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diff --git a/src/armnn/layers/QuantizedLstmLayer.hpp b/src/armnn/layers/QuantizedLstmLayer.hpp
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+++ b/src/armnn/layers/QuantizedLstmLayer.hpp
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+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <Layer.hpp>
+
+namespace armnn
+{
+
+class ScopedCpuTensorHandle;
+
+struct QuantizedLstmParameters
+{
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_InputToInputWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_InputToForgetWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_InputToCellWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_InputToOutputWeights;
+
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToInputWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToForgetWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToCellWeights;
+    /// A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
+    std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToOutputWeights;
+
+    /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
+    std::unique_ptr<ScopedCpuTensorHandle> m_InputGateBias;
+    /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
+    std::unique_ptr<ScopedCpuTensorHandle> m_ForgetGateBias;
+    /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
+    std::unique_ptr<ScopedCpuTensorHandle> m_CellBias;
+    /// A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
+    std::unique_ptr<ScopedCpuTensorHandle> m_OutputGateBias;
+};
+
+/// This layer represents a QuantizedLstm operation.
+class QuantizedLstmLayer : public Layer
+{
+public:
+
+    QuantizedLstmParameters m_QuantizedLstmParameters;
+
+    /// Makes a workload for the QuantizedLstm type.
+    /// @param [in] graph The graph where this layer can be found.
+    /// @param [in] factory The workload factory which will create the workload.
+    /// @return A pointer to the created workload, or nullptr if not created.
+    virtual std::unique_ptr<IWorkload> CreateWorkload(const Graph&            graph,
+                                                      const IWorkloadFactory& factory) const override;
+
+    /// Creates a dynamically-allocated copy of this layer.
+    /// @param [in] graph The graph into which this layer is being cloned.
+    QuantizedLstmLayer* Clone(Graph& graph) const override;
+
+    /// Check if the input tensor shape(s)
+    /// will lead to a valid configuration of @ref QuantizedLstmLayer.
+    void ValidateTensorShapesFromInputs() override;
+
+    /// By default returns inputShapes if the number of inputs are equal to number of outputs,
+    /// otherwise infers the output shapes from given input shapes and layer properties.
+    /// @param [in] inputShapes The input shapes layer has.
+    /// @return A vector to the inferred output shape.
+    std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override;
+
+    void Accept(ILayerVisitor& visitor) const override;
+
+protected:
+    /// Constructor to create a QuantizedLstmLayer.
+    /// @param [in] name Optional name for the layer.
+    QuantizedLstmLayer(const char* name);
+
+    /// Default destructor
+    ~QuantizedLstmLayer() = default;
+
+    /// Retrieve the handles to the constant values stored by the layer.
+    /// @return A vector of the constant tensors stored by this layer.
+    Layer::ConstantTensors GetConstantTensorsByRef() override;
+};
+
+} // namespace armnn