summaryrefslogtreecommitdiff
path: root/src/caffe/test/test_power_layer.cpp
blob: a1b716ad531eb0ea1a92f35e36b04d1f01c4cd99 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
// Copyright 2014 BVLC and contributors.

#include <algorithm>
#include <vector>

#include "cuda_runtime.h"
#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_gradient_check_util.hpp"

#include "caffe/test/test_caffe_main.hpp"

using std::isnan;

namespace caffe {

extern cudaDeviceProp CAFFE_TEST_CUDA_PROP;

template <typename TypeParam>
class PowerLayerTest : public MultiDeviceTest<TypeParam> {
  typedef typename TypeParam::Dtype Dtype;

 protected:
  PowerLayerTest()
      : blob_bottom_(new Blob<Dtype>(2, 3, 4, 5)),
        blob_top_(new Blob<Dtype>()) {
    Caffe::set_random_seed(1701);
    // fill the values
    FillerParameter filler_param;
    GaussianFiller<Dtype> filler(filler_param);
    filler.Fill(this->blob_bottom_);
    blob_bottom_vec_.push_back(blob_bottom_);
    blob_top_vec_.push_back(blob_top_);
  }
  virtual ~PowerLayerTest() { delete blob_bottom_; delete blob_top_; }

  void TestForward(Dtype power, Dtype scale, Dtype shift) {
    LayerParameter layer_param;
    layer_param.mutable_power_param()->set_power(power);
    layer_param.mutable_power_param()->set_scale(scale);
    layer_param.mutable_power_param()->set_shift(shift);
    PowerLayer<Dtype> layer(layer_param);
    layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
    layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
    // Now, check values
    const Dtype* bottom_data = this->blob_bottom_->cpu_data();
    const Dtype* top_data = this->blob_top_->cpu_data();
    const Dtype min_precision = 1e-5;
    for (int i = 0; i < this->blob_bottom_->count(); ++i) {
      Dtype expected_value = pow(shift + scale * bottom_data[i], power);
      if (power == Dtype(0) || power == Dtype(1) || power == Dtype(2)) {
        EXPECT_FALSE(isnan(top_data[i]));
      }
      if (isnan(expected_value)) {
        EXPECT_TRUE(isnan(top_data[i]));
      } else {
        Dtype precision = max(Dtype(abs(expected_value * 0.0001)),
                              min_precision);
        EXPECT_NEAR(expected_value, top_data[i], precision);
      }
    }
  }

  void TestBackward(Dtype power, Dtype scale, Dtype shift) {
    LayerParameter layer_param;
    layer_param.mutable_power_param()->set_power(power);
    layer_param.mutable_power_param()->set_scale(scale);
    layer_param.mutable_power_param()->set_shift(shift);
    PowerLayer<Dtype> layer(layer_param);
    if (power != Dtype(0) && power != Dtype(1) && power != Dtype(2)) {
      // Avoid NaNs by forcing (shift + scale * x) >= 0
      Dtype* bottom_data = this->blob_bottom_->mutable_cpu_data();
      Dtype min_value = -shift / scale;
      for (int i = 0; i < this->blob_bottom_->count(); ++i) {
        if (bottom_data[i] < min_value) {
          bottom_data[i] = min_value + (min_value - bottom_data[i]);
        }
      }
    }
    GradientChecker<Dtype> checker(1e-2, 1e-2, 1701, 0., 0.01);
    checker.CheckGradientEltwise(&layer, &(this->blob_bottom_vec_),
        &(this->blob_top_vec_));
  }

  Blob<Dtype>* const blob_bottom_;
  Blob<Dtype>* const blob_top_;
  vector<Blob<Dtype>*> blob_bottom_vec_;
  vector<Blob<Dtype>*> blob_top_vec_;
};

TYPED_TEST_CASE(PowerLayerTest, TestDtypesAndDevices);

TYPED_TEST(PowerLayerTest, TestPower) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 0.37;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestForward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerGradient) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 0.37;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestBackward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerGradientShiftZero) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 0.37;
  Dtype scale = 0.83;
  Dtype shift = 0.0;
  this->TestBackward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerZero) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 0.0;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestForward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerZeroGradient) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 0.0;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestBackward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerOne) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 1.0;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestForward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerOneGradient) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 1.0;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestBackward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerTwo) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 2.0;
  Dtype scale = 0.34;
  Dtype shift = -2.4;
  this->TestForward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerTwoGradient) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 2.0;
  Dtype scale = 0.83;
  Dtype shift = -2.4;
  this->TestBackward(power, scale, shift);
}

TYPED_TEST(PowerLayerTest, TestPowerTwoScaleHalfGradient) {
  typedef typename TypeParam::Dtype Dtype;
  Dtype power = 2.0;
  Dtype scale = 0.5;
  Dtype shift = -2.4;
  this->TestBackward(power, scale, shift);
}

}  // namespace caffe