def get_infos(self):
first_dim_factor = self.first_dim_factor<EOL>infos = {'<STR_LIT>': [], '<STR_LIT>': self.stats,<EOL>'<STR_LIT>': first_dim_factor}<EOL>for cache_level, cache_info in list(enumerate(self.machine['<STR_LIT>'])):<EOL><INDENT>infos['<STR_LIT>'].append({<EOL>'<STR_LIT:index>': len(infos['<STR_LIT>']),<EOL>'<STR_LIT>': '<STR_LIT:{}>'.format(cache_info['<STR_LIT>']),<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': self.stats[cache_level]['<STR_LIT>']/first_dim_factor,<EOL>'<STR_LIT>': None})<EOL><DEDENT>return infos<EOL>
Return verbose information about the predictor.