def run(args):
data = loader.load_treebanks(TREEBANK_PATH)
train_data, dev_data, test_data = loader.train_test_split(
data, 0.8, 0.1, 0.1)
words, embeddings = loader.load_word_embeddings(EMBEDDING_PATH)
pcfg = PCFG(train_data)
pcfg.train(train_data)
pcfg.set_oov(OOV, words, embeddings)
if args.generate_output:
output = pcfg.generate_output(test_data)
if args.evaluation:
accs, nb_no_parse = pcfg.predict(test_data[:2])
if args.parse:
corpus = []
with open(args.txt_path, 'r') as f:
corpus = f.read().split('\n')
pcfg.parse_from_txt(corpus)
def run(args):
has_effect = False
if args:
try:
train_corpus, val_corpus, test_corpus = data.get_train_val_test()
words, embeddings = data.get_polyglot_words_embeddings()
parser = PCFG()
parser.learn_probabilities_and_rules(train_corpus)
parser.set_oov_module(OovModule, words, embeddings)
if args.inference:
get_gold(parser, test_corpus, filename='evaluation_data.gold')
get_predictions(parser,
test_corpus,
filename='evaluation_data.parser_output')
if args.evaluation:
evaluation('evaluation_data.gold',
'evaluation_data.parser_output')
if args.parse:
parser.parse_from_txt(args.txt_path)
except Exception as e:
logger.exception(e)
logger.error("Uhoh, the script halted with an error.")
else:
if not has_effect:
logger.error(
"Script halted without any effect. To run code, use command:\npython3 main.py <args>"
)