Caffe-HRT/unit_tests/prof_convolution_layer.cpp at master · OAID/Caffe-HRT · GitHub

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#include <vector>

#include "caffe/blob.hpp"

#include "caffe/common.hpp"

#include "caffe/filler.hpp"

#include "caffe/layers/conv_layer.hpp"

#include <glog/logging.h>

extern "C" {

#include "testbed.h"

}

#define TYPED_TEST(a,b) template <typename TypeParam> void a <TypeParam>:: b (void)

#define EXPECT_NEAR(a,b,c) {}

#define EXPECT_EQ(a,b) {}

namespace caffe {

template <typename TypeParam>

struct CPUDevice {

typedef TypeParam Dtype;

static const Caffe::Brew device = Caffe::CPU;

};

template <typename TypeParam>

class ConvolutionLayerTest {

typedef typename TypeParam::Dtype Dtype;

public:

void TestSimpleConvolution(void);

void TestDilatedConvolution(void);

void Test0DConvolution(void);

void TestSimple3DConvolution(void);

void TestDilated3DConvolution(void);

void Test1x1Convolution(void);

void TestSimpleConvolutionGroup(void);

void TestNDAgainst2D(void);

void RunConvolution(void);

ConvolutionLayerTest()

: blob_bottom_(new Blob<Dtype>(2, 3, 6, 4)),

blob_bottom_2_(new Blob<Dtype>(2, 3, 6, 4)),

blob_top_(new Blob<Dtype>()),

blob_top_2_(new Blob<Dtype>()) {}

virtual void SetUp() {

// fill the values

FillerParameter filler_param;

filler_param.set_value(1.);

GaussianFiller<Dtype> filler(filler_param);

filler.Fill(this->blob_bottom_);

filler.Fill(this->blob_bottom_2_);

blob_bottom_vec_.push_back(blob_bottom_);

blob_top_vec_.push_back(blob_top_);

}

virtual ~ConvolutionLayerTest() {

delete blob_bottom_;

delete blob_bottom_2_;

delete blob_top_;

delete blob_top_2_;

}

virtual Blob<Dtype>* MakeReferenceTop(Blob<Dtype>* top) {

this->ref_blob_top_.reset(new Blob<Dtype>());

this->ref_blob_top_->ReshapeLike(*top);

return this->ref_blob_top_.get();

}

Blob<Dtype>* const blob_bottom_;

Blob<Dtype>* const blob_bottom_2_;

Blob<Dtype>* const blob_top_;

Blob<Dtype>* const blob_top_2_;

shared_ptr<Blob<Dtype> > ref_blob_top_;

vector<Blob<Dtype>*> blob_bottom_vec_;

vector<Blob<Dtype>*> blob_top_vec_;

shared_ptr<Layer<Dtype> > layer;

};

TYPED_TEST(ConvolutionLayerTest, RunConvolution) {

layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, TestSimpleConvolution) {

typedef typename TypeParam::Dtype Dtype;

this->blob_bottom_vec_.push_back(this->blob_bottom_2_);

this->blob_top_vec_.push_back(this->blob_top_2_);

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(3);

convolution_param->add_stride(2);

convolution_param->set_num_output(4);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("constant");

convolution_param->mutable_bias_filler()->set_value(0.1);

layer=shared_ptr<Layer<Dtype> > (new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, TestDilatedConvolution) {

typedef typename TypeParam::Dtype Dtype;

vector<int> bottom_shape;

bottom_shape.push_back(2);

bottom_shape.push_back(3);

bottom_shape.push_back(8);

bottom_shape.push_back(7);

this->blob_bottom_vec_.push_back(this->blob_bottom_2_);

this->blob_top_vec_.push_back(this->blob_top_2_);

for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {

this->blob_bottom_vec_[i]->Reshape(bottom_shape);

}

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(3);

convolution_param->add_dilation(2);

convolution_param->set_num_output(4);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("constant");

convolution_param->mutable_bias_filler()->set_value(0.1);

layer=shared_ptr<Layer<Dtype> > (new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, Test0DConvolution) {

typedef typename TypeParam::Dtype Dtype;

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

const int kNumOutput = 3;

convolution_param->set_num_output(kNumOutput);

convolution_param->set_axis(3);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("gaussian");

layer=shared_ptr<Layer<Dtype> > (

new ConvolutionLayer<Dtype>(layer_param));

vector<int> top_shape = this->blob_bottom_->shape();

top_shape[3] = kNumOutput;

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

EXPECT_EQ(top_shape, this->blob_top_->shape());

}

TYPED_TEST(ConvolutionLayerTest, TestSimple3DConvolution) {

typedef typename TypeParam::Dtype Dtype;

this->blob_bottom_vec_.push_back(this->blob_bottom_2_);

this->blob_top_vec_.push_back(this->blob_top_2_);

vector<int> bottom_shape(5);

bottom_shape[0] = this->blob_bottom_vec_[0]->shape(0);

bottom_shape[1] = this->blob_bottom_vec_[0]->shape(1);

bottom_shape[2] = 5;

bottom_shape[3] = this->blob_bottom_vec_[0]->shape(2);

bottom_shape[4] = this->blob_bottom_vec_[0]->shape(3);

FillerParameter filler_param;

GaussianFiller<Dtype> filler(filler_param);

for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {

this->blob_bottom_vec_[i]->Reshape(bottom_shape);

filler.Fill(this->blob_bottom_vec_[i]);

}

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(3);

convolution_param->add_stride(2);

convolution_param->set_num_output(4);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("gaussian");

layer=shared_ptr<Layer<Dtype> > (

new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, TestDilated3DConvolution) {

typedef typename TypeParam::Dtype Dtype;

this->blob_bottom_vec_.push_back(this->blob_bottom_2_);

this->blob_top_vec_.push_back(this->blob_top_2_);

vector<int> bottom_shape(5);

bottom_shape[0] = this->blob_bottom_vec_[0]->shape(0);

bottom_shape[1] = this->blob_bottom_vec_[0]->shape(1);

bottom_shape[2] = 6;

bottom_shape[3] = 7;

bottom_shape[4] = 8;

FillerParameter filler_param;

GaussianFiller<Dtype> filler(filler_param);

for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {

this->blob_bottom_vec_[i]->Reshape(bottom_shape);

filler.Fill(this->blob_bottom_vec_[i]);

}

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(3);

convolution_param->add_dilation(2);

convolution_param->set_num_output(4);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("gaussian");

layer=shared_ptr<Layer<Dtype> > (

new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, Test1x1Convolution) {

typedef typename TypeParam::Dtype Dtype;

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(1);

convolution_param->add_stride(1);

convolution_param->set_num_output(4);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("constant");

convolution_param->mutable_bias_filler()->set_value(0.1);

layer=shared_ptr<Layer<Dtype> > (

new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

TYPED_TEST(ConvolutionLayerTest, TestSimpleConvolutionGroup) {

typedef typename TypeParam::Dtype Dtype;

LayerParameter layer_param;

ConvolutionParameter* convolution_param =

layer_param.mutable_convolution_param();

convolution_param->add_kernel_size(3);

convolution_param->add_stride(2);

convolution_param->set_num_output(3);

convolution_param->set_group(3);

convolution_param->mutable_weight_filler()->set_type("gaussian");

convolution_param->mutable_bias_filler()->set_type("constant");

convolution_param->mutable_bias_filler()->set_value(0.1);

layer=shared_ptr<Layer<Dtype> > (

new ConvolutionLayer<Dtype>(layer_param));

layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);

}

} // namespace caffe

using namespace caffe;

ConvolutionLayerTest<CPUDevice<float> > * g_convptr;

void single_forward(void * dummy )

{

g_convptr->RunConvolution();

}

void forward_convolution(void)

{

run_test(16,0,single_forward,NULL);

}

#define RUN_FUNC(test_case) test_ ## test_case ()

#define DEF_TEST_FUNC(test_case) \

void test_## test_case (void)\

std::cout<<__FUNCTION__<<" start ..."<<std::endl;\

g_convptr=new ConvolutionLayerTest<CPUDevice<float> >;\

g_convptr->SetUp();\

g_convptr->Test ## test_case ();\

forward_convolution();\

delete g_convptr;\

std::cout<<__FUNCTION__<<" DONE"<<std::endl;\

}

DEF_TEST_FUNC(SimpleConvolution)

DEF_TEST_FUNC(DilatedConvolution)

DEF_TEST_FUNC(0DConvolution)

DEF_TEST_FUNC(Simple3DConvolution)

DEF_TEST_FUNC(Dilated3DConvolution)

DEF_TEST_FUNC(1x1Convolution)

DEF_TEST_FUNC(SimpleConvolutionGroup)

int main(int argc, char * argv[])

{

caffe::GlobalInit(&argc, &argv);

init_testbed();

RUN_FUNC(SimpleConvolution);

RUN_FUNC(DilatedConvolution);

RUN_FUNC(0DConvolution);

RUN_FUNC(Simple3DConvolution);

RUN_FUNC(Dilated3DConvolution);

RUN_FUNC(1x1Convolution);

RUN_FUNC(SimpleConvolutionGroup);

release_testbed();

return 0;

}

Caffe-HRT/unit_tests/prof_convolution_layer.cpp at master · OAID/Caffe-HRT · GitHub

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