exc = exc.children[1].children[0].clone() IndexError: tuple index out of range on futurize --stage1 -w

[noamzilo]

running

futurize --stage1 -w C:\code\EPMD\Kodex-1.4.6a\Algorithms\src\python\epmd\

gives me the following error:

File "C:\code\epmd\futurize\venv\Scripts\futurize-script.py", line 11, in
load_entry_point('future==0.18.2', 'console_scripts', 'futurize')()
File "C:\code\EPMD\futurize\venv\lib\site-packages\libfuturize\main.py", line 313, in main
options.processes)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 687, in refactor
items, write, doctests_only)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 280, in refactor
self.refactor_dir(dir_or_file, write, doctests_only)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 300, in refactor_dir
self.refactor_file(fullname, write, doctests_only)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 728, in refactor_file
*args, **kwargs)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 335, in refactor_file
tree = self.refactor_string(input, filename)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 367, in refactor_string
self.refactor_tree(tree, name)
File "C:\Program Files\Python37\lib\lib2to3\refactor.py", line 441, in refactor_tree
new = fixer.transform(node, results)
File "C:\code\EPMD\futurize\venv\lib\site-packages\libfuturize\fixes\fix_raise.py", line 61, in transform
exc = exc.children[1].children[0].clone()
IndexError: tuple index out of range

on the following file:

# -*- coding: utf-8 -*-
"""
Created on Mon Apr 18 13:37:52 2016

@author: aaaaaa
"""

import numpy as np


def l_test(Mtst ,input_param_mean, input_param_std, MODEL):
    
    L = np.shape(Mtst)[0]
    
    test_mat_mean = np.tile(input_param_mean, (L, 1))
    
    test_mat_std = np.tile(input_param_std, (L, 1))
    
    Mtst = (Mtst-0*test_mat_mean)  #/test_mat_std
    
    test_est = MODEL.predict(Mtst)
    
    return [test_est]

Would love some assistance here :)

[noamzilo]

commenting out all of the code does pass.

however, the following does not:

import numpy as np

def l_test(m_test, input_param_mean, input_param_std, model):
    #
    #     length = np.shape(m_test)[0]
    #
    #     test_mat_mean = np.tile(input_param_mean, (length, 1))
    #
    #     m_test = (m_test - 0 * test_mat_mean)
    #
    #     test_est = model.predict(m_test)
    #
    #     return [test_est]
    #
    return 0

with the same error

Also this fails:

def l_test(m_test, input_param_mean, input_param_std, model):

    return 0