class_docstr: State of one execution of the Hungarian algorithm.
  
  Parameters
  ----------
  cost_matrix : 2D matrix
      The cost matrix. Does not have to be square.
class_docstr_tok: ["State","of","one","execution","of","the","Hungarian","algorithm",".","Parameters","--","--","--","--","--","cost_matrix",":","2D","matrix","The","cost","matrix",".","Does","not","have","to","be","square","."]
docstr: Find the first prime element in the specified row. Returns
  the column index, or -1 if no starred element was found.
docstr_tok: ["Find","the","first","prime","element","in","the","specified","row",".","Returns","the","column","index",",","or","-1","if","no","starred","element","was","found","."]
code: def _find_prime_in_row(self, row):
      """
      Find the first prime element in the specified row. Returns
      the column index, or -1 if no starred element was found.
      """
      col = np.argmax(self.marked[row] == 2)
      if self.marked[row, col] != 2:
          col = -1
      return col
  
file_path: catboost/contrib/python/scikit-learn/py2/sklearn/utils/linear_assignment_.py
imports: import numpy
  from .fixes import astype
label_desc: Use image node_id 2 for calling the _HungarianState obj's underlying member method code with example usage: obj._find_prime_in_row(row) and returns: col