text: #include <cmath>
  #include <cstdlib>
  #include <cstring>
  #include <vector>
  
  #include "gtest/gtest.h"
  
  #include "caffe/blob.hpp"
  #include "caffe/common.hpp"
  #include "caffe/filler.hpp"
  #include "caffe/loss_layers.hpp"
  
  #include "caffe/test/test_caffe_main.hpp"
  #include "caffe/test/test_gradient_check_util.hpp"
  
  namespace caffe {
  
  template <typename TypeParam>
  class InfogainLossLayerTest : public MultiDeviceTest<TypeParam> {
    typedef typename TypeParam::Dtype Dtype;
  
   protected:
    InfogainLossLayerTest()
        : blob_bottom_data_(new Blob<Dtype>(10, 5, 1, 1)),
          blob_bottom_label_(new Blob<Dtype>(10, 1, 1, 1)),
          blob_bottom_infogain_(new Blob<Dtype>(1, 1, 5, 5)),
          blob_top_loss_(new Blob<Dtype>()) {
      Caffe::set_random_seed(1701);
      FillerParameter filler_param;
      PositiveUnitballFiller<Dtype> filler(filler_param);
      filler.Fill(this->blob_bottom_data_);
      blob_bottom_vec_.push_back(blob_bottom_data_);
      for (int i = 0; i < blob_bottom_label_->count(); ++i) {
        blob_bottom_label_->mutable_cpu_data()[i] = caffe_rng_rand() % 5;
      }
      blob_bottom_vec_.push_back(blob_bottom_label_);
      filler_param.set_min(0.1);
      filler_param.set_max(2.0);
      UniformFiller<Dtype> infogain_filler(filler_param);
      infogain_filler.Fill(this->blob_bottom_infogain_);
      blob_bottom_vec_.push_back(blob_bottom_infogain_);
      blob_top_vec_.push_back(blob_top_loss_);
    }
    virtual ~InfogainLossLayerTest() {
      delete blob_bottom_data_;
      delete blob_bottom_label_;
      delete blob_bottom_infogain_;
      delete blob_top_loss_;
    }
    Blob<Dtype>* const blob_bottom_data_;
    Blob<Dtype>* const blob_bottom_label_;
    Blob<Dtype>* const blob_bottom_infogain_;
    Blob<Dtype>* const blob_top_loss_;
    vector<Blob<Dtype>*> blob_bottom_vec_;
    vector<Blob<Dtype>*> blob_top_vec_;
  };
  
  TYPED_TEST_CASE(InfogainLossLayerTest, TestDtypesAndDevices);
  
  
  TYPED_TEST(InfogainLossLayerTest, TestGradient) {
    typedef typename TypeParam::Dtype Dtype;
    LayerParameter layer_param;
    InfogainLossLayer<Dtype> layer(layer_param);
    GradientChecker<Dtype> checker(1e-4, 2e-2, 1701, 1, 0.01);
    checker.CheckGradientExhaustive(&layer, this->blob_bottom_vec_,
        this->blob_top_vec_, 0);
  }
  
  }  // namespace caffe
  