diff options
Diffstat (limited to 'src/backends/reference/workloads/RefNormalizationWorkload.cpp')
| -rw-r--r-- | src/backends/reference/workloads/RefNormalizationWorkload.cpp | 25 |
1 files changed, 12 insertions, 13 deletions
diff --git a/src/backends/reference/workloads/RefNormalizationWorkload.cpp b/src/backends/reference/workloads/RefNormalizationWorkload.cpp index a41f68349a..d5d2104cba 100644 --- a/src/backends/reference/workloads/RefNormalizationWorkload.cpp +++ b/src/backends/reference/workloads/RefNormalizationWorkload.cpp @@ -8,11 +8,10 @@ #include <armnn/Logging.hpp> #include <armnn/Tensor.hpp> #include <armnnUtils/DataLayoutIndexed.hpp> +#include <armnn/utility/NumericCast.hpp> #include <Profiling.hpp> -#include <boost/numeric/conversion/cast.hpp> - #include "RefWorkloadUtils.hpp" #include "Decoders.hpp" #include "Encoders.hpp" @@ -37,7 +36,7 @@ void NormalizeWithinUingLbr(Decoder<float>& inputData, const unsigned int rows = tensorShape[2]; const unsigned int cols = tensorShape[3]; - int radius = boost::numeric_cast<int>(norm_size / 2u); /* Strong Assumption on rounding Mode */ + int radius = armnn::numeric_cast<int>(norm_size / 2u); /* Strong Assumption on rounding Mode */ for (unsigned int n = 0; n < batchSize; n++) { @@ -52,23 +51,23 @@ void NormalizeWithinUingLbr(Decoder<float>& inputData, { for (int x = -radius; x <= radius; x++) { - int i = boost::numeric_cast<int>(w) + x; - int j = boost::numeric_cast<int>(h) + y; + int i = armnn::numeric_cast<int>(w) + x; + int j = armnn::numeric_cast<int>(h) + y; - if ((i < 0) || (i >= boost::numeric_cast<int>(cols))) + if ((i < 0) || (i >= armnn::numeric_cast<int>(cols))) { continue; } - if ((j < 0) || (j >= boost::numeric_cast<int>(rows))) + if ((j < 0) || (j >= armnn::numeric_cast<int>(rows))) { continue; } unsigned int inputIndex = n * cols * rows * depth + c * cols * rows + - boost::numeric_cast<unsigned int>(j) * cols + - boost::numeric_cast<unsigned int>(i); + armnn::numeric_cast<unsigned int>(j) * cols + + armnn::numeric_cast<unsigned int>(i); inputData[inputIndex]; float inval = inputData.Get(); @@ -106,7 +105,7 @@ void NormalizeAcrossUingLbr(Decoder<float>& inputData, const unsigned int rows = tensorShape[dataLayoutIndexed.GetHeightIndex()]; const unsigned int cols = tensorShape[dataLayoutIndexed.GetWidthIndex()]; - int radius = boost::numeric_cast<int>(norm_size / 2u); /* Strong Assumption on rounding Mode */ + int radius = armnn::numeric_cast<int>(norm_size / 2u); /* Strong Assumption on rounding Mode */ for (unsigned int n = 0; n < batchSize; n++) { @@ -119,16 +118,16 @@ void NormalizeAcrossUingLbr(Decoder<float>& inputData, float accumulated_scale = 0.0; for (int z = -radius; z <= radius; z++) { - int k = boost::numeric_cast<int>(c) + z; + int k = armnn::numeric_cast<int>(c) + z; - if ((k < 0) || (k >= boost::numeric_cast<int>(depth))) + if ((k < 0) || (k >= armnn::numeric_cast<int>(depth))) { continue; } unsigned inputIndex = dataLayoutIndexed.GetIndex(tensorShape, n, - boost::numeric_cast<unsigned int>(k), + armnn::numeric_cast<unsigned int>(k), h, w); |