COMPMID-3280: Make all ML primitives for CL use the new interface - Part 2

- CLFunctions have been updated

Change-Id: Ie3256a6c775bc12f3126482bd8e8a46da54b267c
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3053
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 46 insertions, 0 deletions

diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
index a94f239472..a29513aaae 100644
--- a/arm_compute/runtime/CL/functions/CLLSTMLayer.h
+++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
@@ -102,6 +102,52 @@ public:
                    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);
+    /** Initialize function's tensors.
+     *
+     * @param[in]  compile_context             The compile context to be used.
+     * @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                 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.
+     *                                         input_layer_norm_weights   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         forget_layer_norm_weights  1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         cell_layer_norm_weights    1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         output_layer_norm_weights  1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in]  activation_info             Contains activation information described in @ref ActivationLayerInfo.
+     * @param[in]  cell_threshold              (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip].
+     *                                         If set to 0.0f then clipping is disabled.
+     * @param[in]  projection_threshold        (Optional) The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
+     *                                         If set to 0.0f then clipping is disabled.
+     */
+    void configure(const CLCompileContext &compile_context, 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,
+                   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
      *