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[test] simple test for DeconvolutionLayer
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#include <cstring> | ||
#include <vector> | ||
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#include "gtest/gtest.h" | ||
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#include "caffe/blob.hpp" | ||
#include "caffe/common.hpp" | ||
#include "caffe/filler.hpp" | ||
#include "caffe/vision_layers.hpp" | ||
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#include "caffe/test/test_caffe_main.hpp" | ||
#include "caffe/test/test_gradient_check_util.hpp" | ||
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namespace caffe { | ||
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// Since ConvolutionLayerTest checks the shared conv/deconv code in detail, | ||
// we'll just do a simple forward test and a gradient check. | ||
template <typename TypeParam> | ||
class DeconvolutionLayerTest : public MultiDeviceTest<TypeParam> { | ||
typedef typename TypeParam::Dtype Dtype; | ||
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protected: | ||
DeconvolutionLayerTest() | ||
: 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_); | ||
} | ||
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virtual ~DeconvolutionLayerTest() { | ||
delete blob_bottom_; | ||
delete blob_bottom_2_; | ||
delete blob_top_; | ||
delete blob_top_2_; | ||
} | ||
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Blob<Dtype>* const blob_bottom_; | ||
Blob<Dtype>* const blob_bottom_2_; | ||
Blob<Dtype>* const blob_top_; | ||
Blob<Dtype>* const blob_top_2_; | ||
vector<Blob<Dtype>*> blob_bottom_vec_; | ||
vector<Blob<Dtype>*> blob_top_vec_; | ||
}; | ||
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TYPED_TEST_CASE(DeconvolutionLayerTest, TestDtypesAndDevices); | ||
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TYPED_TEST(DeconvolutionLayerTest, TestSetup) { | ||
typedef typename TypeParam::Dtype Dtype; | ||
LayerParameter layer_param; | ||
ConvolutionParameter* convolution_param = | ||
layer_param.mutable_convolution_param(); | ||
convolution_param->set_kernel_size(3); | ||
convolution_param->set_stride(2); | ||
convolution_param->set_num_output(4); | ||
this->blob_bottom_vec_.push_back(this->blob_bottom_2_); | ||
this->blob_top_vec_.push_back(this->blob_top_2_); | ||
shared_ptr<Layer<Dtype> > layer( | ||
new DeconvolutionLayer<Dtype>(layer_param)); | ||
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_); | ||
EXPECT_EQ(this->blob_top_->num(), 2); | ||
EXPECT_EQ(this->blob_top_->channels(), 4); | ||
EXPECT_EQ(this->blob_top_->height(), 13); | ||
EXPECT_EQ(this->blob_top_->width(), 9); | ||
EXPECT_EQ(this->blob_top_2_->num(), 2); | ||
EXPECT_EQ(this->blob_top_2_->channels(), 4); | ||
EXPECT_EQ(this->blob_top_2_->height(), 13); | ||
EXPECT_EQ(this->blob_top_2_->width(), 9); | ||
// setting group should not change the shape | ||
convolution_param->set_num_output(3); | ||
convolution_param->set_group(3); | ||
layer.reset(new DeconvolutionLayer<Dtype>(layer_param)); | ||
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_); | ||
EXPECT_EQ(this->blob_top_->num(), 2); | ||
EXPECT_EQ(this->blob_top_->channels(), 3); | ||
EXPECT_EQ(this->blob_top_->height(), 13); | ||
EXPECT_EQ(this->blob_top_->width(), 9); | ||
EXPECT_EQ(this->blob_top_2_->num(), 2); | ||
EXPECT_EQ(this->blob_top_2_->channels(), 3); | ||
EXPECT_EQ(this->blob_top_2_->height(), 13); | ||
EXPECT_EQ(this->blob_top_2_->width(), 9); | ||
} | ||
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TYPED_TEST(DeconvolutionLayerTest, TestSimpleDeconvolution) { | ||
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->set_kernel_size(3); | ||
convolution_param->set_stride(2); | ||
convolution_param->set_num_output(4); | ||
convolution_param->mutable_weight_filler()->set_type("constant"); | ||
convolution_param->mutable_weight_filler()->set_value(1); | ||
convolution_param->mutable_bias_filler()->set_type("constant"); | ||
convolution_param->mutable_bias_filler()->set_value(0.1); | ||
shared_ptr<Layer<Dtype> > layer( | ||
new DeconvolutionLayer<Dtype>(layer_param)); | ||
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_); | ||
// constant-fill the bottom blobs | ||
FillerParameter filler_param; | ||
filler_param.set_value(1.); | ||
ConstantFiller<Dtype> filler(filler_param); | ||
filler.Fill(this->blob_bottom_); | ||
filler.Fill(this->blob_bottom_2_); | ||
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_); | ||
// simply check that accumulation works with overlapping filters | ||
const Dtype* top_data = this->blob_top_->cpu_data(); | ||
for (int n = 0; n < this->blob_top_->num(); ++n) { | ||
for (int c = 0; c < this->blob_top_->channels(); ++c) { | ||
for (int h = 0; h < this->blob_top_->height(); ++h) { | ||
for (int w = 0; w < this->blob_top_->width(); ++w) { | ||
Dtype expected = 3.1; | ||
bool h_overlap = h % 2 == 0 && h > 0 | ||
&& h < this->blob_top_->height() - 1; | ||
bool w_overlap = w % 2 == 0 && w > 0 | ||
&& w < this->blob_top_->width() - 1; | ||
if (h_overlap && w_overlap) { | ||
expected += 9; | ||
} else if (h_overlap || w_overlap) { | ||
expected += 3; | ||
} | ||
EXPECT_NEAR(top_data[this->blob_top_->offset(n, c, h, w)], | ||
expected, 1e-4); | ||
} | ||
} | ||
} | ||
} | ||
} | ||
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TYPED_TEST(DeconvolutionLayerTest, TestGradient) { | ||
typedef typename TypeParam::Dtype Dtype; | ||
LayerParameter layer_param; | ||
ConvolutionParameter* convolution_param = | ||
layer_param.mutable_convolution_param(); | ||
this->blob_bottom_vec_.push_back(this->blob_bottom_2_); | ||
this->blob_top_vec_.push_back(this->blob_top_2_); | ||
convolution_param->set_kernel_size(2); | ||
convolution_param->set_stride(1); | ||
convolution_param->set_num_output(1); | ||
convolution_param->mutable_weight_filler()->set_type("gaussian"); | ||
convolution_param->mutable_bias_filler()->set_type("gaussian"); | ||
DeconvolutionLayer<Dtype> layer(layer_param); | ||
GradientChecker<Dtype> checker(1e-2, 1e-3); | ||
checker.CheckGradientExhaustive(&layer, this->blob_bottom_vec_, | ||
this->blob_top_vec_); | ||
} | ||
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} // namespace caffe |