class_docstr: Encapsulate the results obtained by the :py:class:`kornia.contrib.FaceDetector`.
  
  Args:
      data: the encoded results coming from the feature detector with shape :math:`(14,)`.
class_docstr_tok: ["Encapsulate","the","results","obtained","by","the",":","py",":","class",":","`","kornia.contrib.FaceDetector","`",".","Args",":","data",":","the","encoded","results","coming","from","the","feature","detector","with","shape",":","math",":","`","(","14",",",")","`","."]
docstr: Like :func:`torch.nn.Module.to()` method.
docstr_tok: ["Like",":","func",":","`","torch.nn.Module.to","(",")","`","method","."]
code: def to(
      self,
      device: Optional[torch.device] = None,
      dtype: Optional[torch.dtype] = None,
  ) -> "FaceDetectorResult":
      """Like :func:`torch.nn.Module.to()` method."""
      self._data = self._data.to(device=device, dtype=dtype)
      return self
  
imports: import math
  from enum import Enum
  from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.geometry.bbox import nms
  from kornia.utils.helpers import map_location_to_cpu
label_desc: Use image node_id 2 for calling the FaceDetectorResult obj's underlying member method code with example usage: obj.to(device, dtype) and returns: self