1 files changed, 86 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/InstanceNorm.cpp b/src/backends/reference/workloads/InstanceNorm.cpp
new file mode 100644
index 0000000000..9d6532fa6e
--- /dev/null
+++ b/src/backends/reference/workloads/InstanceNorm.cpp
@@ -0,0 +1,86 @@
+//
+// Copyright © 2019 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "InstanceNorm.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include <armnn/Tensor.hpp>
+
+#include <DataLayoutIndexed.hpp>
+
+#include <cmath>
+
+namespace armnn
+{
+
+void InstanceNorm(const InstanceNormalizationQueueDescriptor& data,
+                  Decoder<float>& inputDecoder,
+                  Encoder<float>& outputEncoder)
+{
+    const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[0]);
+    const TensorShape inputShape = inputInfo.GetShape();
+
+    armnnUtils::DataLayoutIndexed dataLayout(data.m_Parameters.m_DataLayout);
+
+    unsigned int inputBatches  = inputShape[0];
+    unsigned int inputHeight   = inputShape[dataLayout.GetHeightIndex()];
+    unsigned int inputWidth    = inputShape[dataLayout.GetWidthIndex()];
+    unsigned int inputChannels = inputShape[dataLayout.GetChannelsIndex()];
+
+    float beta  = data.m_Parameters.m_Beta;
+    float eps   = data.m_Parameters.m_Eps;
+    float gamma = data.m_Parameters.m_Gamma;
+
+    for (unsigned int n = 0; n < inputBatches; ++n)
+    {
+        for (unsigned int c = 0; c < inputChannels; ++c)
+        {
+            float mean = 0, var = 0;
+
+            //Calculate Mean
+            for (unsigned int h = 0; h < inputHeight; h++)
+            {
+                for (unsigned int w = 0; w < inputWidth; w++)
+                {
+                    unsigned int index = dataLayout.GetIndex(inputShape, n, c, h, w);
+
+                    inputDecoder[index];
+                    float value = inputDecoder.Get();
+                    mean += value;
+                }
+            }
+            mean /= static_cast<float>(inputHeight * inputWidth);
+
+            //Calculate Variance
+            for (unsigned int h = 0; h < inputHeight; h++)
+            {
+                for (unsigned int w = 0; w < inputWidth; w++)
+                {
+                    unsigned int index = dataLayout.GetIndex(inputShape, n, c, h, w);
+
+                    inputDecoder[index];
+                    float value = inputDecoder.Get();
+                    var += (value - mean) * (value - mean);
+                }
+            }
+            var /= static_cast<float>(inputHeight * inputWidth);
+
+            // Apply Instance Normalisation
+            for (unsigned int h = 0; h < inputHeight; ++h)
+            {
+                for (unsigned int w = 0; w < inputWidth; ++w)
+                {
+                    unsigned int index = dataLayout.GetIndex(inputShape, n, c, h, w);
+                    inputDecoder[index];
+                    outputEncoder[index];
+                    outputEncoder.Set((inputDecoder.Get() - mean) * gamma /  std::sqrt ( var + eps) + beta);
+                }
+
+            }
+        }
+    }
+}
+
+} // namespace armnn