生成batch代码：

def generate_batch(self, batch_size):
	#根据已有的数据self 生成各种需要的数组
    if self.shuffle:
        shuffled_arg = np.arange(self.length)
        np.random.shuffle(shuffled_arg)
        self.inputs = self.inputs[shuffled_arg]
        self.mask = self.mask[shuffled_arg]
        self.targets = self.targets[shuffled_arg]
    n_batch = int(self.length / batch_size)
    #计算batch长度
    if self.length % batch_size != 0:
        n_batch += 1
    #分割batch
    slices = np.split(np.arange(n_batch * batch_size), n_batch)
    #最后这个batch要重新换成有数据index
    slices[-1] = np.arange(self.length-batch_size, self.length)
    pdb.set_trace()
    return slices

最后一个batch：
可见和上一个batch有很多重复数据，防止最后一组数据越界

 array([1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110,
       1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121,
       1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132,
       1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143,
       1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154,
       1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165,
       1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176,
       1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187,
       1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198,
       1199]), 
       array([1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115,
       1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126,
       1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137,
       1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148,
       1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159,
       1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170,
       1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181,
       1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192,
       1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203,
       1204])]