// Copyright 2018 Xiaomi, Inc.  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/core/runtime/opencl/opencl_runtime.h"
#include "mace/kernels/conv_2d.h"
#include "mace/kernels/opencl/helper.h"
#include "mace/utils/tuner.h"

namespace mace {
namespace kernels {

namespace {
// (inputs + weights + outputs) * array_size * sizeof(float)
const uint32_t kernel_cache_size = (4 + 4 + 4) * 4 * 4;
// TODO(liuqi): Fix the specific value.
const uint32_t lws_limit = 128;
std::vector<uint32_t> LocalWS(const uint32_t *gws, const uint32_t kwg_size) {
  std::vector<uint32_t> lws(4, 0);
  uint64_t cache_size = OpenCLRuntime::Global()->device_global_mem_cache_size();
  uint32_t compute_units = OpenCLRuntime::Global()->device_compute_units();
  uint32_t base = cache_size / kBaseGPUMemCacheSize;
  lws[1] = std::min<uint32_t>(gws[1], kwg_size);
  if (lws[1] >= base) {
    lws[0] = std::min<uint32_t>(gws[0], base);
  } else if ((1 < lws[1] && lws[1] < base) && gws[0] >= lws_limit) {
    lws[0] = std::min<uint32_t>(gws[0], base);
  } else {
    lws[0] = gws[0] / 8;
    if (lws[0] < base) {
      lws[0] = std::max<uint32_t>(gws[0] / 4, base);
    }
  }
  lws[0] = std::min<uint32_t>(lws[0], kwg_size / lws[1]);
  const uint32_t lws_size = lws[0] * lws[1];
  lws[2] = std::min<uint32_t>(
      (cache_size / kernel_cache_size / lws_size / compute_units) * 8, gws[2]);
  if (lws[2] == 0) {
    lws[2] = std::min<uint32_t>(gws[2], base);
  }
  lws[2] = std::min<uint32_t>(lws[2], kwg_size / lws_size);
  return lws;
}

}  // namespace

extern MaceStatus Conv2dOpenclK1x1(cl::Kernel *kernel,
                                   const Tensor *input,
                                   const Tensor *filter,
                                   const Tensor *bias,
                                   const int stride,
                                   const int *padding,
                                   const int *dilations,
                                   const ActivationType activation,
                                   const float relux_max_limit,
                                   const DataType dt,
                                   std::vector<index_t> *prev_input_shape,
                                   Tensor *output,
                                   StatsFuture *future,
                                   uint32_t *kwg_size,
                                   std::unique_ptr<BufferBase> *kernel_error) {
  MACE_UNUSED(padding);
  MACE_UNUSED(dilations);
  const index_t batch = output->dim(0);
  const index_t height = output->dim(1);
  const index_t width = output->dim(2);
  const index_t channels = output->dim(3);
  const index_t input_batch = input->dim(0);
  const index_t input_height = input->dim(1);
  const index_t input_width = input->dim(2);
  const index_t input_channels = input->dim(3);

  const index_t channel_blocks = RoundUpDiv4(channels);
  const index_t width_blocks = RoundUpDiv4(width);
  const index_t input_channel_blocks = RoundUpDiv4(input_channels);

  auto runtime = OpenCLRuntime::Global();

  if (kernel->get() == nullptr) {
    MACE_CHECK(input_batch == batch);

    std::set<std::string> built_options;
    std::string kernel_name = MACE_OBFUSCATE_SYMBOL("conv_2d_1x1");
    built_options.emplace("-Dconv_2d_1x1=" + kernel_name);
    built_options.emplace("-DDATA_TYPE=" + DtToUpstreamCLDt(dt));
    built_options.emplace("-DCMD_DATA_TYPE=" + DtToUpstreamCLCMDDt(dt));
    if (runtime->IsOutOfRangeCheckEnabled()) {
      built_options.emplace("-DOUT_OF_RANGE_CHECK");
      *kernel_error = std::move(std::unique_ptr<Buffer>(
          new Buffer(GetDeviceAllocator(DeviceType::GPU))));
      MACE_RETURN_IF_ERROR((*kernel_error)->Allocate(1));
      (*kernel_error)->Map(nullptr);
      *((*kernel_error)->mutable_data<char>()) = 0;
      (*kernel_error)->UnMap();
    }
    if (runtime->IsNonUniformWorkgroupsSupported()) {
      built_options.emplace("-DNON_UNIFORM_WORK_GROUP");
    }
    if (bias != nullptr) {
      built_options.emplace("-DBIAS");
    }
    switch (activation) {
      case NOOP:
        break;
      case RELU:
        built_options.emplace("-DUSE_RELU");
        break;
      case RELUX:
        built_options.emplace("-DUSE_RELUX");
        break;
      case TANH:
        built_options.emplace("-DUSE_TANH");
        break;
      case SIGMOID:
        built_options.emplace("-DUSE_SIGMOID");
        break;
      default:
        LOG(FATAL) << "Unknown activation type: " << activation;
    }

    *kernel = runtime->BuildKernel("conv_2d_1x1", kernel_name, built_options);

    *kwg_size =
        static_cast<uint32_t>(runtime->GetKernelMaxWorkGroupSize(*kernel));
  }

  const uint32_t gws[3] = {static_cast<uint32_t>(channel_blocks),
                           static_cast<uint32_t>(width_blocks),
                           static_cast<uint32_t>(height * batch)};

  if (!IsVecEqual(*prev_input_shape, input->shape())) {
    uint32_t idx = 0;
    if (runtime->IsOutOfRangeCheckEnabled()) {
      kernel->setArg(idx++,
                     *(static_cast<cl::Buffer *>((*kernel_error)->buffer())));
    }
    if (!runtime->IsNonUniformWorkgroupsSupported()) {
      kernel->setArg(idx++, gws[0]);
      kernel->setArg(idx++, gws[1]);
      kernel->setArg(idx++, gws[2]);
    }
    kernel->setArg(idx++, *(input->opencl_image()));
    kernel->setArg(idx++, *(filter->opencl_image()));
    if (bias != nullptr) {
      kernel->setArg(idx++, *(bias->opencl_image()));
    }
    kernel->setArg(idx++, *(output->opencl_image()));
    // FIXME handle flexable data type: half not supported
    kernel->setArg(idx++, relux_max_limit);
    kernel->setArg(idx++, static_cast<int>(input_height));
    kernel->setArg(idx++, static_cast<int>(input_width));
    kernel->setArg(idx++, static_cast<int>(input_channel_blocks));
    kernel->setArg(idx++, static_cast<int>(height));
    kernel->setArg(idx++, static_cast<int>(width));
    kernel->setArg(idx++, stride);

    *prev_input_shape = input->shape();
  }

  std::vector<uint32_t> lws = LocalWS(gws, *kwg_size);
  std::string tuning_key =
      Concat("conv2d_1x1_opencl_kernel", output->dim(0), output->dim(1),
             output->dim(2), output->dim(3));
  TuningOrRun3DKernel(*kernel, tuning_key, gws, lws, future);

  if (runtime->IsOutOfRangeCheckEnabled()) {
    (*kernel_error)->Map(nullptr);
    char *kerror_code = (*kernel_error)->mutable_data<char>();
    MACE_CHECK(*kerror_code == 0) << "Kernel error code: " << *kerror_code;
    (*kernel_error)->UnMap();
  }

  return MACE_SUCCESS;
}

}  // namespace kernels
}  // namespace mace
