class_docstr: Reference: Wen et al. A Discriminative Feature Learning Approach for Deep Face Recognition. ECCV 2016.
code: def __init__(
      self, num_classes=6625, feat_dim=96, center_file_path=None
  ):
      super().__init__()
      self.num_classes = num_classes
      self.feat_dim = feat_dim
      self.centers = paddle.randn(
          shape=[self.num_classes, self.feat_dim]
      ).astype("float64")
  
      if center_file_path is not None:
          assert os.path.exists(
              center_file_path
          ), f"center path({center_file_path}) must exist when it is not None."
          with open(center_file_path, "rb") as f:
              char_dict = pickle.load(f)
              for key in char_dict.keys():
                  self.centers[key] = paddle.to_tensor(char_dict[key])
  
file_path: PaddleOCR/ppocr/losses/center_loss.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import pickle
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new CenterLoss object from inherited base classes: nn with example: obj = CenterLoss(num_classes, feat_dim, center_file_path)