adding forgotten fixed layer files.

src/caffe/layers/dropout_fixed_layer.cpp

@@ -0,0 +1,79 @@
+// TODO (sergeyk): effect should not be dependent on phase. wasted memcpy.
+
+#include <vector>
+
+#include "caffe/common.hpp"
+#include "caffe/layer.hpp"
+#include "caffe/syncedmem.hpp"
+#include "caffe/util/math_functions.hpp"
+#include "caffe/vision_layers.hpp"
+
+namespace caffe {
+
+template <typename Dtype>
+void DropoutFixedLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  NeuronLayer<Dtype>::LayerSetUp(bottom, top);
+  threshold_ = this->layer_param_.dropout_param().dropout_ratio();
+  DCHECK(threshold_ > 0.);
+  DCHECK(threshold_ < 1.);
+  scale_ = 1. / (1. - threshold_);
+  uint_thres_ = static_cast<unsigned int>(UINT_MAX * threshold_);
+}
+
+template <typename Dtype>
+void DropoutFixedLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
+      vector<Blob<Dtype>*>* top) {
+  NeuronLayer<Dtype>::Reshape(bottom, top);
+  // Set up the cache for random number generation
+  rand_vec_.Reshape(bottom[0]->num(), bottom[0]->channels(),
+      bottom[0]->height(), bottom[0]->width());
+}
+
+template <typename Dtype>
+void DropoutFixedLayer<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();
+  unsigned int* mask = rand_vec_.mutable_cpu_data();
+  const int count = bottom[0]->count();
+  if (Caffe::phase() == Caffe::TRAIN) {
+    // Create random numbers
+    caffe_rng_bernoulli(count, 1. - threshold_, mask);
+    for (int i = 0; i < count; ++i) {
+      top_data[i] = bottom_data[i] * mask[i] * scale_;
+    }
+  } else {
+    caffe_copy(bottom[0]->count(), bottom_data, top_data);
+    caffe_scal(count, Dtype(1.0 - threshold_), top_data);
+  }
+}
+
+template <typename Dtype>
+void DropoutFixedLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
+    const vector<bool>& propagate_down,
+    vector<Blob<Dtype>*>* bottom) {
+  if (propagate_down[0]) {
+    const Dtype* top_diff = top[0]->cpu_diff();
+    Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff();
+    if (Caffe::phase() == Caffe::TRAIN) {
+      const unsigned int* mask = 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_;
+      }
+    } else {
+      caffe_copy(top[0]->count(), top_diff, bottom_diff);
+    }
+  }
+}
+
+
+#ifdef CPU_ONLY
+STUB_GPU(DropoutFixedLayer);
+#endif
+
+INSTANTIATE_CLASS(DropoutFixedLayer);
+
+
+}  // namespace caffe

src/caffe/layers/dropout_fixed_layer.cu

@@ -0,0 +1,78 @@
+#include <algorithm>
+#include <limits>
+#include <vector>
+
+#include "caffe/common.hpp"
+#include "caffe/layer.hpp"
+#include "caffe/syncedmem.hpp"
+#include "caffe/util/math_functions.hpp"
+#include "caffe/vision_layers.hpp"
+
+namespace caffe {
+
+
+template <typename Dtype>
+__global__ void DropoutFixedForward(const int n, const Dtype* in,
+    const unsigned int* mask, const unsigned int threshold, const float scale,
+    Dtype* out) {
+  CUDA_KERNEL_LOOP(index, n) {
+    out[index] = in[index] * (mask[index] > threshold) * scale;
+  }
+}
+
+template <typename Dtype>
+void DropoutFixedLayer<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();
+  const int count = bottom[0]->count();
+  if (Caffe::phase() == Caffe::TRAIN) {
+    unsigned int* mask =
+        static_cast<unsigned int*>(rand_vec_.mutable_gpu_data());
+    caffe_gpu_rng_uniform(count, mask);
+    // set thresholds
+    // NOLINT_NEXT_LINE(whitespace/operators)
+    DropoutFixedForward<Dtype><<<CAFFE_GET_BLOCKS(count), CAFFE_CUDA_NUM_THREADS>>>(
+        count, bottom_data, mask, uint_thres_, scale_, top_data);
+    CUDA_POST_KERNEL_CHECK;
+  } else {
+    caffe_copy(count, bottom_data, top_data);
+    caffe_gpu_scal(count, Dtype(1.0 - threshold_), top_data);
+  }
+}
+
+template <typename Dtype>
+__global__ void DropoutFixedBackward(const int n, const Dtype* in_diff,
+    const unsigned int* mask, const unsigned int threshold, const float scale,
+    Dtype* out_diff) {
+  CUDA_KERNEL_LOOP(index, n) {
+    out_diff[index] = in_diff[index] * scale * (mask[index] > threshold);
+  }
+}
+
+template <typename Dtype>
+void DropoutFixedLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top,
+    const vector<bool>& propagate_down,
+    vector<Blob<Dtype>*>* bottom) {
+  if (propagate_down[0]) {
+    const Dtype* top_diff = top[0]->gpu_diff();
+    Dtype* bottom_diff = (*bottom)[0]->mutable_gpu_diff();
+    if (Caffe::phase() == Caffe::TRAIN) {
+      const unsigned int* mask =
+          static_cast<const unsigned int*>(rand_vec_.gpu_data());
+      const int count = (*bottom)[0]->count();
+      // NOLINT_NEXT_LINE(whitespace/operators)
+      DropoutFixedBackward<Dtype><<<CAFFE_GET_BLOCKS(count),
+        CAFFE_CUDA_NUM_THREADS>>>(
+          count, top_diff, mask, uint_thres_, scale_, bottom_diff);
+      CUDA_POST_KERNEL_CHECK;
+    } else {
+      caffe_copy(top[0]->count(), top_diff, bottom_diff);
+    }
+  }
+}
+
+INSTANTIATE_CLASS(DropoutFixedLayer);
+
+
+}  // namespace caffe