Update framework.py

framework.py

@@ -22,7 +22,7 @@ def block_sample(X, Z, Y, sample_num, epoch_idx):
     if part_num == 0:
         part_num = 1
     seg_idx = epoch_idx % part_num 
-    INFO("seg_idx:", seg_idx, ", part num:", part_num, ", data num:", len(X_bak))
+    INFO("seg_idx:", seg_idx, ", part num:", part_num, ", data num:", len(X))
     X = X[sample_num * seg_idx: sample_num * (seg_idx + 1)]
     Z = Z[sample_num * seg_idx: sample_num * (seg_idx + 1)]
     Y = Y[sample_num * seg_idx: sample_num * (seg_idx + 1)]
@@ -150,10 +150,12 @@ def train(model, abducer, X, Z, Y, epochs = 10, sample_num = -1, verbose = -1):
         abduced_Z = abduce_func(preds_res, Y)
 
         abl_acc = get_abl_acc(Y, preds_res['cls'], abducer.kb.logic_forward)
-        if(not char_acc_flag):
+        if(char_acc_flag):
             ori_char_acc = get_char_acc(Z, preds_res['cls'])
             abd_char_acc = get_char_acc(abduced_Z, preds_res['cls'])
-        print('epoch_idx:', epoch_idx, '  abl_acc:', abl_acc, '  ori_char_acc:', ori_char_acc, '  abd_char_acc:', abd_char_acc)
+            print('epoch_idx:', epoch_idx, '  abl_acc:', abl_acc, '  ori_char_acc:', ori_char_acc, '  abd_char_acc:', abd_char_acc)
+        else:
+            print('epoch_idx:', epoch_idx, '  abl_acc:', abl_acc)
         
         finetune_X, finetune_Z = filter_data(X, abduced_Z)
         if len(finetune_X) > 0: