message: Fix numeric_limits::min()->lowest() and clang-format
diff: @@ -498,7 +498,7 @@ Status DoNMS(OpKernelContext* context, const Tensor& boxes,
  original_boxes, sorted_boxes));
  int limited_num_boxes = num_boxes;
  // filter boxes by scores if nms v3
  - if (score_threshold > std::numeric_limits<float>::min()) {
  + if (score_threshold > std::numeric_limits<float>::lowest()) {
  GreaterThanCubOp score_limit(score_threshold);
  TF_RETURN_IF_ERROR(CountIf(context, d_sorted_scores.flat<float>().data(),
  score_limit, num_boxes, &limited_num_boxes));
  @@ -510,8 +510,8 @@ Status DoNMS(OpKernelContext* context, const Tensor& boxes,
  context->allocate_output(0, TensorShape({0}), &output_indices));
  return Status::OK();
  } else {
  - VLOG(2) << "Number of boxes above threshold=" << score_threshold
  - << " is " << limited_num_boxes;
  + VLOG(2) << "Number of boxes above threshold=" << score_threshold << " is "
  + << limited_num_boxes;
  }
  }
  int num_to_keep = 0;
  @@ -580,8 +580,8 @@ class NonMaxSuppressionV2GPUOp : public OpKernel {
  // otherwise tests fail!
  if (num_boxes == 0) {
  Tensor* output_indices = nullptr;
  - OP_REQUIRES_OK(context,
  - context->allocate_output(0, TensorShape({0}), &output_indices));
  + OP_REQUIRES_OK(context, context->allocate_output(0, TensorShape({0}),
  + &output_indices));
  return;
  }
  const int64_t output_size = max_output_size.scalar<int>()();
  @@ -589,7 +589,7 @@ class NonMaxSuppressionV2GPUOp : public OpKernel {
  context,
  DoNMS(context, boxes, scores, output_size, iou_threshold_val,
  /*score_threshold is float min if score threshold is disabled*/
  - std::numeric_limits<float>::min()));
  + std::numeric_limits<float>::lowest()));
  }
  };
  