message: Clang format issues.
diff: @@ -22,7 +22,6 @@ limitations under the License.
  #include <functional>
  #include <string>
  -#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
  #include "tensorflow/core/framework/bounds_check.h"
  #include "tensorflow/core/framework/register_types.h"
  #include "tensorflow/core/framework/tensor.h"
  @@ -33,6 +32,7 @@ limitations under the License.
  #include "tensorflow/core/platform/logging.h"
  #include "tensorflow/core/platform/types.h"
  #include "tensorflow/core/util/work_sharder.h"
  +#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
  #if GOOGLE_CUDA
  #include "tensorflow/core/common_runtime/gpu/gpu_event_mgr.h"
  @@ -452,7 +452,8 @@ struct CropAndResizeBackpropImage<CPUDevice, T> {
  // Parallelize the loop using Eigen thread pool.
  // Assign ranges of boxes into different threads.
  // Split two methods' code to avoid branch mis-prediction.
  - auto CropAndResizeBackImgPerBoxBilinear = [&](int start_box, int limit_box) {
  + auto CropAndResizeBackImgPerBoxBilinear = [&](int start_box,
  + int limit_box) {
  for (int b = start_box; b < limit_box; ++b) {
  const float y1 = boxes(b, 0);
  const float x1 = boxes(b, 1);
  @@ -569,16 +570,16 @@ struct CropAndResizeBackpropImage<CPUDevice, T> {
  (method_name == "bilinear"
  ? depth * (Eigen::TensorOpCost::AddCost<float>() * 4 +
  Eigen::TensorOpCost::MulCost<float>() * 6 +
  - Eigen::TensorOpCost::CastCost<T, float>() * 4)
  - + Eigen::TensorOpCost::AddCost<float>() * 4
  + Eigen::TensorOpCost::CastCost<T, float>() * 4) +
  + Eigen::TensorOpCost::AddCost<float>() * 4
  : depth * (Eigen::TensorOpCost::AddCost<float>() +
  Eigen::TensorOpCost::CastCost<T, float>()));
  const double cost_per_box = crop_height * crop_width * cost_per_pixel;
  const DeviceBase::CpuWorkerThreads& worker_threads =
  *(context->device()->tensorflow_cpu_worker_threads());
  - method_name == "bilinear" ?
  - Shard(worker_threads.num_threads, worker_threads.workers, num_boxes,
  + method_name == "bilinear"
  + ? Shard(worker_threads.num_threads, worker_threads.workers, num_boxes,
  cost_per_box, CropAndResizeBackImgPerBoxBilinear)
  : Shard(worker_threads.num_threads, worker_threads.workers, num_boxes,
  cost_per_box, CropAndResizeBackImgPerBoxNearest);
  