Release 18.08

[platform/upstream/armnn.git] / src / armnn / backends / RefWorkloads / Softmax.cpp

diff --git a/src/armnn/backends/RefWorkloads/Softmax.cpp b/src/armnn/backends/RefWorkloads/Softmax.cpp
index 58840e3..c9f0bc5 100644 (file)
--- a/src/armnn/backends/RefWorkloads/Softmax.cpp
+++ b/src/armnn/backends/RefWorkloads/Softmax.cpp
@@ -11,13 +11,13 @@
 namespace armnn
 {
 
-/// Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo
+/// Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo.
 void Softmax(const float* in, float* out, const TensorInfo& tensorInfo, float beta)
 {
     unsigned int numChannels = tensorInfo.GetShape()[1];
     for (unsigned int n = 0; n < tensorInfo.GetShape()[0]; n++)
     {
-        // find maximum channel
+        // Find maximum channel.
         float max = in[n * numChannels];
         for (unsigned int c = 1; c < numChannels; c++)
         {
@@ -28,7 +28,7 @@ void Softmax(const float* in, float* out, const TensorInfo& tensorInfo, float be
             }
         }
 
-        // exponentiate all values and sum
+        // Exponentiate all values and sum.
         std::vector<float> exponentials(numChannels);
         float              sum = 0.0f;
         for (unsigned int c = 0; c < numChannels; c++)
@@ -38,7 +38,7 @@ void Softmax(const float* in, float* out, const TensorInfo& tensorInfo, float be
             sum += exponentials[c];
         }
 
-        // divide exponentials by sum to give outputs
+        // Divide exponentials by sum to give outputs.
         for (unsigned int c = 0; c < numChannels; c++)
         {
             out[n * numChannels + c] = exponentials[c] / sum;