COMPMID-3280: Make all ML primitives for CL use the new interface - Part 1

- Only CLKernels have been updated

Change-Id: Ife55b847c2e39e712a186eb6ca452503d5b66937
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3001
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 30 insertions, 1 deletions

diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
index 449c333143..45df67673c 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -76,6 +76,35 @@ public:
     void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
                    const GEMMRHSMatrixInfo &rhs_info,
                    const GEMMKernelInfo    &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @note The F16 computation also supports mixed precision through the gemm_info.fp_mixed_precision flag.
+     *       Mixed precision combines different floating precisions during the computation, in particular, F32 for the accumulations and F16 for the
+     *       multiplications. i.e. float c = (half)a * (half)b
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS reshaped matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4
+     * @param[in]  input1          Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0. The number of dimensions for the RHS matrix must be less or equal than 3
+     * @param[in]  input2          Input tensor containing the bias matrix. Data type supported: same as @p input0.
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+     * @param[in]  alpha           Weight of the matrix product
+     * @param[in]  beta            Weight of the matrix bias
+     * @param[in]  lhs_info        LHS matrix information used for reshaping the input0 tensor.  Only the following values are supported:
+     *                             lhs_info.m0: 2,3,4,5,6,7,8
+     *                             lhs_info.k0: 2,3,4,8,16
+     *                             lhs_info.transpose: false
+     * @param[in]  rhs_info        RHS matrix information used for reshaping the input1 tensor.  Only the following values are supported:
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: 2,3,4,8,16
+     *                             rhs_info.transpose: true
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     *
+     * @note lhs_info.k0 must be equal to rhs_info.k0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
+                   const GEMMLHSMatrixInfo &lhs_info,
+                   const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMKernelInfo    &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyReshapedKernel
      *
      * @param[in] input0    Input tensor containing the LHS reshaped matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4