/*
 * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "CpuExecutor.h"
#include "NeuralNetworks.h"
#include "Operations.h"

#include "NNFWKernels.h"

#ifdef USE_NNFW_ACL_KERNELS
#include "kernel/acl/Conv2D.h"
#include "kernel/acl/DepthwiseConv2D.h"
#include "kernel/acl/Pooling.h"
#include "kernel/acl/Softmax.h"
#include "kernel/acl/FullyConnected.h"
#include "kernel/acl/Concatenation.h"
#include "kernel/acl/Reshape.h"
#include "kernel/acl/nnfw_kernel_acl.h"
#endif // USE_NNFW_ACL_KERNELS

#include <map>

namespace nnfw {
namespace rt {

#define NNFW_KERNEL(Name, Ret, Params) \
    NNFW_KERNELS_##Name nnfw_kernels_##Name;

#include "NNFWKernels.lst"
#undef NNFW_KERNEL

void init_nnfw_kernels()
{
#ifdef USE_NNFW_ACL_KERNELS
  nnfw::kernel::acl::Initialize();

  nnfw_kernels_convFloat32["acl"] = nnfw::kernel::acl::convFloat32;
  nnfw_kernels_depthwiseConvFloat32["acl"] = nnfw::kernel::acl::depthwiseConvFloat32;
  nnfw_kernels_averagePoolFloat32["acl"] = nnfw::kernel::acl::averagePoolFloat32;
  nnfw_kernels_maxPoolFloat32["acl"] = nnfw::kernel::acl::maxPoolFloat32;
  nnfw_kernels_softmaxFloat32["acl"] = nnfw::kernel::acl::softmaxFloat32;
  nnfw_kernels_fullyConnectedFloat32["acl"] = nnfw::kernel::acl::fullyConnectedFloat32;
  nnfw_kernels_concatenationFloat32["acl"] = nnfw::kernel::acl::concatenationFloat32;
  nnfw_kernels_reshapeGeneric["acl"] = nnfw::kernel::acl::reshapeGeneric;

  nnfw_kernels_convFloat32["neon"] = nnfw::kernel::acl::neon::convFloat32;
  nnfw_kernels_depthwiseConvFloat32["neon"] = nnfw::kernel::acl::neon::depthwiseConvFloat32;
  nnfw_kernels_averagePoolFloat32["neon"] = nnfw::kernel::acl::neon::averagePoolFloat32;
  nnfw_kernels_maxPoolFloat32["neon"] = nnfw::kernel::acl::neon::maxPoolFloat32;
  nnfw_kernels_softmaxFloat32["neon"] = nnfw::kernel::acl::neon::softmaxFloat32;
  nnfw_kernels_fullyConnectedFloat32["neon"] = nnfw::kernel::acl::neon::fullyConnectedFloat32;
  nnfw_kernels_concatenationFloat32["neon"] = nnfw::kernel::acl::neon::concatenationFloat32;
  nnfw_kernels_reshapeGeneric["neon"] = nnfw::kernel::acl::reshapeGeneric;
#endif // USE_NNFW_ACL_KERNELS
  return;
}

} // namespace rt
} // namespace nnfw