def main():
options = read_options()
# Set logging
logger.setLevel(logging.INFO)
fmt = logging.Formatter('%(asctime)s: [ %(message)s ]',
'%m/%d/%Y %I:%M:%S %p')
console = logging.StreamHandler()
console.setFormatter(fmt)
logfile = None
logger.addHandler(console)
# read the vocab files, it will be used by many classes hence global scope
logger.info('reading vocab files...')
relation_vocab = json.load(open(options['vocab_dir'] + '/relation_vocab.json'))
entity_vocab = json.load(open(options['vocab_dir'] + '/entity_vocab.json'))
logger.info('Reading mid to name map')
mid_to_word = {}
# with open('/iesl/canvas/rajarshi/data/RL-Path-RNN/FB15k-237/fb15k_names', 'r') as f:
# mid_to_word = json.load(f)
logger.info('Done..')
logger.info('Total number of entities {}'.format(len(entity_vocab)))
logger.info('Total number of relations {}'.format(len(relation_vocab)))
save_path = ''
config = tf.ConfigProto()
config.gpu_options.allow_growth = False
config.log_device_placement = False
best_permutation = None
best_acc = 0
for permutation in create_permutations(options):
current_time = datetime.datetime.now()
current_time = current_time.strftime('%y_%b_%d__%H_%M_%S')
permutation['output_dir'] = options['base_output_dir'] + '/' + str(current_time) + '__' + str(uuid.uuid4())[
:4] + '_' + str(
permutation['path_length']) + '_' + str(permutation['beta']) + '_' + str(
permutation['test_rollouts']) + '_' + str(
permutation['Lambda'])
permutation['model_dir'] = permutation['output_dir'] + '/' + 'model/'
permutation['load_model'] = (permutation['load_model'] == 1)
##Logger##
permutation['path_logger_file'] = permutation['output_dir']
permutation['log_file_name'] = permutation['output_dir'] + '/log.txt'
os.makedirs(permutation['output_dir'])
os.mkdir(permutation['model_dir'])
with open(permutation['output_dir'] + '/config.txt', 'w') as out:
pprint(permutation, stream=out)
# print and return
maxLen = max([len(ii) for ii in permutation.keys()])
fmtString = '\t%' + str(maxLen) + 's : %s'
print('Arguments:')
for keyPair in sorted(permutation.items()): print(fmtString % keyPair)
logger.removeHandler(logfile)
logfile = logging.FileHandler(permutation['log_file_name'], 'w')
logfile.setFormatter(fmt)
logger.addHandler(logfile)
permutation['relation_vocab'] = relation_vocab
permutation['entity_vocab'] = entity_vocab
judge = SimpleClassifier(permutation)
judge.construct_graph()
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
judge.train(sess)
logger.info("Hits@10: {0:7.4f}".format(all_final_reward_10))
logger.info("Hits@20: {0:7.4f}".format(all_final_reward_20))
logger.info("auc: {0:7.4f}".format(auc))
def top_k(self, scores, k):
scores = scores.reshape(
-1, k * self.max_num_actions) # [B, (k*max_num_actions)]
idx = np.argsort(scores, axis=1)
idx = idx[:, -k:] # take the last k highest indices # [B , k]
return idx.reshape((-1))
if __name__ == '__main__':
# read command line options
options = read_options()
# Set logging
logger.setLevel(logging.INFO)
fmt = logging.Formatter('%(asctime)s: [ %(message)s ]',
'%m/%d/%Y %I:%M:%S %p')
console = logging.StreamHandler()
console.setFormatter(fmt)
logger.addHandler(console)
logfile = logging.FileHandler(options['log_file_name'], 'w')
logfile.setFormatter(fmt)
logger.addHandler(logfile)
#read dataset
options['dataset'] = {}
Dataset_list = ['train', 'test', 'dev', 'graph']
for dataset in Dataset_list: