code: def main(readcsv=pd_read_csv):
      data_path = Path(__file__).parent / "data" / "batch"
      infile = data_path / "custom.csv"
      # Read the data, let's have 4 independent variables
      data = readcsv(infile, range(4))
      dep_data = readcsv(infile, range(4, 5))
      nVectors = data.shape[0]
  
      # configure a logistic loss object
      ll_algo = d4p.optimization_solver_logistic_loss(
          nVectors, interceptFlag=True
      )
      ll_algo.setup(data, dep_data)
  
      # configure a SGD object
      lrs = np.array([[0.01]], dtype=np.double)
      niters = 1000
      sgd_algo = d4p.optimization_solver_sgd(
          ll_algo,
          learningRateSequence=lrs,
          accuracyThreshold=0.02,
          nIterations=niters,
      )
  
      # finally do the computation
      inp = np.array([[1], [1], [1], [1], [1]], dtype=np.double)
      res = sgd_algo.compute(inp)
  
      # The SGD result provides minimum and nIterations
      assert (
          res.minimum.shape == inp.shape
          and res.nIterations[0][0] <= niters
      )
  
      return res
  
imports: from pathlib import Path
  import numpy
  from readcsv import pd_read_csv
  import daal4py
label_desc: Use image node_id 1 for calling a global function with example usage: main(readcsv) and returns: res