def get_gen_results(args):
# -get param-stamp
param_stamp = get_param_stamp_from_args(args)
# -check whether already run, and if not do so
eval_tag = "" if args.eval_tag == "none" else "-{}".format(args.eval_tag)
if not os.path.isfile("{}/prec-{}.txt".format(args.r_dir, param_stamp)):
print("{}: ...running...".format(param_stamp))
args.train = True
main_cl.run(args)
elif (os.path.isfile("{}/ll-{}.txt".format(args.r_dir, param_stamp))
and os.path.isfile("{}/is{}-{}.txt".format(args.r_dir, eval_tag,
param_stamp))):
print("{}: already run".format(param_stamp))
else:
print("{}: ...running evaluation only...".format(param_stamp))
args.train = False
main_cl.run(args)
# -get average precisions
fileName = '{}/prec-{}.txt'.format(args.r_dir, param_stamp)
file = open(fileName)
ave = float(file.readline())
file.close()
# -get log-likelihoods
fileName = '{}/ll-{}.txt'.format(args.r_dir, param_stamp)
file = open(fileName)
ll = float(file.readline())
file.close()
# -get reconstruction error (per input unit)
fileName = '{}/re-{}.txt'.format(args.r_dir, param_stamp)
file = open(fileName)
re = float(file.readline())
file.close()
# -get inception score
fileName = '{}/is{}-{}.txt'.format(args.r_dir, eval_tag, param_stamp)
file = open(fileName)
IS = float(file.readline())
file.close()
# -get Frechet inception distance
fileName = '{}/fid{}-{}.txt'.format(args.r_dir, eval_tag, param_stamp)
file = open(fileName)
FID = float(file.readline())
file.close()
# -get precision and recall curve
file_name = '{}/precision{}-{}.txt'.format(args.r_dir, eval_tag,
param_stamp)
precision = []
with open(file_name, 'r') as f:
for line in f:
precision.append(float(line[:-1]))
file_name = '{}/recall{}-{}.txt'.format(args.r_dir, eval_tag, param_stamp)
recall = []
with open(file_name, 'r') as f:
for line in f:
recall.append(float(line[:-1]))
# -return tuple with the results
return (ave, ll, re, IS, FID, precision, recall)
def get_results(args, model_name, shift, slot):
# -get param-stamp
param_stamp = get_param_stamp_from_args(args)
# -check whether already run; if not do so
if os.path.isfile('{}/dict-{}-{}-{}.pkl'.format(args.r_dir, param_stamp,
args.slot, args.shift)):
print("{}: already run".format(param_stamp))
else:
print("{}: ...running...".format(param_stamp))
args.metrics = True
main_cl.run(args, model_name=model_name, shift=shift, slot=slot)
'''# -get average precision
def get_result(args):
# -get param-stamp
param_stamp = get_param_stamp_from_args(args)
# -check whether already run, and if not do so
if os.path.isfile('{}/prec-{}.txt'.format(args.r_dir, param_stamp)):
print("{}: already run".format(param_stamp))
else:
print("{}: ...running...".format(param_stamp))
main_cl.run(args)
# -get average precision
fileName = '{}/prec-{}.txt'.format(args.r_dir, param_stamp)
file = open(fileName)
ave = float(file.readline())
file.close()
# -return it
return ave
def get_results(args):
# -get param-stamp
param_stamp = get_param_stamp_from_args(args)
# -check whether already run, and if not do so
if os.path.isfile("{}/dict-{}.pkl".format(args.r_dir, param_stamp)):
print("{}: already run".format(param_stamp))
else:
print("{}: ...running...".format(param_stamp))
main_cl.run(args)
# -get average precisions
fileName = '{}/prec-{}.txt'.format(args.r_dir, param_stamp)
file = open(fileName)
ave = float(file.readline())
file.close()
# -results-dict
dict = utils.load_object("{}/dict-{}".format(args.r_dir, param_stamp))
# -return tuple with the results
return (dict, ave)
def get_results(args):
# -get param-stamp
param_stamp = get_param_stamp_from_args(args)
# -check whether already run; if not do so
if os.path.isfile('{}/dict-{}.pkl'.format(args.r_dir, param_stamp)):
print("{}: already run".format(param_stamp))
else:
print("{}: ...running...".format(param_stamp))
args.metrics = True
main_cl.run(args)
# -get average precision
file_name = '{}/prec-{}.txt'.format(args.r_dir, param_stamp)
file = open(file_name)
ave = float(file.readline())
file.close()
# -get metrics-dict
file_name = '{}/dict-{}'.format(args.r_dir, param_stamp)
metrics_dict = utils.load_object(file_name)
# -print average precision on screen
print("--> average precision: {}".format(ave))
# -return average precision & metrics-dict
return (ave, metrics_dict)