def log(self, log_dict, step=None):
"""
step | time stamp | val01 | val02 | val03
0
-
1
-
Appending new column is much easier than appending new row.
Args:
log_dict:
step:
"""
self.df = pandas.read_csv(self.path, index_col=0)
time_stamp = get_time_stamp()
# create data dict for adding new data to csv file
datadict = OrderedDict()
if (self.mode=='train') or (self.mode=='val'):
datadict['step'] = int(step)
datadict['time stamp'] = time_stamp
for k,v in log_dict.items():
datadict[k] = v
new_df = pandas.DataFrame(datadict, index=[self.row_idx])
self.df = self.df.append(new_df, sort=False)
self._save()
self.row_idx += 1
def test_logger():
log_path_root = '/home/gatheluck/Scratch/selectivenet/logs'
log_basename = 'log_test_'+get_time_stamp('short')
log_path = os.path.join(log_path_root, log_basename)
logger = Logger(log_path)
log_dict = {'loss01':1.0, 'loss02':2.0}
log_dict_ = {'loss01':1.0, 'loss03':3.0}
logger.log(log_dict, 1)
logger.log(log_dict, 2)
logger.log(log_dict, 3)
logger.log(log_dict_, 4)
datadict = OrderedDict()
if (self.mode=='train') or (self.mode=='val'):
datadict['step'] = int(step)
datadict['time stamp'] = time_stamp
for k,v in log_dict.items():
datadict[k] = v
new_df = pandas.DataFrame(datadict, index=[self.row_idx])
self.df = self.df.append(new_df, sort=False)
self._save()
self.row_idx += 1
def _save(self):
self.df.to_csv(self.path)
if __name__ == '__main__':
log_path_root = '/home/gatheluck/Scratch/selectivenet/logs'
log_basename = 'log_test_'+get_time_stamp('short')
log_path = os.path.join(log_path_root, log_basename)
logger = Logger(log_path)
log_dict = {'loss01':1.0, 'loss02':2.0}
log_dict_ = {'loss01':1.0, 'loss03':3.0}
logger.log(log_dict, 1)
logger.log(log_dict, 2)
logger.log(log_dict, 3)
logger.log(log_dict_, 4)