1 files changed, 49 insertions, 0 deletions
diff --git a/src/armnn/backends/RefWorkloads/Softmax.cpp b/src/armnn/backends/RefWorkloads/Softmax.cpp
new file mode 100644
index 0000000000..58840e3076
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/Softmax.cpp
@@ -0,0 +1,49 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+
+#include "Softmax.hpp"
+
+#include <cmath>
+#include <vector>
+
+namespace armnn
+{
+
+/// 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
+        float max = in[n * numChannels];
+        for (unsigned int c = 1; c < numChannels; c++)
+        {
+            float val = in[n * numChannels + c];
+            if (val > max)
+            {
+                max = val;
+            }
+        }
+
+        // exponentiate all values and sum
+        std::vector<float> exponentials(numChannels);
+        float              sum = 0.0f;
+        for (unsigned int c = 0; c < numChannels; c++)
+        {
+            float val       = in[n * numChannels + c];
+            exponentials[c] = expf((val - max) * beta);
+            sum += exponentials[c];
+        }
+
+        // divide exponentials by sum to give outputs
+        for (unsigned int c = 0; c < numChannels; c++)
+        {
+            out[n * numChannels + c] = exponentials[c] / sum;
+        }
+    }
+}
+
+} //namespace armnn