code: def l1_loss(tensor, weight=1.0, scope=None):
    
    with tf.name_scope(scope, 'L1Loss', [tensor]):
      weight = tf.convert_to_tensor(weight,
                                    dtype=tensor.dtype.base_dtype,
                                    name='loss_weight')
      loss = tf.multiply(weight, tf.reduce_sum(tf.abs(tensor)), name='value')
      tf.add_to_collection(LOSSES_COLLECTION, loss)
      return loss
docs: Define a L1Loss, useful for regularize, i.e. lasso.
  
    Args:
      tensor: tensor to regularize.
      weight: scale the loss by this factor.
      scope: Optional scope for name_scope.
  
    Returns:
      the L1 loss op.