diff options
Diffstat (limited to 'src/backends/cl/workloads')
8 files changed, 33 insertions, 25 deletions
diff --git a/src/backends/cl/workloads/ClArgMinMaxWorkload.cpp b/src/backends/cl/workloads/ClArgMinMaxWorkload.cpp index a79a7b286d..5910080859 100644 --- a/src/backends/cl/workloads/ClArgMinMaxWorkload.cpp +++ b/src/backends/cl/workloads/ClArgMinMaxWorkload.cpp @@ -11,6 +11,7 @@ #include <backendsCommon/CpuTensorHandle.hpp> #include <armnnUtils/TensorUtils.hpp> +#include <armnn/utility/NumericCast.hpp> #include <cl/ClTensorHandle.hpp> #include <cl/ClLayerSupport.hpp> @@ -36,7 +37,7 @@ arm_compute::Status ClArgMinMaxWorkloadValidate(const TensorInfo& input, auto numDims = input.GetNumDimensions(); auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, descriptor.m_Axis); - int aclAxis = boost::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis)); + int aclAxis = armnn::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis)); if (descriptor.m_Function == ArgMinMaxFunction::Max) { @@ -60,7 +61,7 @@ ClArgMinMaxWorkload::ClArgMinMaxWorkload(const ArgMinMaxQueueDescriptor& descrip auto numDims = info.m_InputTensorInfos[0].GetNumDimensions(); auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, m_Data.m_Parameters.m_Axis); - int aclAxis = boost::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis)); + int aclAxis = armnn::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis)); if (m_Data.m_Parameters.m_Function == ArgMinMaxFunction::Max) { diff --git a/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp b/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp index a714e031e4..1a7a8dca81 100644 --- a/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp +++ b/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp @@ -9,6 +9,8 @@ #include <backendsCommon/CpuTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/NumericCast.hpp> + #include "ClWorkloadUtils.hpp" namespace armnn @@ -27,8 +29,8 @@ ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDesc input.info()->set_data_layout(aclDataLayout); // ArmNN blockShape is [H, W] Cl asks for W, H - int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[0]); - int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[1]); + int32_t blockHeight = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[0]); + int32_t blockWidth = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[1]); arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); output.info()->set_data_layout(aclDataLayout); @@ -49,8 +51,8 @@ arm_compute::Status ClBatchToSpaceNdWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, dataLayout); // ArmNN blockShape is [H, W] Cl asks for W, H - int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_BlockShape[0]); - int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_BlockShape[1]); + int32_t blockHeight = armnn::numeric_cast<int32_t>(desc.m_BlockShape[0]); + int32_t blockWidth = armnn::numeric_cast<int32_t>(desc.m_BlockShape[1]); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, dataLayout); diff --git a/src/backends/cl/workloads/ClDepthToSpaceWorkload.cpp b/src/backends/cl/workloads/ClDepthToSpaceWorkload.cpp index 04885b18aa..43c81dc209 100644 --- a/src/backends/cl/workloads/ClDepthToSpaceWorkload.cpp +++ b/src/backends/cl/workloads/ClDepthToSpaceWorkload.cpp @@ -8,12 +8,12 @@ #include "ClWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> + +#include <armnn/utility/NumericCast.hpp> #include <armnn/utility/PolymorphicDowncast.hpp> #include <cl/ClTensorHandle.hpp> -#include <boost/numeric/conversion/cast.hpp> - namespace armnn { @@ -26,7 +26,7 @@ arm_compute::Status ClDepthToSpaceWorkloadValidate(const TensorInfo& input, DataLayout dataLayout = desc.m_DataLayout; const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, dataLayout); - int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_BlockSize); + int32_t blockSize = armnn::numeric_cast<int32_t>(desc.m_BlockSize); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, dataLayout); @@ -48,7 +48,7 @@ ClDepthToSpaceWorkload::ClDepthToSpaceWorkload(const DepthToSpaceQueueDescriptor PolymorphicPointerDowncast<IClTensorHandle>(m_Data.m_Inputs[0])->GetTensor(); input.info()->set_data_layout(aclDataLayout); - int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); + int32_t blockSize = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); arm_compute::ICLTensor& output = PolymorphicPointerDowncast<IClTensorHandle>(m_Data.m_Outputs[0])->GetTensor(); diff --git a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp index 9d06428902..fe9b45e054 100644 --- a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp +++ b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp @@ -9,6 +9,8 @@ #include <cl/ClLayerSupport.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/NumericCast.hpp> + #include <arm_compute/runtime/CL/functions/CLLSTMLayer.h> #include "ClWorkloadUtils.hpp" @@ -132,8 +134,8 @@ ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor &descriptor, // Get the batch_size and the num_units from the cellStateIn dimensions const TensorInfo& inputTensorInfo = info.m_InputTensorInfos[2]; - const unsigned int batch_size = boost::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[0]); - const unsigned int num_units = boost::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[1]); + const unsigned int batch_size = armnn::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[0]); + const unsigned int num_units = armnn::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[1]); m_ScratchBuffer = std::make_unique<arm_compute::CLTensor>(); if (m_Data.m_Parameters.m_CifgEnabled) diff --git a/src/backends/cl/workloads/ClSpaceToBatchNdWorkload.cpp b/src/backends/cl/workloads/ClSpaceToBatchNdWorkload.cpp index b87658b3f9..443c56b7b5 100644 --- a/src/backends/cl/workloads/ClSpaceToBatchNdWorkload.cpp +++ b/src/backends/cl/workloads/ClSpaceToBatchNdWorkload.cpp @@ -9,6 +9,7 @@ #include <aclCommon/ArmComputeUtils.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/NumericCast.hpp> #include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <cl/ClLayerSupport.hpp> @@ -27,8 +28,8 @@ arm_compute::Status ClSpaceToBatchNdWorkloadValidate(const TensorInfo& input, const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); // ArmNN blockShape is [H, W] Cl asks for W, H - int32_t blockHeight = boost::numeric_cast<int32_t>(descriptor.m_BlockShape[0]); - int32_t blockWidth = boost::numeric_cast<int32_t>(descriptor.m_BlockShape[1]); + int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[0]); + int32_t blockWidth = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[1]); arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D( descriptor.m_PadList[1].first, descriptor.m_PadList[0].first); @@ -55,8 +56,8 @@ ClSpaceToBatchNdWorkload::ClSpaceToBatchNdWorkload( armnn::PolymorphicPointerDowncast<IClTensorHandle>(m_Data.m_Outputs[0])->GetTensor(); // ArmNN blockShape is [H, W] Cl asks for W, H - int32_t blockHeight = boost::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[0]); - int32_t blockWidth = boost::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[1]); + int32_t blockHeight = armnn::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[0]); + int32_t blockWidth = armnn::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[1]); arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D( m_Data.m_Parameters.m_PadList[1].first, m_Data.m_Parameters.m_PadList[0].first); diff --git a/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp b/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp index 1acb5c64e6..f35fe0e3c9 100644 --- a/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp +++ b/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp @@ -11,6 +11,8 @@ #include <backendsCommon/CpuTensorHandle.hpp> #include <cl/ClTensorHandle.hpp> +#include <armnn/utility/NumericCast.hpp> + namespace armnn { using namespace armcomputetensorutils; @@ -26,7 +28,7 @@ ClSpaceToDepthWorkload::ClSpaceToDepthWorkload(const SpaceToDepthQueueDescriptor arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); input.info()->set_data_layout(aclDataLayout); - int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); + int32_t blockSize = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); output.info()->set_data_layout(aclDataLayout); @@ -47,7 +49,7 @@ arm_compute::Status ClSpaceToDepthWorkloadValidate(const TensorInfo& input, DataLayout dataLayout = desc.m_DataLayout; const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, dataLayout); - int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_BlockSize); + int32_t blockSize = armnn::numeric_cast<int32_t>(desc.m_BlockSize); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, dataLayout); diff --git a/src/backends/cl/workloads/ClStackWorkload.cpp b/src/backends/cl/workloads/ClStackWorkload.cpp index e434f9897f..c0b88b1193 100644 --- a/src/backends/cl/workloads/ClStackWorkload.cpp +++ b/src/backends/cl/workloads/ClStackWorkload.cpp @@ -5,6 +5,7 @@ #include "ClStackWorkload.hpp" #include "ClWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/NumericCast.hpp> #include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <cl/ClTensorHandle.hpp> @@ -12,8 +13,6 @@ #include <arm_compute/core/Types.h> -#include <boost/numeric/conversion/cast.hpp> - namespace armnn { using namespace armcomputetensorutils; @@ -22,8 +21,8 @@ namespace { int CalcAxis(const unsigned int axis, const unsigned int inputDimensions) { - const int intAxis = boost::numeric_cast<int>(axis); - return boost::numeric_cast<int>(inputDimensions) - intAxis; + const int intAxis = armnn::numeric_cast<int>(axis); + return armnn::numeric_cast<int>(inputDimensions) - intAxis; } } //namespace diff --git a/src/backends/cl/workloads/ClStridedSliceWorkload.cpp b/src/backends/cl/workloads/ClStridedSliceWorkload.cpp index 6b0a34d90e..b094a910f4 100644 --- a/src/backends/cl/workloads/ClStridedSliceWorkload.cpp +++ b/src/backends/cl/workloads/ClStridedSliceWorkload.cpp @@ -13,7 +13,8 @@ #include <backendsCommon/CpuTensorHandle.hpp> #include <backendsCommon/WorkloadUtils.hpp> -#include <boost/numeric/conversion/cast.hpp> +#include <armnn/utility/NumericCast.hpp> + #include <cl/ClLayerSupport.hpp> #include <cl/ClTensorHandle.hpp> #include <cl/ClLayerSupport.hpp> @@ -36,7 +37,7 @@ arm_compute::Status ClStridedSliceWorkloadValidate(const TensorInfo& input, std::tie(starts, ends, strides) = SetClStridedSliceData(descriptor.m_Begin, descriptor.m_End, descriptor.m_Stride); - auto numDimensions = boost::numeric_cast<int>(input.GetNumDimensions()); + auto numDimensions = armnn::numeric_cast<int>(input.GetNumDimensions()); int32_t begin_mask = ConvertMaskToACLFormat(descriptor.m_BeginMask, numDimensions); int32_t end_mask = ConvertMaskToACLFormat(descriptor.m_EndMask, numDimensions); int32_t shrink_axis_mask = ConvertMaskToACLFormat(descriptor.m_ShrinkAxisMask, numDimensions); @@ -68,7 +69,7 @@ ClStridedSliceWorkload::ClStridedSliceWorkload(const StridedSliceQueueDescriptor m_Data.m_Parameters.m_End, m_Data.m_Parameters.m_Stride); - auto numDimensions = boost::numeric_cast<int>(info.m_InputTensorInfos[0].GetNumDimensions()); + auto numDimensions = armnn::numeric_cast<int>(info.m_InputTensorInfos[0].GetNumDimensions()); int32_t begin_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_BeginMask, numDimensions); int32_t end_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_EndMask, numDimensions); int32_t shrink_axis_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_ShrinkAxisMask, numDimensions); |