text: // 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/ops/opencl/buffer/depthwise_conv2d.h"
  
  #include <set>
  #include <string>
  
  namespace mace {
  namespace ops {
  namespace opencl {
  namespace buffer {
  namespace depthwise {
  
  MaceStatus DepthwiseConv2d(OpContext *context,
                             cl::Kernel *kernel,
                             const Tensor *padded_input,   // NHWC
                             const Tensor *filter,  // HWIM
                             const Tensor *bias,
                             const int *strides,
                             const int *dilations,
                             const DataType dt,
                             const ActivationType activation,
                             const float relux_max_limit,
                             const bool input_changed,
                             Tensor *output,
                             StatsFuture *future) {
    const index_t batch = output->dim(0);
    const index_t height = output->dim(1);
    const index_t width = output->dim(2);
    const index_t channel = output->dim(3);
  
    const index_t in_height = padded_input->dim(1);
    const index_t in_width = padded_input->dim(2);
    const index_t in_channel = padded_input->dim(3);
  
    const index_t filter_height = filter->dim(2);
    const index_t filter_width = filter->dim(3);
  
    auto runtime = context->device()->gpu_runtime()->opencl_runtime();
    MACE_OUT_OF_RANGE_DEFINITION
  
    if (kernel->get() == nullptr) {
      std::set<std::string> built_options;
      MACE_OUT_OF_RANGE_CONFIG;
      MACE_NON_UNIFORM_WG_CONFIG;
      std::string kernel_name = MACE_OBFUSCATE_SYMBOL("depthwise_conv2d");
      built_options.emplace("-Ddepthwise_conv2d=" + kernel_name);
      built_options.emplace("-DIN_DATA_TYPE=" + DtToCLDt(padded_input->dtype()));
      built_options.emplace("-DOUT_DATA_TYPE=" + DtToCLDt(dt));
      built_options.emplace("-DDATA_TYPE=" + DtToUpCompatibleCLDt(dt));
      built_options.emplace(bias != nullptr ? "-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;
      }
  
      MACE_RETURN_IF_ERROR(
          runtime->BuildKernel("depthwise_conv2d_buffer", kernel_name,
                               built_options, kernel));
    }
  
    const uint32_t gws[2] = {
        static_cast<uint32_t>(RoundUpDiv4(channel) * RoundUpDiv4(width)),
        static_cast<uint32_t>(height * batch)
    };
  
    MACE_OUT_OF_RANGE_INIT(*kernel);
    if (input_changed) {
      uint32_t idx = 0;
      MACE_BUFF_OUT_OF_RANGE_SET_ARGS(*kernel, output->size());
      MACE_SET_2D_GWS_ARGS(*kernel, gws);
      kernel->setArg(idx++, *(padded_input->opencl_buffer()));
      kernel->setArg(idx++, *(filter->opencl_buffer()));
      if (bias != nullptr) {
        kernel->setArg(idx++, *(bias->opencl_buffer()));
      }
      kernel->setArg(idx++, static_cast<uint32_t>(in_height));
      kernel->setArg(idx++, static_cast<uint32_t>(in_width));
      kernel->setArg(idx++, static_cast<uint32_t>(in_channel));
      kernel->setArg(idx++, static_cast<uint32_t>(filter_height));
      kernel->setArg(idx++, static_cast<uint32_t>(filter_width));
      kernel->setArg(idx++, static_cast<uint32_t>(filter_height * filter_width));
      kernel->setArg(idx++, static_cast<uint32_t>(height));
      kernel->setArg(idx++, static_cast<uint32_t>(width));
      kernel->setArg(idx++, static_cast<uint32_t>(channel));
      kernel->setArg(idx++, static_cast<uint32_t>(strides[0]));
      kernel->setArg(idx++, static_cast<uint32_t>(strides[1]));
      kernel->setArg(idx++, static_cast<int32_t>(
          dilations[0] * in_width * in_channel));
      kernel->setArg(idx++, static_cast<int32_t>(
          dilations[1] * in_channel));
      kernel->setArg(idx++, relux_max_limit);
      kernel->setArg(idx++, *(output->opencl_buffer()));
    }
  
    std::vector<uint32_t> lws = {16, 4, 0};
    std::string tuning_key =
        Concat("depthwise_conv2d_buffer_kernel", in_height, in_width, in_channel,
               filter_height, filter_width, channel);
    MACE_RETURN_IF_ERROR(TuningOrRun2DKernel(runtime, *kernel, tuning_key,
                                             gws, lws, future));
  
    MACE_OUT_OF_RANGE_VALIDATION
    return MaceStatus::MACE_SUCCESS;
  }
  
  }  // namespace depthwise
  }  // namespace buffer
  }  // namespace opencl
  }  // namespace ops
  }  // namespace mace
  