From: Jeff Donahue <jeff.donahue@gmail.com>
Date: Fri, 28 Mar 2014 22:39:33 +0000 (-0700)
Subject: add unit tests for new layer types
X-Git-Tag: submit/tizen/20180823.020014~692^2~55^2~16
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=f3e2fe67ae87dbcc0dfa2e812050ebc9fc55c85d;p=platform%2Fupstream%2Fcaffeonacl.git

add unit tests for new layer types
---

diff --git a/src/caffe/test/test_eltwise_product_layer.cpp b/src/caffe/test/test_eltwise_product_layer.cpp
new file mode 100644
index 0000000..8766f39
--- /dev/null
+++ b/src/caffe/test/test_eltwise_product_layer.cpp
@@ -0,0 +1,122 @@
+// Copyright 2014 BVLC and contributors.
+
+#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"
+
+namespace caffe {
+
+extern cudaDeviceProp CAFFE_TEST_CUDA_PROP;
+
+template <typename Dtype>
+class EltwiseProductLayerTest : public ::testing::Test {
+ protected:
+  EltwiseProductLayerTest()
+      : blob_bottom_a_(new Blob<Dtype>(2, 3, 4, 5)),
+        blob_bottom_b_(new Blob<Dtype>(2, 3, 4, 5)),
+        blob_bottom_c_(new Blob<Dtype>(2, 3, 4, 5)),
+        blob_top_(new Blob<Dtype>()) {
+    // fill the values
+    FillerParameter filler_param;
+    UniformFiller<Dtype> filler(filler_param);
+    filler.Fill(this->blob_bottom_a_);
+    filler.Fill(this->blob_bottom_b_);
+    filler.Fill(this->blob_bottom_c_);
+    blob_bottom_vec_.push_back(blob_bottom_a_);
+    blob_bottom_vec_.push_back(blob_bottom_b_);
+    blob_bottom_vec_.push_back(blob_bottom_c_);
+    blob_top_vec_.push_back(blob_top_);
+  }
+  virtual ~EltwiseProductLayerTest() {
+    delete blob_bottom_a_;
+    delete blob_bottom_b_;
+    delete blob_bottom_c_;
+    delete blob_top_;
+  }
+  Blob<Dtype>* const blob_bottom_a_;
+  Blob<Dtype>* const blob_bottom_b_;
+  Blob<Dtype>* const blob_bottom_c_;
+  Blob<Dtype>* const blob_top_;
+  vector<Blob<Dtype>*> blob_bottom_vec_;
+  vector<Blob<Dtype>*> blob_top_vec_;
+};
+
+typedef ::testing::Types<float, double> Dtypes;
+TYPED_TEST_CASE(EltwiseProductLayerTest, Dtypes);
+
+TYPED_TEST(EltwiseProductLayerTest, TestSetUp) {
+  LayerParameter layer_param;
+  shared_ptr<EltwiseProductLayer<TypeParam> > layer(
+      new EltwiseProductLayer<TypeParam>(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(), 4);
+  EXPECT_EQ(this->blob_top_->width(), 5);
+}
+
+TYPED_TEST(EltwiseProductLayerTest, TestCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  shared_ptr<EltwiseProductLayer<TypeParam> > layer(
+      new EltwiseProductLayer<TypeParam>(layer_param));
+  layer->SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer->Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  const TypeParam* data = this->blob_top_->cpu_data();
+  const int count = this->blob_top_->count();
+  const TypeParam* in_data_a = this->blob_bottom_a_->cpu_data();
+  const TypeParam* in_data_b = this->blob_bottom_b_->cpu_data();
+  const TypeParam* in_data_c = this->blob_bottom_c_->cpu_data();
+  for (int i = 0; i < count; ++i) {
+    EXPECT_EQ(data[i], in_data_a[i] * in_data_b[i] * in_data_c[i]);
+  }
+}
+
+TYPED_TEST(EltwiseProductLayerTest, TestGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  shared_ptr<EltwiseProductLayer<TypeParam> > layer(
+      new EltwiseProductLayer<TypeParam>(layer_param));
+  layer->SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer->Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  const TypeParam* data = this->blob_top_->cpu_data();
+  const int count = this->blob_top_->count();
+  const TypeParam* in_data_a = this->blob_bottom_a_->cpu_data();
+  const TypeParam* in_data_b = this->blob_bottom_b_->cpu_data();
+  const TypeParam* in_data_c = this->blob_bottom_c_->cpu_data();
+  for (int i = 0; i < count; ++i) {
+    EXPECT_EQ(data[i], in_data_a[i] * in_data_b[i] * in_data_c[i]);
+  }
+}
+
+TYPED_TEST(EltwiseProductLayerTest, TestCPUGradient) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  EltwiseProductLayer<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-3);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(EltwiseProductLayerTest, TestGPUGradient) {
+  if (sizeof(TypeParam) == 4 || CAFFE_TEST_CUDA_PROP.major >= 2) {
+    Caffe::set_mode(Caffe::GPU);
+    LayerParameter layer_param;
+    EltwiseProductLayer<TypeParam> layer(layer_param);
+    GradientChecker<TypeParam> checker(1e-2, 1e-2);
+    checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+        &(this->blob_top_vec_));
+  } else {
+    LOG(ERROR) << "Skipping test due to old architecture.";
+  }
+}
+
+}  // namespace caffe
diff --git a/src/caffe/test/test_lrn_map_layer.cpp b/src/caffe/test/test_lrn_map_layer.cpp
new file mode 100644
index 0000000..93377cc
--- /dev/null
+++ b/src/caffe/test/test_lrn_map_layer.cpp
@@ -0,0 +1,160 @@
+// 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::min;
+using std::max;
+
+namespace caffe {
+
+extern cudaDeviceProp CAFFE_TEST_CUDA_PROP;
+
+template <typename Dtype>
+class LRNMapLayerTest : public ::testing::Test {
+ protected:
+  LRNMapLayerTest()
+      : blob_bottom_(new Blob<Dtype>()),
+        blob_top_(new Blob<Dtype>()) {}
+  virtual void SetUp() {
+    Caffe::set_random_seed(1701);
+    blob_bottom_->Reshape(2, 2, 7, 7);
+    // 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_);
+    epsilon_ = 1e-5;
+  }
+  virtual ~LRNMapLayerTest() { delete blob_bottom_; delete blob_top_; }
+  void ReferenceLRNMapForward(const Blob<Dtype>& blob_bottom,
+      const LayerParameter& layer_param, Blob<Dtype>* blob_top);
+  Blob<Dtype>* const blob_bottom_;
+  Blob<Dtype>* const blob_top_;
+  vector<Blob<Dtype>*> blob_bottom_vec_;
+  vector<Blob<Dtype>*> blob_top_vec_;
+  Dtype epsilon_;
+};
+
+template <typename Dtype>
+void LRNMapLayerTest<Dtype>::ReferenceLRNMapForward(
+    const Blob<Dtype>& blob_bottom, const LayerParameter& layer_param,
+    Blob<Dtype>* blob_top) {
+  blob_top->Reshape(blob_bottom.num(), blob_bottom.channels(),
+      blob_bottom.height(), blob_bottom.width());
+  const Dtype* bottom_data = blob_bottom.cpu_data();
+  Dtype* top_data = blob_top->mutable_cpu_data();
+  const Dtype alpha = layer_param.lrn_map_param().alpha();
+  const Dtype beta = layer_param.lrn_map_param().beta();
+  const int size = layer_param.lrn_map_param().local_size();
+  for (int n = 0; n < blob_bottom.num(); ++n) {
+    for (int c = 0; c < blob_bottom.channels(); ++c) {
+      for (int h = 0; h < blob_bottom.height(); ++h) {
+        int h_start = h - (size - 1) / 2;
+        int h_end = min(h_start + size, blob_bottom.height());
+        h_start = max(h_start, 0);
+        for (int w = 0; w < blob_bottom.width(); ++w) {
+          Dtype scale = 1.;
+          int w_start = w - (size - 1) / 2;
+          int w_end = min(w_start + size, blob_bottom.width());
+          w_start = max(w_start, 0);
+          for (int nh = h_start; nh < h_end; ++nh) {
+            for (int nw = w_start; nw < w_end; ++nw) {
+              Dtype value = blob_bottom.data_at(n, c, nh, nw);
+              scale += value * value * alpha / (size * size);
+            }
+          }
+          *(top_data + blob_top->offset(n, c, h, w)) =
+            blob_bottom.data_at(n, c, h, w) / pow(scale, beta);
+        }
+      }
+    }
+  }
+}
+
+typedef ::testing::Types<float, double> Dtypes;
+TYPED_TEST_CASE(LRNMapLayerTest, Dtypes);
+
+TYPED_TEST(LRNMapLayerTest, TestSetup) {
+  LayerParameter layer_param;
+  LRNMapLayer<TypeParam> layer(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(), 2);
+  EXPECT_EQ(this->blob_top_->height(), 7);
+  EXPECT_EQ(this->blob_top_->width(), 7);
+}
+
+TYPED_TEST(LRNMapLayerTest, TestCPUForward) {
+  LayerParameter layer_param;
+  LRNMapLayer<TypeParam> layer(layer_param);
+  Caffe::set_mode(Caffe::CPU);
+  layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  Blob<TypeParam> top_reference;
+  this->ReferenceLRNMapForward(*(this->blob_bottom_), layer_param,
+      &top_reference);
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    EXPECT_NEAR(this->blob_top_->cpu_data()[i], top_reference.cpu_data()[i],
+                this->epsilon_);
+  }
+}
+
+TYPED_TEST(LRNMapLayerTest, TestGPUForward) {
+  LayerParameter layer_param;
+  LRNMapLayer<TypeParam> layer(layer_param);
+  Caffe::set_mode(Caffe::GPU);
+  layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  Blob<TypeParam> top_reference;
+  this->ReferenceLRNMapForward(*(this->blob_bottom_), layer_param,
+      &top_reference);
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    EXPECT_NEAR(this->blob_top_->cpu_data()[i], top_reference.cpu_data()[i],
+                this->epsilon_);
+  }
+}
+
+TYPED_TEST(LRNMapLayerTest, TestCPUGradient) {
+  LayerParameter layer_param;
+  LRNMapLayer<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2);
+  Caffe::set_mode(Caffe::CPU);
+  layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  for (int i = 0; i < this->blob_top_->count(); ++i) {
+    this->blob_top_->mutable_cpu_diff()[i] = 1.;
+  }
+  layer.Backward(this->blob_top_vec_, true, &(this->blob_bottom_vec_));
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(LRNMapLayerTest, TestGPUGradient) {
+  LayerParameter layer_param;
+  LRNMapLayer<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2);
+  Caffe::set_mode(Caffe::GPU);
+  layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  for (int i = 0; i < this->blob_top_->count(); ++i) {
+    this->blob_top_->mutable_cpu_diff()[i] = 1.;
+  }
+  layer.Backward(this->blob_top_vec_, true, &(this->blob_bottom_vec_));
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+}  // namespace caffe
diff --git a/src/caffe/test/test_power_layer.cpp b/src/caffe/test/test_power_layer.cpp
new file mode 100644
index 0000000..40734b6
--- /dev/null
+++ b/src/caffe/test/test_power_layer.cpp
@@ -0,0 +1,429 @@
+// Copyright 2014 BVLC and contributors.
+
+#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"
+
+namespace caffe {
+
+extern cudaDeviceProp CAFFE_TEST_CUDA_PROP;
+
+template <typename Dtype>
+class PowerLayerTest : public ::testing::Test {
+ protected:
+  PowerLayerTest()
+      : blob_bottom_(new Blob<Dtype>(2, 3, 4, 5)),
+        blob_top_(new Blob<Dtype>()) {
+    // 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_; }
+  Blob<Dtype>* const blob_bottom_;
+  Blob<Dtype>* const blob_top_;
+  vector<Blob<Dtype>*> blob_bottom_vec_;
+  vector<Blob<Dtype>*> blob_top_vec_;
+};
+
+typedef ::testing::Types<float, double> Dtypes;
+TYPED_TEST_CASE(PowerLayerTest, Dtypes);
+
+TYPED_TEST(PowerLayerTest, TestPowerCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = pow(shift + scale * bottom_data[i], power);
+    if (isnan(expected_value)) {
+      EXPECT_TRUE(isnan(top_data[i]));
+    } else {
+      TypeParam precision = expected_value * 0.0001;
+      precision *= (precision < 0) ? -1 : 1;
+      EXPECT_NEAR(expected_value, top_data[i], precision);
+    }
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerGradientCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  // Avoid NaNs by forcing (shift + scale * x) >= 0
+  TypeParam* bottom_data = this->blob_bottom_->mutable_cpu_data();
+  TypeParam 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<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerGradientShiftZeroCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = 0.0;
+  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<TypeParam> layer(layer_param);
+  // Flip negative values in bottom vector as x < 0 -> x^0.37 = nan
+  TypeParam* bottom_data = this->blob_bottom_->mutable_cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    bottom_data[i] *= (bottom_data[i] < 0) ? -1 : 1;
+  }
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerZeroCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  TypeParam expected_value = TypeParam(1);
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    EXPECT_EQ(expected_value, top_data[i]);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerZeroGradientCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerOneCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 1.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = shift + scale * bottom_data[i];
+    EXPECT_NEAR(expected_value, top_data[i], 0.001);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerOneGradientCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 1.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.34;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = pow(shift + scale * bottom_data[i], 2);
+    EXPECT_NEAR(expected_value, top_data[i], 0.001);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoGradientCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoScaleHalfGradientCPU) {
+  Caffe::set_mode(Caffe::CPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.5;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = pow(shift + scale * bottom_data[i], power);
+    if (isnan(expected_value)) {
+      EXPECT_TRUE(isnan(top_data[i]));
+    } else {
+      TypeParam precision = expected_value * 0.0001;
+      precision *= (precision < 0) ? -1 : 1;
+      EXPECT_NEAR(expected_value, top_data[i], precision);
+    }
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerGradientGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  // Avoid NaNs by forcing (shift + scale * x) >= 0
+  TypeParam* bottom_data = this->blob_bottom_->mutable_cpu_data();
+  TypeParam 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<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerGradientShiftZeroGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.37;
+  TypeParam scale = 0.83;
+  TypeParam shift = 0.0;
+  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<TypeParam> layer(layer_param);
+  // Flip negative values in bottom vector as x < 0 -> x^0.37 = nan
+  TypeParam* bottom_data = this->blob_bottom_->mutable_cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    bottom_data[i] *= (bottom_data[i] < 0) ? -1 : 1;
+  }
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerZeroGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  TypeParam expected_value = TypeParam(1);
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    EXPECT_EQ(expected_value, top_data[i]);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerZeroGradientGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 0.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerOneGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 1.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = shift + scale * bottom_data[i];
+    EXPECT_NEAR(expected_value, top_data[i], 0.001);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerOneGradientGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 1.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.34;
+  TypeParam shift = -2.4;
+  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<TypeParam> 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 TypeParam* bottom_data = this->blob_bottom_->cpu_data();
+  const TypeParam* top_data = this->blob_top_->cpu_data();
+  for (int i = 0; i < this->blob_bottom_->count(); ++i) {
+    TypeParam expected_value = pow(shift + scale * bottom_data[i], 2);
+    EXPECT_NEAR(expected_value, top_data[i], 0.001);
+  }
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoGradientGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.83;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+TYPED_TEST(PowerLayerTest, TestPowerTwoScaleHalfGradientGPU) {
+  Caffe::set_mode(Caffe::GPU);
+  LayerParameter layer_param;
+  TypeParam power = 2.0;
+  TypeParam scale = 0.5;
+  TypeParam shift = -2.4;
+  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<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2, 1701, 0., 0.01);
+  checker.CheckGradientExhaustive(&layer, &(this->blob_bottom_vec_),
+      &(this->blob_top_vec_));
+}
+
+}  // namespace caffe