1 files changed, 51 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index c8c4f9aae4..52d14097af 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -2642,4 +2642,55 @@ void SliceQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     }
 }
 
+void DepthToSpaceQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
+{
+    const std::string descriptorName{"DepthToSpaceQueueDescriptor"};
+
+    ValidateNumInputs(workloadInfo,  descriptorName, 1);
+    ValidateNumOutputs(workloadInfo, descriptorName, 1);
+
+    const TensorInfo& inputInfo  = workloadInfo.m_InputTensorInfos[0];
+    const TensorInfo& outputInfo = workloadInfo.m_OutputTensorInfos[0];
+
+    ValidateTensorNumDimensions(inputInfo,  descriptorName, 4, "input");
+    ValidateTensorNumDimensions(outputInfo, descriptorName, 4, "output");
+
+    std::vector<DataType> supportedTypes =
+    {
+        DataType::Float32,
+        DataType::Float16,
+        DataType::QuantisedAsymm8,
+        DataType::QuantisedSymm16
+    };
+
+    ValidateDataTypes(inputInfo,  supportedTypes, descriptorName);
+    ValidateDataTypes(outputInfo, supportedTypes, descriptorName);
+
+    ValidateTensorNumElementsMatch(inputInfo, outputInfo, descriptorName, "input", "output");
+
+    if (m_Parameters.m_BlockSize == 0)
+    {
+        throw InvalidArgumentException(descriptorName + ": Block size cannot be 0.");
+    }
+
+    DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout);
+    const unsigned int wIndex = dimensionIndices.GetWidthIndex();
+    const unsigned int hIndex = dimensionIndices.GetHeightIndex();
+    const unsigned int cIndex = dimensionIndices.GetChannelsIndex();
+
+    const TensorShape& outputShape = outputInfo.GetShape();
+    if (outputShape[hIndex] % m_Parameters.m_BlockSize != 0 || outputShape[wIndex]  % m_Parameters.m_BlockSize != 0)
+    {
+        throw InvalidArgumentException(descriptorName + ": Output width and height shape"
+                                       "must be divisible by block size.");
+    }
+
+    const TensorShape& inputShape = inputInfo.GetShape();
+    if (inputShape[cIndex] % (m_Parameters.m_BlockSize * m_Parameters.m_BlockSize) != 0)
+    {
+        throw InvalidArgumentException(descriptorName + ": The depth of the input tensor"
+                                       "must be divisible by the square of block size." );
+    }
+}
+
 } // namespace armnn