code: def parse_tadm_weights(paramfile):
      """
      Given the stdout output generated by ``tadm`` when training a
      model, return a ``numpy`` array containing the corresponding weight
      vector.
      """
      weights = []
      for line in paramfile:
          weights.append(float(line.strip()))
      return numpy.array(weights, "d")
  
file_path: nltk/nltk/classify/tadm.py
imports: import subprocess
  import sys
  from nltk.internals import find_binary
label_desc: Use image node_id 3 for calling a global function with example usage: parse_tadm_weights(paramfile) and returns: numpy