text: /*
   * Copyright (c) 2017-2018 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 "arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h"
  
  #include "arm_compute/core/AccessWindowStatic.h"
  #include "arm_compute/core/CL/CLHelpers.h"
  #include "arm_compute/core/CL/CLKernelLibrary.h"
  #include "arm_compute/core/CL/ICLTensor.h"
  #include "arm_compute/core/TensorInfo.h"
  #include "arm_compute/core/Utils.h"
  #include "arm_compute/core/Validate.h"
  #include "arm_compute/core/Window.h"
  
  using namespace arm_compute;
  
  namespace
  {
  Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *min_max)
  {
      ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, min_max);
      ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
      ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() < 3);
  
      if(output->tensor_shape().total_size() > 0)
      {
          ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
          ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
      }
  
      return Status{};
  }
  
  std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, ITensorInfo *min_max)
  {
      // Output tensor auto initialization if not yet initialized
      auto_init_if_empty(*output, input->tensor_shape(), 1, DataType::F32);
  
      constexpr unsigned int num_elems_processed_per_iteration = 4;
  
      // Configure window
      Window                 win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
      AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
      AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
      AccessWindowStatic     min_max_access(min_max, 0, 0, 2, min_max->dimension(1));
  
      // Update window and padding
      bool window_changed = update_window_and_padding(win, input_access, output_access, min_max_access);
  
      output_access.set_valid_region(win, input->valid_region());
  
      Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
      return std::make_tuple(err, win);
  }
  } // namespace
  
  CLDequantizationLayerKernel::CLDequantizationLayerKernel()
      : _input(nullptr), _output(nullptr), _min_max(nullptr)
  {
  }
  
  void CLDequantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *min_max)
  {
      ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, min_max);
      ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), min_max->info()));
  
      _input   = input;
      _output  = output;
      _min_max = min_max;
  
      // Create kernel
      _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("dequantization_layer"));
  
      // Configure kernel window
      auto win_config = validate_and_configure_window(input->info(), output->info(), min_max->info());
  
      ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
  
      ICLKernel::configure_internal(std::get<1>(win_config));
  }
  
  Status CLDequantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *min_max)
  {
      ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, min_max));
      ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get(), min_max->clone().get())));
  
      return Status{};
  }
  
  void CLDequantizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
  {
      ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
      ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
  
      Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), 3);
      Window slice            = window_collapsed.first_slice_window_3D();
  
      Window min_max_window = window;
      min_max_window.set(Window::DimX, Window::Dimension(0, 0, 0));
      min_max_window.set(Window::DimY, Window::Dimension(0, _min_max->info()->dimension(1), 1));
      min_max_window.set(Window::DimZ, Window::Dimension(0, 0, 0));
  
      Window min_max_slice = min_max_window.first_slice_window_1D();
  
      do
      {
          unsigned int idx = 0;
          add_3D_tensor_argument(idx, _input, slice);
          add_3D_tensor_argument(idx, _output, slice);
          add_1D_tensor_argument(idx, _min_max, min_max_slice);
          enqueue(queue, *this, slice);
      }
      while(window_collapsed.slide_window_slice_3D(slice) && min_max_window.slide_window_slice_1D(min_max_slice));
  }
  