features = convert_lst_to_features(msg, self.max_seq_len, self.tokenizer)
input_fn = input_fn_builder(features, self.max_seq_len, self.batch_size)
result = []
for r in Estimator(self.model_fn).predict(input_fn):
result.append([round(float(x), 8) for x in r["pooled"].flat])
worker.send_multipart([ident, pickle.dumps(result)])
logger.info("worker %d: encoding %d strings in %.4fs speed: %d/s" % (self.id,
len(msg), time.time() - start_t,