// Copyright 2018 The MACE Authors. 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 "mace/ops/activation.h"

#include <memory>
#include <set>

#include "mace/core/ops/operator.h"
#include "mace/core/registry/ops_registry.h"
#include "mace/ops/delegator/activation.h"

#ifdef MACE_ENABLE_OPENCL
#include "mace/ops/opencl/buffer_transformer.h"
#include "mace/ops/opencl/image/activation.h"
#endif  // MACE_ENABLE_OPENCL
#include "mace/utils/memory.h"

namespace mace {
namespace ops {

template<DeviceType D, class T>
class ActivationOp;

template<typename T>
class ActivationOp<DeviceType::CPU, T> : public Operation {
 public:
  explicit ActivationOp(OpConstructContext *context)
      : Operation(context),
        activation_type_(ops::StringToActivationType(
            Operation::GetOptionalArg<std::string>("activation", "NOOP"))),
        activation_delegator_(delegator::Activation::Create(
            context->workspace(),
            MACE_DELEGATOR_KEY(Activation, DeviceType::CPU, T, kCpuImplType),
            delegator::ActivationParam(
                activation_type_,
                Operation::GetOptionalArg<float>("max_limit", 0.f),
                Operation::GetOptionalArg<float>(
                    "leakyrelu_coefficient", 0.f)))) {}

  MaceStatus Run(OpContext *context) override {
    MACE_UNUSED(context);
    const Tensor *input = this->Input(0);
    Tensor *output = this->Output(0);

    if (activation_type_ == PRELU || activation_type_ == ELU) {
      MACE_RETURN_IF_ERROR(output->ResizeLike(input));
      const T *input_ptr = input->data<T>();
      T *output_ptr = output->mutable_data<T>();
      MACE_CHECK(this->InputSize() > 1);
      const Tensor *alpha = this->Input(1);
      const T *alpha_ptr = alpha->data<T>();
      const index_t outer_size = output->dim(0);
      const index_t inner_size = output->dim(2) * output->dim(3);
      ActivationWithAlpha(context, input_ptr, outer_size, input->dim(1),
                          inner_size, alpha_ptr, activation_type_, output_ptr);
    } else {
      activation_delegator_->Compute(context, input, output);
    }
    return MaceStatus::MACE_SUCCESS;
  }

 private:
  ActivationType activation_type_;
  std::unique_ptr<delegator::Activation> activation_delegator_;
};

#ifdef MACE_ENABLE_OPENCL
template<>
class ActivationOp<DeviceType::GPU, float> : public Operation {
 public:
  explicit ActivationOp(OpConstructContext *context)
      : Operation(context) {
    ActivationType type = ops::StringToActivationType(
        Operation::GetOptionalArg<std::string>("activation",
                                              "NOOP"));
    auto relux_max_limit = Operation::GetOptionalArg<float>("max_limit", 0.0f);
    auto leakyrelu_coefficient =
        Operation::GetOptionalArg<float>("leakyrelu_coefficient", 0.0f);
    MemoryType mem_type;
    if (context->GetOpMemoryType() == MemoryType::GPU_IMAGE) {
      mem_type = MemoryType::GPU_IMAGE;
      kernel_ = make_unique<opencl::image::ActivationKernel>(
          type, relux_max_limit, leakyrelu_coefficient);
    } else {
      MACE_NOT_IMPLEMENTED;
    }
    if (type == ActivationType::PRELU || type == ActivationType::ELU) {
      MACE_CHECK(TransformFilter(
          context, operator_def_.get(), 1, OpenCLBufferType::ARGUMENT, mem_type)
                     == MaceStatus::MACE_SUCCESS);
    }
  }
  MaceStatus Run(OpContext *context) override {
    const Tensor *input = this->Input(0);
    const Tensor *alpha = this->InputSize() > 1 ? this->Input(1) : nullptr;
    Tensor *output = this->Output(0);
    MACE_RETURN_IF_ERROR(output->ResizeLike(input));

    return kernel_->Compute(context, input, alpha, output);
  }

 private:
  std::unique_ptr<OpenCLActivationKernel> kernel_;
};
#endif  // MACE_ENABLE_OPENCL

void RegisterActivation(OpRegistry *op_registry) {
  MACE_REGISTER_OP(op_registry, "Activation", ActivationOp,
                   DeviceType::CPU, float);
  MACE_REGISTER_BF16_OP(op_registry, "Activation",
                        ActivationOp, DeviceType::CPU);
#ifdef MACE_ENABLE_QUANTIZE
  MACE_REGISTER_OP(op_registry, "Activation", ActivationOp,
                   DeviceType::CPU, uint8_t);
#endif  // MACE_ENABLE_QUANTIZE
  MACE_REGISTER_GPU_OP(op_registry, "Activation", ActivationOp);
  MACE_REGISTER_OP_CONDITION(
      op_registry,
      OpConditionBuilder("Activation")
          .SetDevicePlacerFunc(
              [](OpConditionContext *context) -> std::set<DeviceType> {
                auto op = context->operator_def();
                if (op->output_shape_size() != op->output_size()) {
                  return {DeviceType::CPU, DeviceType::GPU};
                }
                int has_data_format =
                    ProtoArgHelper::GetOptionalArg<OperatorDef, int>(
                        *op, "has_data_format", 0);
                if (!has_data_format ||
                    op->output_shape(0).dims_size() != 4) {
                  return {DeviceType::CPU};
                }
                return {DeviceType::CPU, DeviceType::GPU};
              }));
}

}  // namespace ops
}  // namespace mace
