friend void swap(ViewsDescriptor& first, ViewsDescriptor& second);
private:
OriginsDescriptor m_Origins;
- uint32_t** m_ViewSizes;
+ uint32_t** m_ViewSizes;
};
/// Convenience template to create an OriginsDescriptor to use when creating a Merger layer for performing concatenation
ResizeBilinearDescriptor()
: m_TargetWidth(0)
, m_TargetHeight(0)
+ , m_DataLayout(DataLayout::NCHW)
{}
- uint32_t m_TargetWidth;
- uint32_t m_TargetHeight;
+ uint32_t m_TargetWidth;
+ uint32_t m_TargetHeight;
+ DataLayout m_DataLayout;
};
struct ReshapeDescriptor
}
{
- const unsigned int inputChannelCount = workloadInfo.m_InputTensorInfos[0].GetShape()[1];
- const unsigned int outputChannelCount = workloadInfo.m_OutputTensorInfos[0].GetShape()[1];
+ // DataLayout is NCHW by default (channelsIndex = 1)
+ const unsigned int channelsIndex = this->m_Parameters.m_DataLayout == armnn::DataLayout::NHWC ? 3 : 1;
+
+ const unsigned int inputChannelCount = workloadInfo.m_InputTensorInfos[0].GetShape()[channelsIndex];
+ const unsigned int outputChannelCount = workloadInfo.m_OutputTensorInfos[0].GetShape()[channelsIndex];
if (inputChannelCount != outputChannelCount)
{
throw InvalidArgumentException(
#include <backends/CpuTensorHandle.hpp>
#include <backends/cl/ClLayerSupport.hpp>
#include <backends/aclCommon/ArmComputeUtils.hpp>
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
#include "ClWorkloadUtils.hpp"
+using namespace armnn::armcomputetensorutils;
+
namespace armnn
{
ClResizeBilinearFloatWorkload::ClResizeBilinearFloatWorkload(const ResizeBilinearQueueDescriptor& descriptor,
- const WorkloadInfo& info)
+ const WorkloadInfo& info)
: FloatWorkload<ResizeBilinearQueueDescriptor>(descriptor, info)
{
m_Data.ValidateInputsOutputs("ClResizeBilinearFloatWorkload", 1, 1);
arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+ (&input)->info()->set_data_layout(ConvertDataLayout(m_Data.m_Parameters.m_DataLayout));
+ (&output)->info()->set_data_layout(ConvertDataLayout(m_Data.m_Parameters.m_DataLayout));
+
m_ResizeBilinearLayer.configure(&input, &output, arm_compute::InterpolationPolicy::BILINEAR,
arm_compute::BorderMode::REPLICATE, arm_compute::PixelValue(0.f),
arm_compute::SamplingPolicy::TOP_LEFT);