diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
index cf7e078..6896a97 100644
--- a/arm_compute/runtime/CL/functions/CLLSTMLayer.h
+++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
@@ -188,55 +188,62 @@
     CLLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Initialize function's tensors.
      *
-     * @param[in]      input                       Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
-     * @param[in]      input_to_forget_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      input_to_cell_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      input_to_output_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      recurrent_to_cell_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in]      forget_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in]      cell_bias                   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in]      output_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in, out] output_state                2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
-     * @param[in, out] cell_state                  2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
-     * @param[out]     scratch_buffer              2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
-     * @param[out]     output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
-     *                                             Data types supported: Same as @p input.
-     * @param[in]      lstm_params                 (Optional) Weights tensors used in peephole optimization:
-     *                                             input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     *                                             recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                             cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
-     *                                             cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                             cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                             input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
-     *                                             projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                             projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
-     * @param[in]      activation_info             Contains activation information described in @ref ActivationLayerInfo.
-     * @param[in]      cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
-     * @param[in]      projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in]  input                       Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
+     * @param[in]  input_to_forget_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  input_to_cell_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  input_to_output_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  recurrent_to_cell_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in]  forget_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]  cell_bias                   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]  output_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]  output_state_in             2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in]  cell_state_in               2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[out] scratch_buffer              2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
+     * @param[out] output_state_out            2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[out] cell_state_out              2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[out] output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
+     *                                         Data types supported: Same as @p input.
+     * @param[in]  lstm_params                 (Optional) Weights tensors used in peephole optimization:
+     *                                         input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     *                                         recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                         cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
+     *                                         cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
+     *                                         projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                         projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     * @param[in]  activation_info             Contains activation information described in @ref ActivationLayerInfo.
+     * @param[in]  cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in]  projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
      */
-    void configure(const ICLTensor *input, const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
+    void configure(const ICLTensor *input,
+                   const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
                    const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights,
-                   const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, ICLTensor *output_state, ICLTensor *cell_state, ICLTensor *scratch_buffer, ICLTensor *output,
+                   const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias,
+                   const ICLTensor *output_state_in, const ICLTensor *cell_state_in,
+                   ICLTensor *scratch_buffer, ICLTensor *output_state_out, ICLTensor *cell_state_out, ICLTensor *output,
                    const LSTMParams<ICLTensor> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer
      *
-     * @param[in] input                       Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: F16/F32.
-     * @param[in] input_to_forget_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] input_to_cell_weights       2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] input_to_output_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_cell_weights   2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] forget_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] cell_bias                   1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] output_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] output_state                2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
-     * @param[in] cell_state                  2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
-     * @param[in] scratch_buffer              2D tensor info with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
-     * @param[in] output                      Destination tensor info. Output is a 2D tensor with dimensions [output_size, batch_size].
+     * @param[in] input                       Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
+     * @param[in] input_to_forget_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_cell_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_output_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_cell_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] forget_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] cell_bias                   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_state_in             2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_in               2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] scratch_buffer              2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
+     * @param[in] output_state_out            2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_out              2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
      *                                        Data types supported: Same as @p input.
      * @param[in] lstm_params                 (Optional) Weights tensors used in peephole optimization:
      *                                        input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
@@ -253,10 +260,12 @@
      *
      * @return a status
      */
-    static Status validate(const ITensorInfo *input, const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights,
+    static Status validate(const ITensorInfo *input,
+                           const ITensorInfo *input_to_forget_weights, const ITensorInfo *input_to_cell_weights, const ITensorInfo *input_to_output_weights,
                            const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights,
                            const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias,
-                           const ITensorInfo *output_state, const ITensorInfo *cell_state, const ITensorInfo *scratch_buffer, const ITensorInfo *output,
+                           const ITensorInfo *output_state_in, const ITensorInfo *cell_state_in,
+                           const ITensorInfo *scratch_buffer, const ITensorInfo *output_state_out, const ITensorInfo *cell_state_out, const ITensorInfo *output,
                            const LSTMParams<ITensorInfo> &lstm_params, const ActivationLayerInfo &activation_info, float cell_threshold = 0.f, float projection_threshold = 0.f);
 
     // Inherited methods overridden:
@@ -326,7 +335,7 @@
     CLTensor                        _output4;
     CLTensor                        _output5;
     CLTensor                        _cell_state_activation;
-    CLTensor                        _output_projection1;
+    CLTensor                        _output_state1;
     CLTensor                        _ones;
     bool                            _run_peephole_opt;
     bool                            _run_cifg_opt;