class_docstr: L1 regularizer.
  
  >>> reg = snt.regularizers.L1(0.01)
  >>> reg([tf.constant([1.0, 2.0, 3.0])])
  <tf.Tensor: ...>
docstr: Create an L1 regularizer.
  
  Args:
    scale: A non-negative regularization factor.
  
  Raises:
    ValueError: if scale is <0.
docstr_tok: ["Create","an","L1","regularizer",".","Args",":","scale",":","A","non-negative","regularization","factor",".","Raises",":","ValueError",":","if","scale","is","<","0","."]
code: def __init__(self, scale: types.FloatLike):
      """Create an L1 regularizer.
  
      Args:
        scale: A non-negative regularization factor.
  
      Raises:
        ValueError: if scale is <0.
      """
      _check_scale(scale)
      self.scale = scale
  
imports: import abc
  from typing import Sequence
  from sonnet.src import types
  import tensorflow
label_desc: Use image node_id 1 to create a new L1 object from inherited base classes: Regularizer with example: obj = L1(scale)