def get_time_for_files(translator, pairs,split_type='none'):
times = []
print(len(pairs))
for pair in pairs:
single_time = get_time_for_single(translator,pair,split_type)
write_to_log("Time = {}".format(single_time))
times.append(single_time)
return times
def get_results(omega, model_num=2, split_type="none", fm_flag=False):
med_results = []
norm_med_results = []
bow_results = []
for pair in test_train_split:
train = get_splits(pair[1], split_type)
test = get_splits(pair[0], split_type)
translator = get_translator(train, omega, fm_flag, model_num)
med, bow, norm_med = useful_functions.get_med_bow_norm(
translator, test)
write_to_log("Edit distance = {}\n".format(med))
med_results.append(med)
bow_results.append(bow)
norm_med_results.append(norm_med)
return med_results, bow_results, norm_med_results
def get_med_bow_norm(translator,test_set):
meds = 0
bows = 0
meds_per_tok = 0
for ts, truth in test_set:
predict = translator(ts)
pred_str = " ".join(predict)
write_to_log("predict: "+pred_str+"\n")
# print(pred_str)
med = minimum_edit_distance(predict, truth)
# write_to_log(str(med)+"\n")
meds += med
bows += bag_of_words_test(predict, truth)
meds_per_tok += minimum_edit_distance_per_token(predict, truth)
return meds,bows,meds_per_tok/len(test_set)
def validate_ibmmodel(omega_range,
model_num=2,
split_type="none",
fm_flag=False):
print("Validate ibmmodel{}".format(model_num))
preprocessed_train = get_splits(train_test_data, split_type)
preprocessed_valid = get_splits(validation_set, split_type)
results = []
for omega in omega_range:
message = "omega {}\n".format(omega)
write_to_log(message)
print("omega", omega)
translator = get_translator(preprocessed_train, omega, fm_flag,
model_num)
med, _, _ = useful_functions.get_med_bow_norm(translator,
preprocessed_valid)
print(med)
write_to_log("Edit distance = {}\n".format(med))
results.append((omega, med))
return results
# med,bow,norm = get_results_from_file("logs/results_enhanced.txt","enhanced")
# print(med)
# print(bow)
# print(norm)
# med = [199, 118, 170, 280, 115, 184, 75, 58, 161]
# bl_med =[161, 107, 134, 187, 89, 137, 88, 80, 129]
# print(sum(med))
# print(sum(bl_med))
test_num = 3
if test_num == 0:
message = "omega v1 100"
print(message)
write_to_log(message)
decoder_with_log.beam_size = 100
omegas = [3.0, 2.7, 2.3]
validate_ibmmodel(omegas, 1, "none", False)
elif test_num == 1:
message = "enhanced omega v2"
print(message)
write_to_log(message)
omegas = [3.0]
validate_ibmmodel(omegas, 2, "enhanced", True)
elif test_num == 2:
message = "results split v2"
print(message)
write_to_log(message)
split_v2_omega = 2.9
get_results(split_v2_omega, 2, "split", False)