def metadata_initial_iofiles(config, dct=None):
    if dct is None:
        dct = {}

    path2iofile = {f.path: n
                   for n, f in iteritems(config.inputs_outputs)
                   if f.read_runs}

    def packed_files():
        yield config.other_files
        for pkg in config.packages:
            if pkg.packfiles:
                yield pkg.files

    for f in itertools.chain.from_iterable(packed_files()):
        f = f.path
        path2iofile.pop(f, None)

    dct['input_files'] = dict((n, False) for n in itervalues(path2iofile))

    return dct
The function to predict (classification will then consist in predicting
dataset/ETHPy150Open ViDA-NYU/reprozip/reprounzip/reprounzip/unpackers/common/misc.py/metadata_initial_iofiles--crossover with--dataset/ETHPy150Open scikit-learn/scikit-learn/examples/gaussian_process/plot_gpc_isoprobability.py/g