code: def e_step(X, inv_cov, means, weights):
      xp = cupy.get_array_module(X)
      weighted_log_prob = estimate_log_prob(X, inv_cov, means) + xp.log(
          weights
      )
      log_prob_norm = xp.log(xp.sum(xp.exp(weighted_log_prob), axis=1))
      log_resp = weighted_log_prob - log_prob_norm[:, None]
      return xp.mean(log_prob_norm), log_resp
  
file_path: cupy/examples/gmm/gmm.py
imports: import argparse
  import contextlib
  import time
  import matplotlib.pyplot
  import numpy
  from scipy import stats
  import cupy
label_desc: Use image node_id 4 for calling a global function with example usage: e_step(X, inv_cov, means, weights) and returns: xp,  log_resp