Move CPU/GPU files from Core/Runtime to the respective backend folders

Legacy structure contained two libraries core/runtime with two backends
in each.
We reduce the core/runtime libraries to a single library thus merging
the backend files

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 201 deletions

diff --git a/src/core/cpu/kernels/CpuSubKernel.cpp b/src/core/cpu/kernels/CpuSubKernel.cpp
deleted file mode 100644
index fa7a55805e..0000000000
--- a/src/core/cpu/kernels/CpuSubKernel.cpp
+++ /dev/null
@@ -1,201 +0,0 @@
-/*
- * Copyright (c) 2021 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "src/core/cpu/kernels/CpuSubKernel.h"
-
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Validate.h"
-#include "src/core/CPP/Validate.h"
-#include "src/core/common/Registrars.h"
-#include "src/core/cpu/kernels/sub/neon/list.h"
-#include "src/core/helpers/AutoConfiguration.h"
-#include "src/core/helpers/WindowHelpers.h"
-
-namespace arm_compute
-{
-namespace cpu
-{
-namespace kernels
-{
-namespace
-{
-struct SubSelectorData
-{
-    DataType dt;
-};
-
-using SubSelectorPtr = std::add_pointer<bool(const SubSelectorData &data)>::type;
-using SubKernelPtr   = std::add_pointer<void(const ITensor *, const ITensor *, ITensor *, const ConvertPolicy &, const Window &)>::type;
-
-struct SubKernel
-{
-    const char          *name;
-    const SubSelectorPtr is_selected;
-    SubKernelPtr         ukernel;
-};
-
-static const SubKernel available_kernels[] =
-{
-    {
-        "neon_fp32_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::F32); },
-        REGISTER_FP32_NEON(arm_compute::cpu::sub_same_neon<float>)
-    },
-#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
-    {
-        "neon_fp16_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::F16); },
-        REGISTER_FP16_NEON(arm_compute::cpu::sub_same_neon<float16_t>)
-    },
-#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */
-    {
-        "neon_u8_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::U8); },
-        REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<uint8_t>)
-    },
-    {
-        "neon_s16_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::S16); },
-        REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<int16_t>)
-    },
-    {
-        "neon_s32_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::S32); },
-        REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon<int32_t>)
-    },
-    {
-        "neon_qu8_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::QASYMM8); },
-        REGISTER_QASYMM8_NEON(arm_compute::cpu::sub_qasymm8_neon)
-    },
-    {
-        "neon_qs8_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
-        REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::sub_qasymm8_signed_neon)
-    },
-    {
-        "neon_qs16_sub",
-        [](const SubSelectorData & data) { return (data.dt == DataType::QSYMM16); },
-        REGISTER_QSYMM16_NEON(arm_compute::cpu::sub_qsymm16_neon)
-    },
-};
-
-/** Micro-kernel selector
- *
- * @param[in] data Selection data passed to help pick the appropriate micro-kernel
- *
- * @return A matching micro-kernel else nullptr
- */
-const SubKernel *get_implementation(DataType dt)
-{
-    for(const auto &uk : available_kernels)
-    {
-        if(uk.is_selected({ dt }))
-        {
-            return &uk;
-        }
-    }
-    return nullptr;
-}
-
-inline Status validate_arguments(const ITensorInfo &src0, const ITensorInfo &src1, const ITensorInfo &dst, ConvertPolicy policy)
-{
-    ARM_COMPUTE_UNUSED(policy);
-    ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&src0);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src0, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::S16, DataType::S32, DataType::F16,
-                                                         DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src0, &src1);
-
-    const auto *uk = get_implementation(src0.data_type());
-    ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
-
-    const TensorShape out_shape = TensorShape::broadcast_shape(src0.tensor_shape(), src1.tensor_shape());
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
-
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(src0.data_type()) && (policy == ConvertPolicy::WRAP),
-                                    "Convert policy cannot be WRAP if datatype is quantized");
-
-    // Validate in case of configured dst
-    if(dst.total_size() > 0)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src0, &dst);
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst.tensor_shape(), 0),
-                                        "Wrong shape for dst");
-    }
-    return Status{};
-}
-} // namespace
-
-void CpuSubKernel::configure(const ITensorInfo *src0, const ITensorInfo *src1, ITensorInfo *dst, ConvertPolicy policy)
-{
-    ARM_COMPUTE_ERROR_ON_NULLPTR(src0, src1, dst);
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*src0, *src1, *dst, policy));
-
-    const TensorShape &out_shape = TensorShape::broadcast_shape(src0->tensor_shape(), src1->tensor_shape());
-
-    // Auto initialize dst if not initialized
-    set_shape_if_empty(*dst, out_shape);
-    set_data_type_if_unknown(*dst, src0->data_type());
-
-    const auto *uk = get_implementation(src0->data_type());
-    ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
-
-    _policy     = policy;
-    _run_method = uk->ukernel;
-    _name       = std::string("CpuSubKernel").append("/").append(uk->name);
-
-    // CpuSubKernel doesn't need padding so update_window_and_padding() can be skipped
-    Window win = calculate_max_window(out_shape, Steps());
-
-    ICpuKernel::configure(win);
-}
-
-Status CpuSubKernel::validate(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *dst, ConvertPolicy policy)
-{
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src0, src1, dst);
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*src0, *src1, *dst, policy));
-
-    return Status{};
-}
-
-void CpuSubKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
-{
-    ARM_COMPUTE_UNUSED(info);
-    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
-    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
-    ARM_COMPUTE_ERROR_ON(_run_method == nullptr);
-
-    const ITensor *src0 = tensors.get_const_tensor(TensorType::ACL_SRC_0);
-    const ITensor *src1 = tensors.get_const_tensor(TensorType::ACL_SRC_1);
-    ITensor       *dst  = tensors.get_tensor(TensorType::ACL_DST);
-
-    _run_method(src0, src1, dst, _policy, window);
-}
-
-const char *CpuSubKernel::name() const
-{
-    return _name.c_str();
-}
-} // namespace kernels
-} // namespace cpu
-} // namespace arm_compute