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
