Reshape layer

include/caffe/vision_layers.hpp

@@ -128,6 +128,29 @@ class FlattenLayer : public Layer<Dtype> {
   int count_;
 };
 
+template <typename Dtype>
+class ReshapeLayer : public Layer<Dtype> {
+ public:
+  explicit ReshapeLayer(const LayerParameter& param)
+      : Layer<Dtype>(param) {}
+  virtual void SetUp(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top);
+
+ protected:
+  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top);
+  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top);
+  virtual Dtype Backward_cpu(const vector<Blob<Dtype>*>& top,
+      const bool propagate_down, vector<Blob<Dtype>*>* bottom);
+  virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top,
+      const bool propagate_down, vector<Blob<Dtype>*>* bottom);
+  int COUNT_;
+  int NUM_;
+  int CHANNELS_;
+  int HEIGHT_;
+  int WIDTH_;  
+};
 
 template <typename Dtype>
 class InnerProductLayer : public Layer<Dtype> {

src/caffe/layer_factory.cpp

@@ -33,6 +33,8 @@ Layer<Dtype>* GetLayer(const LayerParameter& param) {
     return new EuclideanLossLayer<Dtype>(param);
   } else if (type == "flatten") {
     return new FlattenLayer<Dtype>(param);
+  } else if (type == "reshape") {
+    return new ReshapeLayer<Dtype>(param);
   } else if (type == "im2col") {
     return new Im2colLayer<Dtype>(param);
   } else if (type == "infogain_loss") {

src/caffe/layers/reshape_layer.cpp

@@ -0,0 +1,64 @@
+// Copyright 2014 Sergio Guadarama
+
+#include <vector>
+#include <string>
+
+#include "caffe/layer.hpp"
+#include "caffe/vision_layers.hpp"
+#include "caffe/util/math_functions.hpp"
+
+namespace caffe {
+
+template <typename Dtype>
+void ReshapeLayer<Dtype>::SetUp(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  CHECK_EQ(bottom.size(), 1) << "Reshape Layer takes a single blob as input.";
+  CHECK_EQ(top->size(), 1) << "Reshape Layer takes a single blob as output.";
+  NUM_ = this->layer_param_.new_num();
+  CHANNELS_ =  this->layer_param_.new_channels();
+  HEIGHT_ = this->layer_param_.new_height();
+  WIDTH_ = this->layer_param_.new_width();
+  COUNT_ = NUM_*CHANNELS_*HEIGHT_*WIDTH_;
+  (*top)[0]->Reshape(NUM_, CHANNELS_, HEIGHT_, WIDTH_);  
+  CHECK_EQ(COUNT_, bottom[0]->count());
+  CHECK_EQ(COUNT_, (*top)[0]->count());
+};
+
+template <typename Dtype>
+void ReshapeLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  const Dtype* bottom_data = bottom[0]->cpu_data();
+  Dtype* top_data = (*top)[0]->mutable_cpu_data();
+  caffe_copy(COUNT_, bottom_data, top_data);
+}
+
+template <typename Dtype>
+void ReshapeLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  const Dtype* bottom_data = bottom[0]->gpu_data();
+  Dtype* top_data = (*top)[0]->mutable_gpu_data();
+  caffe_gpu_copy(COUNT_, bottom_data, top_data);
+}
+
+template <typename Dtype>
+Dtype ReshapeLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
+      const bool propagate_down, vector<Blob<Dtype>*>* bottom) {
+  const Dtype* top_diff = top[0]->cpu_diff();
+  Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff();
+  caffe_copy(COUNT_, top_diff, bottom_diff);
+  return Dtype(0.);
+}
+
+
+template <typename Dtype>
+Dtype ReshapeLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top,
+      const bool propagate_down, vector<Blob<Dtype>*>* bottom) {
+  const Dtype* top_diff = top[0]->gpu_diff();
+  Dtype* bottom_diff = (*bottom)[0]->mutable_gpu_diff();
+  caffe_gpu_copy(COUNT_, top_diff, bottom_diff);
+  return Dtype(0.);
+}
+
+INSTANTIATE_CLASS(ReshapeLayer);
+
+}  // namespace caffe

src/caffe/proto/caffe.proto

@@ -91,6 +91,12 @@ message LayerParameter {
   // point would be set as rand_skip * rand(0,1). Note that rand_skip should not
   // be larger than the number of keys in the leveldb.
   optional uint32 rand_skip = 53 [ default = 0 ];
+
+  // For the Reshape Layer one need to specify the new dimensions
+  optional int32 new_num = 60 [default = 0];
+  optional int32 new_channels = 61 [default = 0];
+  optional int32 new_height = 62 [default = 0];
+  optional int32 new_width = 63 [default = 0];
 }
 
 message LayerConnection {

src/caffe/test/test_reshape_layer.cpp

@@ -0,0 +1,174 @@
+// Copyright 2014 Sergio Guadarrama
+
+#include <cstring>
+// #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 ReshapeLayerTest : public ::testing::Test {
+ protected:
+  ReshapeLayerTest()
+      : blob_bottom_(new Blob<Dtype>(2, 3, 6, 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 ~ReshapeLayerTest() { 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(ReshapeLayerTest, Dtypes);
+
+TYPED_TEST(ReshapeLayerTest, TestSetup) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(1);
+  layer_param.set_new_channels(2 * 3);
+  layer_param.set_new_height(6);
+  layer_param.set_new_width(5);
+  ReshapeLayer<TypeParam> layer(layer_param);
+  layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
+  EXPECT_EQ(this->blob_top_->num(), 1);
+  EXPECT_EQ(this->blob_top_->channels(), 2 * 3);
+  EXPECT_EQ(this->blob_top_->height(), 6);
+  EXPECT_EQ(this->blob_top_->width(), 5);
+}
+
+TYPED_TEST(ReshapeLayerTest, TestSetup2) {
+  // Reshape like flatten
+  LayerParameter layer_param;
+  layer_param.set_new_num(2);
+  layer_param.set_new_channels(3 * 6 * 5);
+  layer_param.set_new_height(1);
+  layer_param.set_new_width(1);
+  ReshapeLayer<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(), 3 * 6 * 5);
+  EXPECT_EQ(this->blob_top_->height(), 1);
+  EXPECT_EQ(this->blob_top_->width(), 1);
+}
+
+TYPED_TEST(ReshapeLayerTest, TestCPU) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(1);
+  layer_param.set_new_channels(2 * 3);
+  layer_param.set_new_height(6);
+  layer_param.set_new_width(5);
+  ReshapeLayer<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_));
+  for (int c = 0; c < 2 * 3; ++c) {
+    for (int h = 0; h < 6; ++h) {
+      for (int w = 0; w < 5; ++w) {
+        EXPECT_EQ(this->blob_top_->data_at(0, c, h, w),
+          this->blob_bottom_->data_at(c / 3, c % 3, h, w));
+      }
+    }
+  }
+}
+
+TYPED_TEST(ReshapeLayerTest, TestCPU2) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(2);
+  layer_param.set_new_channels(3 * 6 * 5);
+  layer_param.set_new_height(1);
+  layer_param.set_new_width(1);
+  ReshapeLayer<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_));
+  for (int c = 0; c < 3 * 6 * 5; ++c) {
+    EXPECT_EQ(this->blob_top_->data_at(0, c, 0, 0),
+        this->blob_bottom_->data_at(0, c / (6 * 5), (c / 5) % 6, c % 5));
+    EXPECT_EQ(this->blob_top_->data_at(1, c, 0, 0),
+        this->blob_bottom_->data_at(1, c / (6 * 5), (c / 5) % 6, c % 5));
+  }
+}
+
+
+
+TYPED_TEST(ReshapeLayerTest, TestGPU) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(1);
+  layer_param.set_new_channels(2 * 3);
+  layer_param.set_new_height(6);
+  layer_param.set_new_width(5);
+  ReshapeLayer<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_));
+  for (int c = 0; c < 2 * 3; ++c) {
+    for (int h = 0; h < 6; ++h) {
+      for (int w = 0; w < 5; ++w) {
+        EXPECT_EQ(this->blob_top_->data_at(0, c, h, w),
+          this->blob_bottom_->data_at(c / 3, c % 3, h, w));
+      }
+    }
+  }
+}
+
+TYPED_TEST(ReshapeLayerTest, TestGPU2) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(2);
+  layer_param.set_new_channels(3 * 6 * 5);
+  layer_param.set_new_height(1);
+  layer_param.set_new_width(1);
+  ReshapeLayer<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_));
+  for (int c = 0; c < 3 * 6 * 5; ++c) {
+    EXPECT_EQ(this->blob_top_->data_at(0, c, 0, 0),
+        this->blob_bottom_->data_at(0, c / (6 * 5), (c / 5) % 6, c % 5));
+    EXPECT_EQ(this->blob_top_->data_at(1, c, 0, 0),
+        this->blob_bottom_->data_at(1, c / (6 * 5), (c / 5) % 6, c % 5));
+  }
+}
+
+TYPED_TEST(ReshapeLayerTest, TestCPUGradient) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(1);
+  layer_param.set_new_channels(2 * 3);
+  layer_param.set_new_height(6);
+  layer_param.set_new_width(5);
+  Caffe::set_mode(Caffe::CPU);
+  ReshapeLayer<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2);
+  checker.CheckGradientExhaustive(layer, this->blob_bottom_vec_, this->blob_top_vec_);
+}
+
+TYPED_TEST(ReshapeLayerTest, TestGPUGradient) {
+  LayerParameter layer_param;
+  layer_param.set_new_num(1);
+  layer_param.set_new_channels(2 * 3);
+  layer_param.set_new_height(6);
+  layer_param.set_new_width(5);
+  Caffe::set_mode(Caffe::GPU);
+  ReshapeLayer<TypeParam> layer(layer_param);
+  GradientChecker<TypeParam> checker(1e-2, 1e-2);
+  checker.CheckGradientExhaustive(layer, this->blob_bottom_vec_, this->blob_top_vec_);
+}
+
+
+}