class_docstr: The Trimmed Lasso: Sparsity and Robustness. https://arxiv.org/abs/1708.04527
class_docstr_tok: ["The","Trimmed","Lasso",":","Sparsity","and","Robustness",".","https",":","\/\/arxiv.org\/abs\/1708.04527"]
code: def __init__(self, reg_lambda, k):
      super().__init__()
      assert (
          reg_lambda >= 0
      ), "factor ahead of regularization should be 0 or positive"
      assert isinstance(
          k, int
      ), "k should be an interger as expected #. after selection"
      assert k >= 1, "k should be larger than 1"
  
      self.reg_lambda = reg_lambda
      self.k = k
  
imports: from caffe2.python import core, utils
  import numpy
label_desc: Use image node_id 1 to create a new L1NormTrimmed object from inherited base classes: Regularizer with example: obj = L1NormTrimmed(reg_lambda, k)