code: def gross_lev(positions):
      """
      Calculates the gross leverage of a strategy.
  
      Parameters
      ----------
      positions : pd.DataFrame
          Daily net position values.
           - See full explanation in tears.create_full_tear_sheet.
  
      Returns
      -------
      pd.Series
          Gross leverage.
      """
  
      exposure = positions.drop("cash", axis=1).abs().sum(axis=1)
      return exposure / positions.sum(axis=1)
  
imports: from __future__ import division
  from collections import OrderedDict
  from functools import partial
  import empyrical
  import numpy
  import pandas
  import scipy
  import scipy.stats
  from sklearn import linear_model
  from .deprecate import deprecated
  from .interesting_periods import PERIODS
  from .txn import get_turnover
  from .utils import APPROX_BDAYS_PER_MONTH, APPROX_BDAYS_PER_YEAR
  from .utils import DAILY
label_desc: Use image node_id 21 for calling a global function with example usage: gross_lev(positions) and returns: unknown