1 files changed, 100 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/BatchToSpaceNd.cpp b/src/backends/reference/workloads/BatchToSpaceNd.cpp
new file mode 100644
index 0000000000..bedf8418ef
--- /dev/null
+++ b/src/backends/reference/workloads/BatchToSpaceNd.cpp
@@ -0,0 +1,100 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "BatchToSpaceNd.hpp"
+
+#include "RefWorkloadUtils.hpp"
+
+#include <armnn/Types.hpp>
+
+#include <boost/assert.hpp>
+
+namespace armnn
+{
+
+inline unsigned int Offset(const TensorShape& shape, unsigned int batch, unsigned int height, unsigned int width,
+        unsigned int channels, const DataLayoutIndexed& dataLayout)
+{
+    if (dataLayout.GetDataLayout() == DataLayout::NHWC)
+    {
+        return ((batch * shape[dataLayout.GetHeightIndex()] + height) * shape[dataLayout.GetWidthIndex()] + width) *
+               shape[dataLayout.GetChannelsIndex()] + channels;
+    }
+    else
+    {
+        return ((batch * shape[dataLayout.GetChannelsIndex()] + channels) *
+               shape[dataLayout.GetHeightIndex()] + height) *
+               shape[dataLayout.GetWidthIndex()] + width;
+    }
+}
+
+void BatchToSpaceNd(const DataLayoutIndexed& dataLayout,
+                    const TensorInfo& inputTensorInfo,
+                    const TensorInfo& outputTensorInfo,
+                    const std::vector<unsigned int>& blockShape,
+                    const std::vector<std::vector<unsigned int>>& cropsData,
+                    const float* inputData,
+                    float* outputData)
+{
+    TensorShape inputShape = inputTensorInfo.GetShape();
+    unsigned int inputNumDims = inputShape.GetNumDimensions();
+    if (inputNumDims != 4)
+    {
+        throw armnn::InvalidArgumentException("Expected Input with 4 Dimensions");
+    }
+
+    TensorShape outputShape = outputTensorInfo.GetShape();
+    unsigned int outputNumDims = outputShape.GetNumDimensions();
+    if (outputNumDims != 4)
+    {
+        throw armnn::InvalidArgumentException("Expected Output with 4 Dimensions");
+    }
+
+    const unsigned int inputBatchSize = inputShape[0];
+    const unsigned int channels = inputShape[dataLayout.GetChannelsIndex()];
+
+    const unsigned int outputBatchSize = outputShape[0];
+    const unsigned int outputHeight = outputShape[dataLayout.GetHeightIndex()];
+    const unsigned int outputWidth = outputShape[dataLayout.GetWidthIndex()];
+
+    const unsigned int blockShapeHeight = blockShape[0];
+    const unsigned int blockShapeWidth = blockShape[1];
+
+    const unsigned int cropsTop = cropsData[0][0];
+    const unsigned int cropsLeft = cropsData[1][0];
+
+    for (unsigned int inBatch = 0; inBatch < inputBatchSize; ++inBatch)
+    {
+        const unsigned int outBatch = inBatch % outputBatchSize;
+        const unsigned int spatialOffset = inBatch / outputBatchSize;
+
+        for (unsigned int inH = 0; inH < inputTensorInfo.GetShape()[dataLayout.GetHeightIndex()]; ++inH) {
+            const unsigned int outH = inH * blockShapeHeight + spatialOffset / blockShapeWidth - cropsTop;
+
+            if (outH >= outputHeight)
+            {
+                continue;
+            }
+
+            for (unsigned int inW = 0; inW < inputTensorInfo.GetShape()[dataLayout.GetWidthIndex()]; ++inW) {
+                const unsigned int outW = inW * blockShapeWidth + spatialOffset % blockShapeWidth - cropsLeft;
+
+                if (outW >= outputWidth)
+                {
+                    continue;
+                }
+
+                for (unsigned int c = 0; c < channels; c++)
+                {
+                    unsigned int outOffset = Offset(outputShape, outBatch, outH, outW, c, dataLayout);
+                    unsigned int inOffset = Offset(inputShape, inBatch, inH, inW, c, dataLayout);
+                    outputData[outOffset] = inputData[inOffset];
+                }
+            }
+        }
+    }
+}
+
+} //namespace armnn