def write_epoch(self, cur_epoch):
basic_stats = self.basic()
# Try to load customized metrics
task_stats = {}
for custom_metric in cfg.custom_metrics:
func = register.metric_dict.get(custom_metric)
if not func:
raise ValueError(
f'Unknown custom metric function name: {custom_metric}')
custom_metric_score = func(self._true, self._pred, self.task_type)
task_stats[custom_metric] = custom_metric_score
if not task_stats: # use default metrics if no matching custom metric
if self.task_type == 'regression':
task_stats = self.regression()
elif self.task_type == 'classification_binary':
task_stats = self.classification_binary()
elif self.task_type == 'classification_multi':
task_stats = self.classification_multi()
else:
raise ValueError('Task has to be regression or classification')
epoch_stats = {'epoch': cur_epoch}
eta_stats = {'eta': round(self.eta(cur_epoch), cfg.round)}
custom_stats = self.custom()
if self.name == 'train':
stats = {
**epoch_stats,
**eta_stats,
**basic_stats,
**task_stats,
**custom_stats
}
else:
stats = {
**epoch_stats,
**basic_stats,
**task_stats,
**custom_stats
}
# print
logging.info('{}: {}'.format(self.name, stats))
# json
dict_to_json(stats, '{}/stats.json'.format(self.out_dir))
# tensorboard
if cfg.tensorboard_each_run:
dict_to_tb(stats, self.tb_writer, cur_epoch)
self.reset()
def write_epoch(self, cur_epoch):
basic_stats = self.basic()
if self.task_type == 'regression':
task_stats = self.regression()
elif self.task_type == 'classification_binary':
task_stats = self.classification_binary()
elif self.task_type == 'classification_multi':
task_stats = self.classification_multi()
else:
raise ValueError('Task has to be regression or classification')
epoch_stats = {'epoch': cur_epoch}
eta_stats = {'eta': round(self.eta(cur_epoch), cfg.round)}
custom_stats = self.custom()
if self.name == 'train':
stats = {
**epoch_stats,
**eta_stats,
**basic_stats,
**task_stats,
**custom_stats
}
else:
stats = {
**epoch_stats,
**basic_stats,
**task_stats,
**custom_stats
}
# print
logging.info('{}: {}'.format(self.name, stats))
# json
dict_to_json(stats, '{}/stats.json'.format(self.out_dir))
# tensorboard
if cfg.tensorboard_each_run:
dict_to_tb(stats, self.tb_writer, cur_epoch)
self.reset()