def main(_):
logging.init(FLAGS.outfile, mode='w')
text2ids.init()
if FLAGS.add_global_scope:
global_scope = FLAGS.global_scope if FLAGS.global_scope else FLAGS.algo
else:
global_scope = ''
#with tf.variable_scope(FLAGS.algo):
run()
text_strs = []
manager = Manager()
texts_dict = manager.dict()
text_strs_dict = manager.dict()
gtexts = [[]] * FLAGS.threads
gtext_strs = [[]] * FLAGS.threads
#how many records generated
counter = Value('i', 0)
#the max num words of the longest text
max_num_words = Value('i', 0)
#the total words of all text
sum_words = Value('i', 0)
text2ids.init()
def deal_file(file, thread_index):
out_file = '{}/{}_{}'.format(
FLAGS.output_directory, FLAGS.name,
thread_index) if FLAGS.threads > 1 else '{}/{}'.format(
FLAGS.output_directory, FLAGS.name)
print('out_file:', out_file)
with melt.tfrecords.Writer(out_file) as writer:
num = 0
for line in open(file):
if num % 1000 == 0:
print(num)
l = line.rstrip().split('\t')
img = l[0]
def main(_):
text2ids.init()
predictor = melt.Predictor(FLAGS.model_dir)
predict(predictor)