class_docstr: GroupLasso Regularizer:
  The first dimension represents the input layer and the second dimension represents the output layer.
  The groups are defined by the column in the matrix W
class_docstr_tok: ["GroupLasso","Regularizer",":","The","first","dimension","represents","the","input","layer","and","the","second","dimension","represents","the","output","layer",".","The","groups","are","defined","by","the","column","in","the","matrix","W"]
code: def __init__(self, model, lambda_reg=0.01):
      super(GroupLassoRegularizer, self).__init__(model=model)
      self.lambda_reg = lambda_reg
  
imports: from enum import Enum
label_desc: Use image node_id 1 to create a new GroupLassoRegularizer object from inherited base classes: _Regularizer with example: obj = GroupLassoRegularizer(model, lambda_reg)