Splitting source files between CUDA and CPU code.

1 files changed, 63 insertions, 0 deletions

diff --git a/src/caffe/layers/dropout_layer.cpp b/src/caffe/layers/dropout_layer.cpp
new file mode 100644
index 00000000..4e1fbfae
--- /dev/null
+++ b/src/caffe/layers/dropout_layer.cpp
@@ -0,0 +1,63 @@
+// Copyright 2013 Yangqing Jia
+
+#include "caffe/common.hpp"
+#include "caffe/layer.hpp"
+#include "caffe/syncedmem.hpp"
+#include "caffe/vision_layers.hpp"
+
+namespace caffe {
+
+template <typename Dtype>
+void DropoutLayer<Dtype>::SetUp(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  NeuronLayer<Dtype>::SetUp(bottom, top);
+  // Set up the cache for random number generation
+  rand_vec_.reset(new SyncedMemory(bottom[0]->count() * sizeof(int)));
+  threshold_ = this->layer_param_.dropout_ratio();
+  DCHECK(threshold_ > 0.);
+  DCHECK(threshold_ < 1.);
+  scale_ = 1. / (1. - threshold_);
+  uint_thres_ = (unsigned int)(UINT_MAX * threshold_);
+}
+
+template <typename Dtype>
+void DropoutLayer<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();
+  int* mask = reinterpret_cast<int*>(rand_vec_->mutable_cpu_data());
+  const int count = bottom[0]->count();
+  if (Caffe::phase() == Caffe::TRAIN) {
+    // Create random numbers
+    viRngBernoulli(VSL_RNG_METHOD_BERNOULLI_ICDF, Caffe::vsl_stream(),
+        count, mask, 1. - threshold_);
+    for (int i = 0; i < count; ++i) {
+      top_data[i] = bottom_data[i] * mask[i] * scale_;
+    }
+  } else {
+    memcpy(top_data, bottom_data, bottom[0]->count() * sizeof(Dtype));
+  }
+}
+
+template <typename Dtype>
+Dtype DropoutLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
+    const bool propagate_down,
+    vector<Blob<Dtype>*>* bottom) {
+  CHECK(Caffe::phase() == Caffe::TRAIN);
+  if (propagate_down) {
+    const Dtype* top_diff = top[0]->cpu_diff();
+    Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff();
+    const int* mask = reinterpret_cast<const int*>(rand_vec_->cpu_data());
+    const int count = (*bottom)[0]->count();
+    for (int i = 0; i < count; ++i) {
+      bottom_diff[i] = top_diff[i] * mask[i] * scale_;
+    }
+  }
+  return Dtype(0);
+}
+
+
+INSTANTIATE_CLASS(DropoutLayer);
+
+
+}  // namespace caffe