args = parser.parse_args()
P.enable_static()
if not os.path.exists(args.from_pretrained):
raise ValueError('--from_pretrained not found: %s' %
args.from_pretrained)
cfg_file_path = os.path.join(args.from_pretrained, 'ernie_config.json')
param_path = os.path.join(args.from_pretrained, 'params')
vocab_path = os.path.join(args.from_pretrained, 'vocab.txt')
assert os.path.exists(cfg_file_path) and os.path.exists(
param_path) and os.path.exists(vocab_path)
hparams_cli = propeller.parse_hparam(args)
hparams_config_file = json.loads(open(cfg_file_path).read())
default_hparams = propeller.HParams(batch_size=32,
num_labels=3,
warmup_proportion=0.1,
learning_rate=5e-5,
weight_decay=0.01,
use_task_id=False,
use_fp16=args.use_amp)
hparams = default_hparams.join(
propeller.HParams(**hparams_config_file)).join(hparams_cli)
default_run_config = dict(max_steps=args.epoch * 390000 /
hparams.batch_size,
save_steps=1000,
return {'acc': acc}
if __name__ == '__main__':
parser = propeller.ArgumentParser('distill model with ERNIE')
parser.add_argument('--max_seqlen', type=int, default=128)
parser.add_argument('--vocab_file', type=str, required=True)
parser.add_argument('--teacher_vocab_file', type=str, required=True)
parser.add_argument('--teacher_max_seqlen', type=int, default=128)
parser.add_argument('--data_dir', type=str)
parser.add_argument('--server_batch_size', type=int, default=64)
parser.add_argument('--num_coroutine', type=int, default=1)
parser.add_argument('--teacher_host', type=str, required=True)
args = parser.parse_args()
run_config = propeller.parse_runconfig(args)
hparams = propeller.parse_hparam(args)
teacher_vocab = {
j.strip().split(b'\t')[0].decode('utf8'): i
for i, j in enumerate(open(args.teacher_vocab_file, 'rb'))
}
vocab = {
j.strip().split(b'\t')[0].decode('utf8'): i
for i, j in enumerate(open(args.vocab_file, 'rb'))
}
teacher_sep_id = teacher_vocab['[SEP]']
teacher_cls_id = teacher_vocab['[CLS]']
teacher_unk_id = teacher_vocab['[UNK]']
unk_id = vocab['[UNK]']
char_tokenizer = utils.data.CharTokenizer(vocab.keys())