diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp
index 722b778..6c6c2df 100644
--- a/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp
+++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp
@@ -20,12 +20,12 @@
     const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
 
     m_KernelTensor = std::make_unique<arm_compute::Tensor>();
-    BuildArmComputeTensor(*m_KernelTensor, weightInfo, descriptor.m_DataLayout);
+    BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
 
     if (m_Data.m_Parameters.m_BiasEnabled)
     {
         m_BiasTensor = std::make_unique<arm_compute::Tensor>();
-        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), descriptor.m_DataLayout);
+        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
     }
 
     arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
@@ -41,6 +41,10 @@
     arm_compute::ITensor& input  = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
     arm_compute::ITensor& output = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
 
+    arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
+    input.info()->set_data_layout(aclDataLayout);
+    output.info()->set_data_layout(aclDataLayout);
+
     bool use3x3Optimisation = weightInfo.GetShape()[3] == 3 && weightInfo.GetShape()[2] == 3;
     if (use3x3Optimisation)
     {