code: def get_max_squared_sum(X):
      """Get the maximum row-wise sum of squares"""
      return np.sum(X**2, axis=1).max()
  
file_path: scikit-learn/benchmarks/bench_rcv1_logreg_convergence.py
imports: import gc
  import time
  import matplotlib.pyplot
  import numpy
  from joblib import Memory
  from sklearn.datasets import fetch_rcv1
  from sklearn.linear_model import LogisticRegression, SGDClassifier
  from sklearn.linear_model._sag import get_auto_step_size
label_desc: Use image node_id 8 for calling a global function with example usage: get_max_squared_sum(X) and returns: np