code: def logsumexp(x, axis=0):
      xmax = x.max(axis)
      x = xmax + np.log(
          np.sum(np.exp(x - np.expand_dims(xmax, axis)), axis)
      )
      infs = np.isinf(xmax)
      if np.ndim(x) > 0:
          x[infs] = xmax[infs]
      elif infs:
          x = xmax
      return x
  
file_path: espnet/egs/libri_css/asr1/diarization/VB_diarization.py
imports: import numexpr
  import numpy
  import scipy.linalg
  from scipy.sparse import coo_matrix
label_desc: Use image node_id 5 for calling a global function with example usage: logsumexp(x, axis) and returns: x