From 90b0eb085251ab75ed668972b9750160c32e93f0 Mon Sep 17 00:00:00 2001
From: Yangqing Jia <jiayq84@gmail.com>
Date: Fri, 27 Sep 2013 09:54:10 -0700
Subject: [PATCH] forgot to add the renamed file

---
 .../layers/multinomial_logistic_loss_layer.cu      | 52 ++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 src/caffe/layers/multinomial_logistic_loss_layer.cu

diff --git a/src/caffe/layers/multinomial_logistic_loss_layer.cu b/src/caffe/layers/multinomial_logistic_loss_layer.cu
new file mode 100644
index 0000000..5ffa4ac
--- /dev/null
+++ b/src/caffe/layers/multinomial_logistic_loss_layer.cu
@@ -0,0 +1,52 @@
+// Copyright 2013 Yangqing Jia
+
+#include "caffe/layer.hpp"
+#include "caffe/vision_layers.hpp"
+#include "caffe/util/math_functions.hpp"
+#include <algorithm>
+#include <cmath>
+
+using std::max;
+
+namespace caffe {
+
+template <typename Dtype>
+void MultinomialLogisticLossLayer<Dtype>::SetUp(
+    const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) {
+  CHECK_EQ(bottom.size(), 2) << "Loss Layer takes two blobs as input.";
+  CHECK_EQ(top->size(), 0) << "Loss Layer takes no as output.";
+  CHECK_EQ(bottom[0]->num(), bottom[1]->num())
+      << "The data and label should have the same number.";
+  CHECK_EQ(bottom[1]->channels(), 1);
+  CHECK_EQ(bottom[1]->height(), 1);
+  CHECK_EQ(bottom[1]->width(), 1);
+};
+
+
+template <typename Dtype>
+Dtype MultinomialLogisticLossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
+    const bool propagate_down,
+    vector<Blob<Dtype>*>* bottom) {
+  const Dtype* bottom_data = (*bottom)[0]->cpu_data();
+  const Dtype* bottom_label = (*bottom)[1]->cpu_data();
+  Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff();
+  int num = (*bottom)[0]->num();
+  int dim = (*bottom)[0]->count() / (*bottom)[0]->num();
+  memset(bottom_diff, 0, sizeof(Dtype) * (*bottom)[0]->count());
+  Dtype loss = 0;
+  const Dtype kLOG_THRESHOLD = 1e-8;
+  for (int i = 0; i < num; ++i) {
+    int label = static_cast<int>(bottom_label[i]);
+    Dtype prob = max(bottom_data[i * dim + label], kLOG_THRESHOLD);
+    loss -= log(prob);
+    bottom_diff[i * dim + label] = - 1. / prob / num;
+  }
+  return loss / num;
+}
+
+// TODO: implement the GPU version
+
+INSTANTIATE_CLASS(MultinomialLogisticLossLayer);
+
+
+}  // namespace caffe
-- 
2.7.4