def main(unused_argv):
del unused_argv # Unused
corpus = get_lm_corpus(FLAGS.data_dir, FLAGS.dataset)
save_dir = os.path.join(FLAGS.data_dir, "tfrecords")
if not exists(save_dir):
makedirs(save_dir)
# test mode
if FLAGS.per_host_test_bsz > 0:
corpus.convert_to_tfrecords("test",
save_dir,
FLAGS.per_host_test_bsz,
FLAGS.tgt_len,
FLAGS.num_core_per_host,
FLAGS=FLAGS)
return
for split, batch_size in zip(
["train", "valid"],
[FLAGS.per_host_train_bsz, FLAGS.per_host_valid_bsz]):
if batch_size <= 0: continue
print("Converting {} set...".format(split))
corpus.convert_to_tfrecords(split,
save_dir,
batch_size,
FLAGS.tgt_len,
FLAGS.num_core_per_host,
FLAGS=FLAGS)
def main(unused_argv):
del unused_argv # Unused
corpus = get_lm_corpus(FLAGS.data_dir, FLAGS.dataset)
save_dir = os.path.join(FLAGS.data_dir, "tfrecords")
if not exists(save_dir):
makedirs(save_dir)
# # test mode
if FLAGS.per_host_test_bsz > 0:
corpus.convert_to_tfrecords("test",
save_dir,
FLAGS.per_host_test_bsz,
FLAGS.tgt_len,
FLAGS.num_core_per_host,
FLAGS=FLAGS)
return
for split, batch_size in zip(
["train", "valid"],
[FLAGS.per_host_train_bsz, FLAGS.per_host_valid_bsz]):
if batch_size <= 0: continue
print("Converting {} set...".format(split))
corpus.convert_to_tfrecords(split,
save_dir,
batch_size,
FLAGS.tgt_len,
FLAGS.num_core_per_host,
FLAGS=FLAGS)
fn = os.path.join(FLAGS.data_dir, "cache.pkl")
print("Saving dataset...")
with open(fn, "wb") as fp:
pickle.dump(corpus, fp, protocol=2)