stringstream ss;
for (unsigned int i=0; i<n; ++i)
{
if (i>0)
{
ss << " , ";
}
ss << " " << tag << " : " << data << " ";
}
return ss.str();
}
} // namespace <anonymous>
BOOST_AUTO_TEST_SUITE(CaffeParser)
struct ConvolutionFixture : public armnnUtils::ParserPrototxtFixture<armnnCaffeParser::ICaffeParser>
{
ConvolutionFixture(const std::initializer_list<unsigned int> & inputDims,
const std::initializer_list<float> & filterData,
unsigned int kernelSize,
unsigned int numOutput=1,
unsigned int group=1)
{
m_Prototext = R"(
name: "ConvolutionTest"
layer {
name: "input1"
type: "Input"
top: "input1"
input_param { shape: { )" + TaggedSequence("dim", inputDims) + R"( } }
}
layer {
name: "conv1"
type: "Convolution"
bottom: "input1"
top: "conv1"
blobs: { )" + TaggedSequence("data", filterData) + R"( }
blobs: { )" + TaggedSequence("data", 0, numOutput) + R"( }
convolution_param {
num_output: )" + std::to_string(numOutput) + R"(
pad: 0
kernel_size: )" + std::to_string(kernelSize) + R"(
stride: 1
group: )" + std::to_string(group) + R"(
}
}
)";
SetupSingleInputSingleOutput("input1", "conv1");
}
};
struct SimpleConvolutionFixture : public ConvolutionFixture
{
SimpleConvolutionFixture()
: ConvolutionFixture( {1, 1, 2, 2}, {1.0f, 1.0f, 1.0f, 1.0f}, 2)
{
}
};
BOOST_FIXTURE_TEST_CASE(SimpleConvolution, SimpleConvolutionFixture)
{
RunTest<4>({ 1, 3, 5, 7 }, { 16 });
}
struct GroupConvolutionFixture : public ConvolutionFixture
{
GroupConvolutionFixture()
: ConvolutionFixture(
{1, 2, 2, 2},
{
1.0f, 1.0f, 1.0f, 1.0f, // filter for channel #0
2.0f, 2.0f, 2.0f, 2.0f // filter for channel #1
},
2, // kernel size is 2x2
2, // number of output channels is 2
2) // number of groups (separate filters)
{
}
};
BOOST_FIXTURE_TEST_CASE(GroupConvolution, GroupConvolutionFixture)
{
RunTest<4>(
{
1, 2, 3, 4, // input channel #0
5, 6, 7, 8, // input channel #1
},
{
10, // convolution result for channel #0 applying filter #0
52 // same for channel #1 and filter #1
}
);
}
BOOST_AUTO_TEST_SUITE_END()
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