class_docstr: A regularizer that applies a L1 regularization penalty.
  
  The L1 regularization penalty is computed as:
  `loss = l1 * reduce_sum(abs(x))`
  
  L1 may be passed to a layer as a string identifier:
  
  >>> dense = tf.keras.layers.Dense(3, kernel_regularizer='l1')
  
  In this case, the default value used is `l1=0.01`.
  
  Attributes:
      l1: Float; L1 regularization factor.
code: def __call__(self, x):
      return self.l1 * math_ops.reduce_sum(math_ops.abs(x))
  
imports: import math
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.utils.generic_utils import deserialize_keras_object
  from tensorflow.python.keras.utils.generic_utils import serialize_keras_object
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 2 for calling the L1 obj's underlying member method code with example usage: obj.__call__(x) and returns: unknown