def lp(self, ARG_msg): #log and print message
try:
LOCAL_CallerClassName = str(
inspect.stack()[1][0].f_locals["self"].__class__)
except:
LOCAL_CallerClassName = ""
LOCAL_CallerFunction = inspect.currentframe().f_back.f_code.co_name
if isinstance(ARG_msg, basestring):
ARG_msg = [ARG_msg]
HEADER = "[" + GF.DATETIME_GetNowStr(
) + "] [" + LOCAL_CallerClassName + "." + LOCAL_CallerFunction + "]: "
print HEADER
self._LogFileHandler.write(HEADER + "\n")
for itemstr in ARG_msg:
try:
itemstr = str(itemstr).replace('\r', '\n')
except:
itemstr = itemstr.encode('utf-8').replace('\r', '\n')
for item in itemstr.split("\n"):
if len(item) == 0:
item = "-"
item = " " + item
print item
self._LogFileHandler.write(item + "\n")
print ""
self._LogFileHandler.write("\n")
def lp(ARG_msg):
try:
LOCAL_CallerClassName = str(
inspect.stack()[1][0].f_locals["self"].__class__)
except:
LOCAL_CallerClassName = ""
LOCAL_CallerFunction = inspect.currentframe(
).f_back.f_code.co_name
if isinstance(ARG_msg, basestring):
ARG_msg = [ARG_msg]
HEADER = "[" + GF.DATETIME_GetNowStr(
) + "] [" + LOCAL_CallerClassName + "." + LOCAL_CallerFunction + "]: "
print HEADER
for itemstr in ARG_msg:
itemstr = str(itemstr).replace('\r', '\n')
for item in itemstr.split("\n"):
if len(item) == 0:
item = "-"
item = " " + item
print item
print ""
BestMeasure = 2 #Micro-FScore
BestResults = sorted(self.PredMetricLog,
key=lambda x: x[BestMeasure],
reverse=True)[0]
self.GLOBAL_BEST_DEVEL_PRED_RESULTS.append([arch] + BestResults)
self.lp(["-" * 80, "BEST RESULTS so far:", "-" * 80])
for best_result in sorted(self.GLOBAL_BEST_DEVEL_PRED_RESULTS,
key=lambda x: x[BestMeasure + 1],
reverse=True):
self.lp(str(best_result))
if __name__ == "__main__":
default_logfile_address = os.path.dirname(os.path.realpath(
__file__)) + "/LOGS/" + GF.DATETIME_GetNowStr() + ".txt"
parser = argparse.ArgumentParser(description='keras_4_annotations.py')
parser.add_argument(
'-data_folder',
type=str,
help='Location of the data folder',
default='/home/hanmoe/annotation/text-classification/DATA')
parser.add_argument(
'-ann_set',
type=str,
help=
'What annotation set to use, choices={"kipu", "sekavuus", "infektio"}',
choices=['kipu', 'sekavuus', 'infektio'],
required=True)
parser.add_argument(
'-ann_type',
