code: def grad_log_sigmoid(vector):
      """Gradient of log sigmoid function.
  
      Parameters
      ----------
      vector : array-like, shape=[n_samples, dim]
  
      Returns
      -------
      gradient : array-like, shape=[n_samples, dim]
      """
      return 1 / (1 + gs.exp(vector))
  
file_path: geomstats/examples/learning_graph_structured_data_h2.py
imports: import logging
  import matplotlib.pyplot
  import geomstats.backend
  import geomstats.visualization
  from geomstats.datasets.utils import load_karate_graph
  from geomstats.geometry.poincare_ball import PoincareBall
label_desc: Use image node_id 2 for calling a global function with example usage: grad_log_sigmoid(vector) and returns: unknown