[test] simple test for DeconvolutionLayer

diff --git a/src/caffe/test/test_deconvolution_layer.cpp b/src/caffe/test/test_deconvolution_layer.cpp
new file mode 100644 (file)
index 0000000..fc63d5e
--- /dev/null
+++ b/src/caffe/test/test_deconvolution_layer.cpp
@@ -0,0 +1,158 @@
+#include <cstring>
+#include <vector>
+
+#include "gtest/gtest.h"
+
+#include "caffe/blob.hpp"
+#include "caffe/common.hpp"
+#include "caffe/filler.hpp"
+#include "caffe/vision_layers.hpp"
+
+#include "caffe/test/test_caffe_main.hpp"
+#include "caffe/test/test_gradient_check_util.hpp"
+
+namespace caffe {
+
+// 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;
+
+ 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_);
+  }
+
+  virtual ~DeconvolutionLayerTest() {
+    delete blob_bottom_;
+    delete blob_bottom_2_;
+    delete blob_top_;
+    delete blob_top_2_;
+  }
+
+  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_;
+};
+
+TYPED_TEST_CASE(DeconvolutionLayerTest, TestDtypesAndDevices);
+
+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);
+}
+
+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);
+        }
+      }
+    }
+  }
+}
+
+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_);
+}
+
+}  // namespace caffe