def execute_parallel_baseline_1_max_tree(language,
train_models=False,
is_train_dev_together=True):
if (train_models):
logging.info('-' * 50)
logging.info('Training process started')
tp.train_parser_all_lng(language, is_train_dev_together)
logging.info('Training process ended')
logging.info('-' * 50)
logging.info('Noised dependency trees creation started')
noise_maker.create_noised_dps_over_all_languages(
language, is_train_dev_together)
logging.info('Noised dependency trees creation ended')
logging.info('-' * 50)
logging.info('mst wrapper started')
mst_wrapper.mst_wrapper_for_all_languages(
language,
final_file_name='final_liang_1_best_after_predicted_pos',
is_train_dev_together=is_train_dev_together,
is_mst=False,
given_one_file_repeated_sentnces=False)
logging.info('mst wrapper ended')
return language + " is ready"
def execute_parallel_baseline_k_best_trees(language,train_models = False,is_train_dev_together=True):
if (train_models):
logging.info('-'*50)
logging.info('Training process started')
tp.train_parser_all_lng(language,is_train_dev_together)
logging.info('Training process ended')
logging.info('-' * 50)
logging.info('K-best (liang) dependency trees creation started')
noise_maker.create_noised_dps_over_all_languages(specific_languages = language,
is_train_dev_together=True,
k_best_baseline = 100)
logging.info('K-best (liang) dependency trees creation ended')
logging.info('-' * 50)
logging.info('mst wrapper started')
mst_wrapper.mst_wrapper_for_all_languages(language,
final_file_name='UAS_liang_Kbest_baseline_k_100_after_predicted_pos',
is_train_dev_together = is_train_dev_together,
is_mst=True,
given_one_file_repeated_sentnces=True)
logging.info('mst wrapper ended')
logging.info('-' * 50)
logging.info('Oracle wrapper started')
oracle_wrapper.oracle_wrapper_for_all_languages(language,final_file_name = 'UAS_liang_Kbest_baseline_k_100_after_predicted_pos' ,is_train_dev_together=True)
logging.info('Oracle wrapper ended')
return language+" is ready"
def execute_parallel(language,eval_method='oracle',train_models = True,find_noise = True,is_oracle_inference_results=True,fixed_noise=False,noise_method='m'):
if (train_models):
logging.info('-'*50)
logging.info('Training process started')
tp.train_parser_all_lng(language)
logging.info('Training process ended')
if (find_noise):
logging.info('-' * 50)
logging.info('Optimal noise learning started')
optimal_n.find_optimal_noise_per_language(eval_method=eval_method,specific_languages=language,noise_method=noise_method)
logging.info('Optimal noise learning ended')
logging.info('-' * 50)
logging.info('Noised dependency trees creation started')
noise_maker.create_noised_dps_over_all_languages(language,is_train_dev_together= False,k_best_baseline=False,fixed_noise=fixed_noise,noise_method=noise_method)
logging.info('Noised dependency trees creation ended')
logging.info('-' * 50)
logging.info('mst wrapper started')
mst_wrapper.mst_wrapper_for_all_languages(language,
final_file_name='UAS_perturbated_MLN_perturbated_after_predicted_pos',
is_train_dev_together=False,
is_mst=True,
given_one_file_repeated_sentnces=False,
remove_less_than_k_duplication=False)
logging.info('mst wrapper ended')
if (is_oracle_inference_results):
logging.info('Oracle wrapper started')
oracle_wrapper.oracle_wrapper_for_all_languages(language,final_file_name = 'UAS_perturbated_MLN_perturbated_after_predicted_pos' ,is_train_dev_together=False)
logging.info('Oracle wrapper ended')
return language+" is ready"
def execute(self):
logging.info('Execution started')
if (self.create_files):
logging.info('Strat creating per language files')
tp.create_files_per_language()
logging.info('Finish creating per language files')
if (self.train_models):
logging.info('-'*50)
logging.info('Training process started')
tp.train_parser_all_lng()
logging.info('Training process ended')
logging.info('-' * 50)
logging.info('Optimal noise learning started')
optimal_n.find_optimal_noise_per_language()
logging.info('Optimal noise learning ended')
logging.info('-' * 50)
logging.info('Noised dependency trees creation started')
noise_maker.create_noised_dps_over_all_languages()
logging.info('Noised dependency trees creation ended')
logging.info('-' * 50)
logging.info('mst wrapper started')
mst_wrapper.mst_wrapper_for_all_languages()
logging.info('Nmst wrapper ended')
def execute_parallel(
language,
eval_method='unsupervised_min_sim_between_max_sim_to_1best',
train_models=False,
find_noise=True,
is_oracle_inference_results=True,
fixed_noise=False,
noise_method='m'):
if (train_models):
logging.info('-' * 50)
logging.info('Training process started')
tp.train_parser_all_lng(language,
is_train_dev_together,
with_words=True)
logging.info('Training process ended')
if (find_noise and not fixed_noise):
logging.info('-' * 50)
logging.info('Optimal noise learning started')
optimal_n.find_optimal_noise_per_language(
eval_method=eval_method,
specific_languages=language,
noise_method=noise_method,
weight_sim_1best=0.5,
weight_sim_between=0.5)
logging.info('Optimal noise learning ended')
logging.info('-' * 50)
logging.info('Noised dependency trees creation started')
noise_maker.create_noised_dps_over_all_languages(
language,
is_train_dev_together=False,
k_best_baseline=False,
fixed_noise=fixed_noise,
noise_method=noise_method)
logging.info('Noised dependency trees creation ended')
logging.info('-' * 50)
logging.info('mst wrapper started')
mst_wrapper.mst_wrapper_for_all_languages(
language,
final_file_name='UAS_perturbated_k_100_MLN_FULL_mono_lingual',
is_train_dev_together=False,
is_mst=True,
given_one_file_repeated_sentnces=False)
logging.info('mst wrapper ended')
if (is_oracle_inference_results):
logging.info('Oracle wrapper started')
oracle_wrapper.oracle_wrapper_for_all_languages(
language,
final_file_name='UAS_perturbated_k_100_MLN_FULL_mono_lingual',
is_train_dev_together=False)
logging.info('Oracle wrapper ended')
return language + " is ready"