class_docstr: L2 Weight Decay Regularization, which helps to prevent the model over-fitting.
  Args:
      factor(float): regularization coeff. Default:0.0.
class_docstr_tok: ["L2","Weight","Decay","Regularization",",","which","helps","to","prevent","the","model","over-fitting",".","Args",":","factor","(","float",")",":","regularization","coeff",".","Default:0.0","."]
code: def __init__(self, factor=0.0):
      super(L2Decay, self).__init__()
      self.coeff = float(factor)
  
file_path: PaddleOCR/ppocr/optimizer/regularizer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import paddle
label_desc: Use image node_id 1 to create a new L2Decay object from inherited base classes: object with example: obj = L2Decay(factor)