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, 48 insertions, 3 deletions

diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
index 4952029c9d..6d1181eefe 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
@@ -62,6 +62,16 @@ public:
      * @param[in]  num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
      */
     void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  weights         Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
+     *                             Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32.
+     * @param[in]  biases          Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
+     * @param[out] output          Destination tensor. Data types supported: Same as @p weights.
+     * @param[in]  num_groups      (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
+     */
+    void configure(const CLCompileContext &compile_context, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayerReshapeWeights
      *
      * @param[in] weights    Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
@@ -94,9 +104,20 @@ public:
      */
     void configure(const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups)
     {
+        configure(CLKernelLibrary::get().get_compile_context(), input, biases, num_groups);
+    }
+    /** Configures the @ref CLConvolutionLayerReshapeWeights function
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] input           Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[in] biases          Biases tensor. Data type supported: Same as @p input.
+     * @param[in] num_groups      Number of groups when performing a grouped convolution.
+     */
+    void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups)
+    {
         _bias_bit   = (biases != nullptr) ? 1 : 0;
         _num_groups = num_groups;
-        _func.configure(input, biases, &_output, num_groups);
+        _func.configure(compile_context, input, biases, &_output, num_groups);
     }
 
     //Inherited method override
@@ -178,6 +199,28 @@ public:
      */
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(),
                    const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
+     *                             while every optional dimension from 4 and above represent a batch of inputs.
+     *                             Data types supported: QASYMM8/F16/F32.
+     * @param[in]  weights         Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
+     *                             Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
+     * @param[in]  biases          Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+     *                             Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
+     * @param[out] output          Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+     *                             Data types supported: Same as @p input.
+     * @param[in]  conv_info       Contains padding and stride information described in @ref PadStrideInfo.
+     * @param[in]  weights_info    Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
+     *                             tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
+     * @param[in]  dilation        (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
+     * @param[in]  num_groups      (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
+     */
+    void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
+                   const WeightsInfo &weights_info = WeightsInfo(),
+                   const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer.
      *
      * @param[in]  input        Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
@@ -208,6 +251,7 @@ public:
 private:
     /** Configures the appropriate matrix multiply routine
      *
+     * @param[in]      compile_context       The compile context to be used.
      * @param[in]      input                 Input tensor. Data types supported: QASYMM8/F16/F32.
      * @param[in]      weights               Weights tensor. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
      * @param[in]      biases                Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
@@ -218,8 +262,9 @@ private:
      * @param[in]      gemm_3d_depth         Depth of GEMM 3D
      * @param[in]      act_info              Activation to apply after the matrix multiplication
      */
-    void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, int gemm_3d_depth,
-                      const ActivationLayerInfo &act_info);
+    void configure_mm(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
+                      const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
+                      int gemm_3d_depth, const ActivationLayerInfo &act_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines
      *
      * @param[in] input                 Input tensor info. Data types supported: QASYMM8/F16/F32.