class_docstr: L1 Weight Decay Regularization, which encourages the weights to be sparse.
  Args:
      factor(float): regularization coeff. Default:0.0.
class_docstr_tok: ["L1","Weight","Decay","Regularization",",","which","encourages","the","weights","to","be","sparse",".","Args",":","factor","(","float",")",":","regularization","coeff",".","Default:0.0","."]
code: def __init__(self, factor=0.0):
      super(L1Decay, self).__init__()
      self.coeff = 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 L1Decay object from inherited base classes: object with example: obj = L1Decay(factor)