Remove legacy PostOps code

PostOps was the experimental interface for Dynamic Fusion. It is now
replaced by the new Dynamic Fusion interface with code generation using
the Compute Kernel Writer.

Resolves: COMPMID-6190

Change-Id: I813b48facef2fd6f3aee332588886b4f9b3d33d8
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10219
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 10 insertions, 53 deletions

diff --git a/src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.cpp b/src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.cpp
index 5fea097ae3..b8997dfc7f 100644
--- a/src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.cpp
+++ b/src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.cpp
@@ -23,7 +23,6 @@
  */
 #include "src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.h"
 
-#include "arm_compute/core/utils/ActivationFunctionUtils.h"
 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
 #include "arm_compute/core/CL/ICLTensor.h"
@@ -31,11 +30,11 @@
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Validate.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/utils/ActivationFunctionUtils.h"
 #include "arm_compute/core/utils/StringUtils.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "src/core/AccessWindowStatic.h"
 #include "src/core/CL/CLUtils.h"
-#include "src/core/experimental/PostOpUtils.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "src/core/utils/helpers/float_ops.h"
@@ -52,25 +51,6 @@ namespace
 {
 using ElementsProcessed = Steps;
 
-const auto post_op_utils = experimental::PostOpCLKernelUtils(
-{
-    //  PostOp sequence                   -> {Kernel Postfix, PostOp Slots}
-    { {}, { "", {} } },
-    { { experimental::PostOpType::Activation }, { "", { 1 } } },
-
-    { { experimental::PostOpType::Eltwise_Add }, { "_post_act_eltwise_op_act", { 2 } } },
-    { { experimental::PostOpType::Eltwise_PRelu }, { "_post_act_eltwise_op_act", { 2 } } },
-
-    { { experimental::PostOpType::Activation, experimental::PostOpType::Eltwise_Add }, { "_post_act_eltwise_op_act", { 1, 2 } } },
-    { { experimental::PostOpType::Activation, experimental::PostOpType::Eltwise_PRelu }, { "_post_act_eltwise_op_act", { 1, 2 } } },
-
-    { { experimental::PostOpType::Eltwise_Add, experimental::PostOpType::Activation }, { "_post_act_eltwise_op_act", { 2, 3 } } },
-    { { experimental::PostOpType::Eltwise_PRelu, experimental::PostOpType::Activation }, { "_post_act_eltwise_op_act", { 2, 3 } } },
-
-    { { experimental::PostOpType::Activation, experimental::PostOpType::Eltwise_Add, experimental::PostOpType::Activation }, { "_post_act_eltwise_op_act", { 1, 2, 3 } } },
-    { { experimental::PostOpType::Activation, experimental::PostOpType::Eltwise_PRelu, experimental::PostOpType::Activation }, { "_post_act_eltwise_op_act", { 1, 2, 3 } } }
-});
-
 Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
                           const GEMMRHSMatrixInfo &rhs_info,
                           const GEMMKernelInfo    &gemm_info)
@@ -90,7 +70,6 @@ Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, cons
                                     "Bias addition only supported with broadcast mode in case the input or dst has to be reinterpreted as 3D");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision, "Mixed precision not supported");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(rhs_info.export_to_cl_image, "Export to CLImage not supported for GEMM native");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(!post_op_utils.is_post_op_sequence_supported(gemm_info.post_ops), "The sequence of Post Ops is not supported");
 
     const unsigned int m = gemm_info.m;
     const unsigned int n = gemm_info.n;
@@ -133,7 +112,6 @@ Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, cons
         const TensorInfo tensor_info_dst = dst->clone()->set_tensor_shape(misc::shape_calculator::compute_mm_shape(*src0, *src1, gemm_info));
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_dst);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src0, dst);
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(!post_op_utils.are_post_op_shapes_compliant(dst, gemm_info.post_ops), "The Post Op shapes are not compliant");
     }
 
     return Status{};
@@ -240,7 +218,6 @@ void ClGemmMatrixMultiplyNativeKernel::configure(const CLCompileContext &compile
     _reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0;
     _use_dummy_work_items     = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device());
     _add_bias                 = src2 != nullptr;
-    _num_post_op_args         = gemm_info.post_ops.total_num_arguments();
 
     // In case both input and dst have to be reinterpreted as 3D tensors,
     // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
@@ -298,20 +275,11 @@ void ClGemmMatrixMultiplyNativeKernel::configure(const CLCompileContext &compile
     build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0));
     build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
     build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
-    // If post_ops are used, then we disable the use of gemm_info.activation_info
-    if(gemm_info.post_ops.size() > 0)
-    {
-        post_op_utils.set_post_ops_cl_build_options(build_opts, gemm_info.post_ops);
-    }
-    else
-    {
-        build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
-        build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
-        build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
-    }
+    build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation())));
+    build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a()));
+    build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b()));
 
     std::string kernel_name("gemm_mm_native");
-    post_op_utils.set_post_ops_cl_kernel_name(kernel_name, gemm_info.post_ops);
 
     // A macro guard to compile ONLY the kernel of interest
     build_opts.add_option("-D" + upper_string(kernel_name));
@@ -396,11 +364,11 @@ void ClGemmMatrixMultiplyNativeKernel::run_op(ITensorPack &tensors, const Window
         unsigned int idx0;
         if(_add_bias)
         {
-            idx0 = (4 + _num_post_op_args) * num_arguments_per_2D_tensor() + (7 + _num_post_op_args);
+            idx0 = 4 * num_arguments_per_2D_tensor() + 7;
         }
         else
         {
-            idx0 = (3 + _num_post_op_args) * num_arguments_per_2D_tensor() + (6 + _num_post_op_args);
+            idx0 = 3 * num_arguments_per_2D_tensor() + 6;
         }
         const unsigned int total_cross_plane_pad = src0->info()->padding().top + src0->info()->padding().bottom;
         _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
@@ -412,11 +380,11 @@ void ClGemmMatrixMultiplyNativeKernel::run_op(ITensorPack &tensors, const Window
         unsigned int idx0;
         if(_add_bias)
         {
-            idx0 = (4 + _num_post_op_args) * num_arguments_per_2D_tensor() + 7 + (_reinterpret_input_as_3d ? 1 : 0) + _num_post_op_args;
+            idx0 = 4 * num_arguments_per_2D_tensor() + 7 + (_reinterpret_input_as_3d ? 1 : 0);
         }
         else
         {
-            idx0 = (3 + _num_post_op_args) * num_arguments_per_2D_tensor() + 6 + (_reinterpret_input_as_3d ? 1 : 0) + _num_post_op_args;
+            idx0 = 3 * num_arguments_per_2D_tensor() + 6 + (_reinterpret_input_as_3d ? 1 : 0);
         }
         const unsigned int total_cross_plane_pad = dst->info()->padding().top + dst->info()->padding().bottom;
         _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
@@ -440,12 +408,7 @@ void ClGemmMatrixMultiplyNativeKernel::run_op(ITensorPack &tensors, const Window
             add_2D_tensor_argument(idx, src2, slice);
         }
         add_2D_tensor_argument(idx, dst, slice);
-        // post op argument buffers
-        for(size_t i = 0; i < _num_post_op_args; ++i)
-        {
-            const auto post_op_arg = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(experimental::get_post_op_arg_type(i)));
-            add_2D_tensor_argument(idx, post_op_arg, slice);
-        }
+
         _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src0->info()->strides_in_bytes()[2]));
         _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src1->info()->strides_in_bytes()[2]));
         if(_add_bias)
@@ -453,12 +416,6 @@ void ClGemmMatrixMultiplyNativeKernel::run_op(ITensorPack &tensors, const Window
             _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src2->info()->strides_in_bytes()[2]));
         }
         _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[2]));
-        // post op argument stride_z
-        for(size_t i = 0; i < _num_post_op_args; ++i)
-        {
-            const auto post_op_arg = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(experimental::get_post_op_arg_type(i)));
-            _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(post_op_arg->info()->strides_in_bytes()[2]));
-        }
 
         // Pass m, n and k at runtime
         _kernel.setArg<cl_int>(idx++, _m);