def preprocess(self, batch): q_seq, history, label = to_batch_seq(batch) q_emb_var, q_len = self.embed_layer.gen_x_q_batch(q_seq) hs_emb_var, hs_len = self.embed_layer.gen_x_history_batch(history) col_seq, tab_seq, par_tab_nums, foreign_keys = to_batch_tables( batch, self.table_type) from_candidates = to_batch_from_candidates(par_tab_nums, batch) col_emb_var, col_name_len, col_len = self.embed_layer.gen_col_batch( col_seq) input_data = (q_emb_var, q_len, hs_emb_var, hs_len, col_emb_var, col_len, col_name_len, from_candidates) gt_data = label return input_data, gt_data
def preprocess(self, batch): q_seq, history, label = to_batch_seq(batch) q_emb_var, q_len = self.embed_layer.gen_x_q_batch(q_seq) hs_emb_var, hs_len = self.embed_layer.gen_x_history_batch(history) col_seq, tab_seq, par_tab_nums, foreign_keys = to_batch_tables(batch, self.table_type) col_emb_var, col_name_len, col_len = self.embed_layer.gen_col_batch(col_seq) gt_col = np.zeros(q_len.shape, dtype=np.int64) index = 0 for item in batch: gt_col[index] = item["gt_col"] index += 1 input_data = (q_emb_var, q_len, hs_emb_var, hs_len, col_emb_var, col_len, col_name_len, gt_col) gt_data = label return input_data, gt_data