2010/05/23-01:36

本文探讨了远离家乡的游子如何在追求个人梦想与成就的同时,平衡对父母的孝顺与陪伴。通过引用《论语》中的古训“父母在,不远游,游必有方”,作者反思了现代年轻人面临的抉择与困境。文章分享了一位朋友从美国归来的故事,以及崔琦院士与父母的故事,引发读者对“子欲养而亲不在”的深刻思考。文中强调了孝顺不仅仅是物质供养,更是情感与精神的关怀,鼓励年轻人在追求自我价值的同时,不忘家庭责任。

      一点多了,又亢奋睡不着了,也许这就是搞IT的特点吧,果断爬下床抱起电脑直奔隔壁自习室~~~前几天看了个帖子说弄IT的要注意身体,少熬夜,但。。。。

    先记录今天的事情吧,早上一大清早的就被老大和嫂子给吵醒了,老大果断各种妻管严,太悲剧了,各种同情他,起来淘出手机以后看欧冠结果(尽管没有自个喜欢的球队,但是还是蛮关注的,毕竟球迷嘛),国米2:0拜仁,三冠王,最近皇马的赛事都结束了,所以打开电脑,看新闻这项基本就免了,要看下也就是稍微关注下时事,没以前的各种泡在西甲皇马区,久久不会离去。

   看完新闻,得学习了,打开CMD->SQLPLUS->SCOTT->ORCL继续学习了,今天还是很荒废,总共弄了个游标。

   中午和徐小妞跑去图书馆了,C#大作业得开始了,去图书馆找下书,数据库开发的书,开始弄了,毕竟又是一个人系着一组人的命运,不能太那个,从大二开始就这样了,老是系着很多人的命运,同时也习惯了。

   下午在宿舍上网了一会,总而言之,无所事事。

   晚上找野猪吃夜宵去了,我们两个都被汉得录取了,但是他一直在纠结之中,要怎么去走自己的路,他是学C++那套的,本身又对数据库很恶心,然后就纠结了。哎,不知道以后的路咋走呢,稳定VS奋斗,每个人都在纠结中,纠结,纠结,找不到工作纠结,找到工作的也纠结,考研的纠结,不考研的也纠结,找到好工作的纠结,人生就是这样啊,但是无论如何,总得做出选择,如果每天都能和好哥们这样喝酒,吃夜宵多好啊。一个月,大学也许就快结束了,开始了吗,开始了吗,记得大一刚来到的时候。。。。。。。。。

  回来装了个SQLSERVER 2005,要弄C#大作业,没的办法,干净弄完,就废掉windows 7,然后果断我的Ubuntu,好好耍耍,由于吃夜宵回来的比较晚,装到断电还没装好,把我急的,赶紧把电脑搬去自习室。

  也许是软件的原因吧,十二点断电以后,才属于我们的夜生活刚开始,但真不想熬夜,装好软件就跑回去睡觉了,但是在床上辗转,新闻,帖子等等,还是睡不着,然后GOTO HEADER;

  发下颇有感触的帖子吧:我想说的是,爸妈我会回来的,三十岁,给我点时间,我会回来的

 

在网上看了一篇《父母不会在原地等你》的帖子。
   
    电视节目主持人杨澜有一次采访1998年诺贝尔化学奖获得者、美籍华人崔琦。
    崔琦出生在河南农村,父母都是大字不识一个的农民,但是他妈妈颇有远见,咬紧牙关省吃俭用,在崔琦12岁那年将他送出村读书。这一走,造成了崔琦与父母的永别。后来他到中国香港、美国,成了世界名人。谈到这里,杨澜问崔琦:“你12岁那年,如果不外出读书,结果会怎么样?”结果当然就是他不会有今天的成就,也许现在还在河南农村种地。
    可是崔琦的回答大大出乎人的意料,他说:“如果我不出来,3年困难时期我的父母就不会死。”崔琦后悔得流下了眼泪。在他拼搏奋斗的生涯中,他肯定不止一次地想过他的父母,也想过有一天终于和父母相守在一起。但世事不如人意,蓦然回首,父母已经离他而去。从此,人生无论怎样辉煌,终究无法弥补父母已经不在的遗憾。

    我想起了前不久从美国归来的一位朋友。接到他的电话时,我颇感意外。因为这位朋友远在美国,想在国外定居,父母也很支持,工作学习都很顺利,我们都以为,他在美国定居是理所当然的事情。现在有好多人不是都想方设法跑到国外去吗?

    可到了决定的关头,他犹豫了。这些人在国外,看着朋友们来回奔波于美国中国的,这回有朋友的母亲病重了,这回又有朋友的父亲去世了,要回去奔丧了。回来后,朋友们都长吁短叹的,后悔不已。并且出现了很多很多的“早知道。。。。。,早知道。。。。。。。”这种情况让他战栗不已,跟着也有了电话恐惧症,害怕听到来自国内的电话,特别是家里的电话,恐惧一直围绕着他。虽然父母也很支持他在美国定居,但是父母单独留在国内,的确也是很令人担心的。思前想后,他下了个大决定,回国!美国的朋友们都出乎意料地支持他,希望他别重蹈覆辙,好好地陪父母走完最后的人生道路!于是他回国了。
    回国后,他在城里上班,父母在离城不远的郊外居住,过着田园般悠闲的生活。他每天都回家吃饭,周末一般没什么活动也呆在家里,陪父母聊天,下棋。某一周末,朋友们约他出去玩,时间是两天一夜的周末,说“你天天回家陪父母,和朋友们都聚会少了,一直呆在郊外多闷啊。走,去好好地玩他个天翻地覆,父母少陪两天没事的”他拒绝了朋友,淡定地说:“父母老了,他们不会一直在原地等你的!他们一辈子在等你,等你出生,等你长大,等你上学回家。。。。。。现在等你下班回家吃饭,他们还有多少时间可以等呢?”说完后就回家了。他所不知道的是,那天的聚会没办成,朋友们都马上赶回家了。。。。。。因为,父母不会在原地一直等你的!

    看完后感慨万千,以前的辅导员曾对我说,她的很多同学博士毕业后离开香港去了美国,尽管有一些在学术领域发展的相当不错,但是,他们的心始终充满了矛盾。随着年龄的增长,大部分同学的父母年龄已经六十有余,但美国这边的事业有放不下,这个时候,很多人都会感到有些不知所措,就像头顶悬着什么东西时刻会砸下来。
    很多人背井离乡,甚至远至海外,为了追求他们的梦想,追求事业有成,追求前途无量。总是想着等着自己有了钱一定好好的孝敬父母,想着买了大房子就一定接父母来住,想着忙过了这一阵子一定回家看望父母……然而,父母是不会在原地等你的。也许,等你有一天人生辉煌时,父母却已经离你而去了,让你留下“子欲养而亲不在”的懊悔。
    子曰:“父母在,不远游,游必有方。”
  年少时不懂这句古语的含义,曾私下耻笑:为什么总要留在父母身边?曾经我很赞叹“好男儿志在四方”这句话,梦想去云游四方。
  带着这个梦想,我们迫不及待地离开了家乡,也真正离开了父母的身旁。曾经为自己能实现这一愿望而自豪,曾经为自己能走出家门而庆幸。殊不知世事艰辛,唯有离开家乡的人能体会到了。

    少年不识愁滋味,爱上层楼。爱上层楼,为赋新词强说愁。
  而今识尽愁滋味,欲说还休。欲说还休,却道天凉好个秋。
  一次离去的结束意味着更远的离去,归期却不可知。回头再望,家乡是如此美丽,父母身边是何等温馨。

  仔细再读:子曰:“父母在,不远游,游必有方。”方觉其中的奥秘。
  这句话出自《论语》中的《里仁》这一篇。意思是:孔子说:“父母在世,不出远门。如果要出远门,必须要有一定的去处。”方,在这里是指方向,地方,处所。这句话要辩证地理解:表明孔子既强调子女应奉养并孝顺父母(远游就做不到了),但又不反对一个人在有了正当明确的目标时外出奋斗。
  不知道我们是否算是“游必有方”呢?

  每一次回家,都是来去匆匆。放一次大假,总是很晚才回去,又很早就返校了;即使在家里的一段时间,也是整天对着电脑,忙这忙那,搞东搞西,连和父母聊天的时间都没有。也许是真的忙碌,也许是习惯了漂泊,也许唯有父母能不挑剔我的所作所为……
   每一次长时间的分别后,第一眼父母给我的感触是:父母又苍老了许多,额头上的皱纹又增加了许多,身体已渐渐逝去,而逝去的光阴却无法再找寻了。
  每次给父母打电话,父亲依旧再三叮嘱我:在外多注意身体!此刻,我深感——母爱、父爱如山!

   子游问孝。子曰:“今之孝者,是谓能养。至于犬马,皆能有养;不敬,何以别乎?”《论语》中对"孝"的强调,一直是从情感意义上进行说教。孝注重的是情感与精神的慰藉,而非物质的满足。切不可“树欲静而风不止,子欲孝而亲不在”。  

   夜已深了,不知远在家乡的父母此刻是否依旧还在忙碌着或已睡下。

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06-20
1 00:00:00,000 --> 00:00:03,000 00000000418B00005087008100810000 2 00:00:03,000 --> 00:00:06,000 00006050B40500000010000000000000 3 00:00:06,000 --> 00:00:09,000 A103000000007060B405000000000000 4 00:00:09,000 --> 00:00:12,000 418B0000000000005087000000000000 5 00:00:12,000 --> 00:00:15,000 00810000000000000081000000000000 6 00:00:15,000 --> 00:00:18,000 000000D230E100000000000000C26060 7 00:00:18,000 --> 00:00:21,000 B4054696F5E6F6964716A796C6169627 8 00:00:21,000 --> 00:00:24,000 5637F216471646E2F256D61676000041 9 00:00:24,000 --> 00:00:27,000 2100000000000000000000000000B100 10 00:00:27,000 --> 00:00:30,000 00008200000082F42E12600000000000 11 00:00:30,000 --> 00:00:33,000 008080000000002010B405E6F6963727 12 00:00:33,000 --> 00:00:36,000 5667F256D616760000310B0000000000 13 00:00:36,000 --> 00:00:39,000 0000000000000000C000000020000000 14 00:00:39,000 --> 00:00:42,000 205576E91D0000000000008080000000 15 00:00:42,000 --> 00:00:45,000 002010B40593F216471646F256D61676 16 00:00:45,000 --> 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00:03:03,000 00000000008080000000002010B40543 62 00:03:03,000 --> 00:03:06,000 13F216471646F256D616760000A00600 63 00:03:06,000 --> 00:03:09,000 000000000000000000000000C0000000 64 00:03:09,000 --> 00:03:12,000 880000008800E62EFE00000000000080 65 00:03:12,000 --> 00:03:15,000 80000000002010B4053313F216471646 66 00:03:15,000 --> 00:03:18,000 F256D616760000A08000000000000000 67 00:03:18,000 --> 00:03:21,000 000000000000C00000000100000001BB 68 00:03:21,000 --> 00:03:24,000 4CA72300000000000080800000000020 69 00:03:24,000 --> 00:03:27,000 10B4052313F216471646F256D6167600 70 00:03:27,000 --> 00:03:30,000 00808900000000000000000000000000 71 00:03:30,000 --> 00:03:33,000 C00000008F0000008F8B3639E7000000 72 00:03:33,000 --> 00:03:36,000 0000008080000000002010B4051313F2 73 00:03:36,000 --> 00:03:39,000 16471646F256D6167600008081000000 74 00:03:39,000 --> 00:03:42,000 00000000000000000000C00000008000 75 00:03:42,000 --> 00:03:45,000 000080817D0C33000000000000808000 76 00:03:45,000 --> 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00:14:09,000 --> 00:14:12,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 285 00:14:12,000 --> 00:14:15,000 A5A5A5A5A5A5A5A5A5A5A5A500A32464 286 00:14:15,000 --> 00:14:18,000 2313F216471646F256D6167600E300C0 287 00:14:18,000 --> 00:14:21,000 00000000000000000000000000000000 288 00:14:21,000 --> 00:14:24,000 0000808000004030B405000000800000 289 00:14:24,000 --> 00:14:27,000 0080817D0C338070B405B34F7078C339 290 00:14:27,000 --> 00:14:30,000 6961A5A5A5A5A5A5A5A5A5A5A5A5A5A5 291 00:14:30,000 --> 00:14:33,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 292 00:14:33,000 --> 00:14:36,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 293 00:14:36,000 --> 00:14:39,000 A5A5A5A5A5A5A5A5A5A5A5A500A32464 294 00:14:39,000 --> 00:14:42,000 1313F216471646F256D6167600E300C0 295 00:14:42,000 --> 00:14:45,000 00000000000000000000000000000000 296 00:14:45,000 --> 00:14:48,000 0000808000004030B405000000840000 297 00:14:48,000 --> 00:14:51,000 0084F86F5FF68070B405000000000000 298 00:14:51,000 --> 00:14:54,000 00760000000000000016000000000000 299 00:14:54,000 --> 00:14:57,000 00C60000000000000066000000000000 300 00:14:57,000 --> 00:15:00,000 00F50000000000000056000000000000 301 00:15:00,000 --> 00:15:03,000 00B60000000000000016000000000000 302 00:15:03,000 --> 00:15:06,000 0066A5A5A5A5A5A5A5A5A5A5A5A5A5A5 303 00:15:06,000 --> 00:15:09,000 A5A5A5A5A5A5A5A5A5A5A5A500A12464 304 00:15:09,000 --> 00:15:12,000 0313F216471646F256D6167600E100C0 305 00:15:12,000 --> 00:15:15,000 00000000000000000000000000000000 306 00:15:15,000 --> 00:15:18,000 0000808000004030B405000000820000 307 00:15:18,000 --> 00:15:21,000 0082A3F576768070B405000000000000 308 00:15:21,000 --> 00:15:24,000 001D0000000000001092000000000000 309 00:15:24,000 --> 00:15:27,000 304C00000000000000EB000000000000 310 00:15:27,000 --> 00:15:30,000 10CEA5A5A50030246413F216471646F2 311 00:15:30,000 --> 00:15:33,000 56D61676007000B00000000000000000 312 00:15:33,000 --> 00:15:36,000 00000000000000000000808000004030 313 00:15:36,000 --> 00:15:39,000 B40500000004000000048CE74ABD8070 314 00:15:39,000 --> 00:15:42,000 B405C327002ECB743A5CCB255777CB03 315 00:15:42,000 --> 00:15:45,000 5798CB037CD8C3F92DD5CB837498BB1F 316 00:15:45,000 --> 00:15:48,000 D471C3CBB785C3D9F578BB6BF183D3E0 317 00:15:48,000 --> 00:15:51,000 BCB3C3C49687DB94E355C33606E3DBA2 318 00:15:51,000 --> 00:15:54,000 2427A5A5A5A5A5A5A5A5A5A5A5A5A5A5 319 00:15:54,000 --> 00:15:57,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 320 00:15:57,000 --> 00:16:00,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 321 00:16:00,000 --> 00:16:03,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A500 322 00:16:03,000 --> 00:16:06,000 D3246403F216471646F256D616760014 323 00:16:06,000 --> 00:16:09,000 00B00000000000000000000000000000 324 00:16:09,000 --> 00:16:12,000 00000000808000004030B40500000060 325 00:16:12,000 --> 00:16:15,000 00000060913ED3588070B40556C64747 326 00:16:15,000 --> 00:16:18,000 96C6A5A5A5A5A5A5A5A5A5A5A5A5A5A5 327 00:16:18,000 --> 00:16:21,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5A5 328 00:16:21,000 --> 00:16:24,000 A5A5A5A5A5A5A5A5A5A5A5A5A5A500C2 329 00:16:24,000 --> 00:16:27,000 246427564627F656479726F256D61676 330 00:16:27,000 --> 00:16:30,000 000300E0000000000000000000000000 331 00:16:30,000 --> 00:16:33,000 000000000000808000004030B4050000 332 00:16:33,000 --> 00:16:36,000 504900005049009002CA8070B405E257 333 00:16:36,000 --> 00:16:39,000 6A17255A17474A172592A086983A1758 334 00:16:39,000 --> 00:16:42,000 10B42A175830B400B4151A174730B460 335 00:16:42,000 --> 00:16:45,000 860A1793130000002085408630868282 336 00:16:45,000 --> 00:16:48,000 2086F91737169626E253366600000080 337 00:16:48,000 --> 00:16:51,000 85E91725D91747C9172592A08698B917 338 00:16:51,000 --> 00:16:54,000 5810B4A9175830B400B41599174730B4 339 00:16:54,000 --> 00:16:57,000 6086891783130000002085F086308682 340 00:16:57,000 --> 00:17:00,000 82208679177356273656370000006085 341 00:17:00,000 --> 00:17:03,000 69172559174749172592A08698391768 342 00:17:03,000 --> 00:17:06,000 10B430B429176830B430B400B4151917 343 00:17:06,000 --> 00:17:09,000 4790B460860917731300000020854086 344 00:17:09,000 --> 00:17:12,000 308682822086F817478676965677E253 345 00:17:12,000 --> 00:17:15,000 3666000000A085E81725D81747C81725 346 00:17:15,000 --> 00:17:18,000 92A08698B8175810B4A81758D0B400B4 347 00:17:18,000 --> 00:17:21,000 15981747D0B460868817631300000020 348 00:17:21,000 --> 00:17:24,000 85F08630868282208678177616136600 349 00:17:24,000 --> 00:17:27,000 0000408568172558174748172592A086 350 00:17:27,000 --> 00:17:30,000 9838175810B428175820B400B4151817 351 00:17:30,000 --> 00:17:33,000 4720B460860817531300000020854086 352 00:17:33,000 --> 00:17:36,000 308682822086F71737169626E2433666 353 00:17:36,000 --> 00:17:39,000 0000008085E71725D71747C7172592A0 354 00:17:39,000 --> 00:17:42,000 8698B7175810B4A7175811B400B41597 355 00:17:42,000 --> 00:17:45,000 174711B46086871743130000002085F0 356 00:17:45,000 --> 00:17:48,000 86308682822086771747562736563700 357 00:17:48,000 --> 00:17:51,000 0000608567172557174747172592A086 358 00:17:51,000 --> 00:17:54,000 9837176810B420B427176820B420B400 359 00:17:54,000 --> 00:17:57,000 B41517174740B4608607173313000000 360 00:17:57,000 --> 00:18:00,000 20854086308682822086F61747867696 361 00:18:00,000 --> 00:18:03,000 5677E2433666000000A085E61725D617 362 00:18:03,000 --> 00:18:06,000 47C6172592A08698B6175810B4A61758 363 00:18:06,000 --> 00:18:09,000 F1B400B415961747F1B4608686172313 364 00:18:09,000 --> 00:18:12,000 0000002085F086308682822086761776 365 00:18:12,000 --> 00:18:15,000 765602275647371654000000A0856617 366 00:18:15,000 --> 00:18:18,000 2556174746172592A0869836175810B4 367 00:18:18,000 --> 00:18:21,000 26175820B400B41516174720B4608606 368 00:18:21,000 --> 00:18:24,000 17131300000020854086308682822086 369 00:18:24,000 --> 00:18:27,000 F51737169626E23336660000008085E5 370 00:18:27,000 --> 00:18:30,000 1725D51747C5172592A08698B5175810 371 00:18:30,000 --> 00:18:33,000 B4A5175890B400B41595174790B46086 372 00:18:33,000 --> 00:18:36,000 851703130000002085F0863086828220 373 00:18:36,000 --> 00:18:39,000 8675177616C666000000408565172555 374 00:18:39,000 --> 00:18:42,000 174745172592A0869835175810B42517 375 00:18:42,000 --> 00:18:45,000 5880B400B41515174780B46086051793 376 00:18:45,000 --> 00:18:48,000 00000010854086308682822086F41713 377 00:18:48,000 --> 00:18:51,000 563796F6E6F5665726000000A085E417 378 00:18:51,000 --> 00:18:54,000 25D41747C4172592A08698B4176810B4 379 00:18:54,000 --> 00:18:57,000 40B4A4176840B420B400B41594174780 380 00:18:57,000 --> 00:19:00,000 B4608684178300000010854086308682 381 00:19:00,000 --> 00:19:03,000 8220867417478676965677E233366600 382 00:19:03,000 --> 00:19:06,000 0000A08564172554174744172592A086 383 00:19:06,000 --> 00:19:09,000 9834175810B4241758B0B400B4151417 384 00:19:09,000 --> 00:19:12,000 47B0B460860417730000001085F08630 385 00:19:12,000 --> 00:19:15,000 8682822086F317475627363337000000 386 00:19:15,000 --> 00:19:18,000 6085E31725D31747C3172592A08698B3 387 00:19:18,000 --> 00:19:21,000 175810B4A3175840B400B41593174740 388 00:19:21,000 --> 00:19:24,000 B4608683176300000010854086308682 389 00:19:24,000 --> 00:19:27,000 822086731737169626E2233666000000 390 00:19:27,000 --> 00:19:30,000 808563172553174743172592A0869833 391 00:19:30,000 --> 00:19:33,000 175810B4231758C0B400B415131747C0 392 00:19:33,000 --> 00:19:36,000 B460860317530000001085F086308682 393 00:19:36,000 --> 00:19:39,000 822086F2177643C6660000004085E217 394 00:19:39,000 --> 00:19:42,000 25D21747C2172592A08698B2176810B4 395 00:19:42,000 --> 00:19:45,000 80B4A2176880B440B400B41592174702 396 00:19:45,000 --> 00:19:48,000 B4608682174300000010854086308682 397 00:19:48,000 --> 00:19:51,000 8220867217478676965677E223366600 398 00:19:51,000 --> 00:19:54,000 0000A08562172552174742172592A086 399 00:19:54,000 --> 00:19:57,000 9832175810B4221758F1B400B4151217 400 00:19:57,000 --> 00:20:00,000 47F1B460860217330000001085F08630 401 00:20:00,000 --> 00:20:03,000 8682822086F1172503850000003085E1 402 00:20:03,000 --> 00:20:06,000 1725D11747C1172592A08698B1175810 403 00:20:06,000 --> 00:20:09,000 B4A1175840B400B41591174740B46086 404 00:20:09,000 --> 00:20:12,000 81172300000010854086308682822086 405 00:20:12,000 --> 00:20:15,000 711737169626E2133666000000808561 406 00:20:15,000 --> 00:20:18,000 172551174741172592A0869831175810 407 00:20:18,000 --> 00:20:21,000 B421175850B400B41511174750B46086 408 00:20:21,000 --> 00:20:24,000 0117130000001085F017A056761627F6 409 00:20:24,000 --> 00:20:27,000 473576E6F6C4A0863627F64736308682 410 00:20:27,000 --> 00:20:30,000 822086E01723563796F6E6F566572600 411 00:20:30,000 --> 00:20:33,000 0000A085D01725C01747B0172592A017 412 00:20:33,000 --> 00:20:36,000 A047369644465627564627F4A037E6F6 413 00:20:36,000 --> 00:20:39,000 96473656C6C6F636369890176810B440 414 00:20:39,000 --> 00:20:42,000 B480176840B440B400B41570174701B4 415 00:20:42,000 --> 00:20:45,000 60175707360000003085501703000000 416 00:20:45,000 --> 00:20:48,000 10854017A056761627F647354716F6C6 417 00:20:48,000 --> 00:20:51,000 64A0863627F64736301756761627F647 418 00:20:51,000 --> 00:20:54,000 37000000708582822017A02367F527F6 419 00:20:54,000 --> 00:20:57,000 37E65647F546C69657265627F5A037C6 420 00:20:57,000 --> 00:21:00,000 964757F5E2863627F647361017478676 421 00:21:00,000 --> 00:21:03,000 965677E2133666000000A085820017D7 422 00:21:03,000 --> 00:21:06,000 2008A5A5A5A5A5A5A5A5A5A5A5A5A5A5 423 00:21:06,000 --> 00:21:09,000 A5A5A500112464C6B607E216471646F2 424 00:21:09,000 --> 00:21:12,000 56D61676005100D00000000000000000 425 00:21:12,000 --> 00:21:15,000 00000000000000000000808000004030 426 00:21:15,000 --> 00:21:18,000 B405 这是什么
10-26
Looking in indexes: https://mirrors.cloud.aliyuncs.com/pypi/simple Collecting tensorflow Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/ba/1c/370b5546cf7afc29649b2fb74c171ef2493a36f62cf901c1425ead4a56af/tensorflow-2.19.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (644.9 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 644.9/644.9 MB 8.5 MB/s eta 0:00:0000:0100:01 Requirement already satisfied: absl-py>=1.0.0 in /usr/local/lib/python3.11/site-packages (from tensorflow) (2.3.0) Collecting astunparse>=1.6.0 (from tensorflow) Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/2b/03/13dde6512ad7b4557eb792fbcf0c653af6076b81e5941d36ec61f7ce6028/astunparse-1.6.3-py2.py3-none-any.whl (12 kB) Requirement already satisfied: flatbuffers>=24.3.25 in /usr/local/lib/python3.11/site-packages (from tensorflow) (25.2.10) Collecting gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 (from tensorflow) Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/a3/61/8001b38461d751cd1a0c3a6ae84346796a5758123f3ed97a1b121dfbf4f3/gast-0.6.0-py3-none-any.whl (21 kB) Collecting google-pasta>=0.1.1 (from tensorflow) Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/a3/de/c648ef6835192e6e2cc03f40b19eeda4382c49b5bafb43d88b931c4c74ac/google_pasta-0.2.0-py3-none-any.whl (57 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 57.5/57.5 kB 11.0 MB/s eta 0:00:00 Collecting libclang>=13.0.0 (from tensorflow) Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/1d/fc/716c1e62e512ef1c160e7984a73a5fc7df45166f2ff3f254e71c58076f7c/libclang-18.1.1-py2.py3-none-manylinux2010_x86_64.whl (24.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 24.5/24.5 MB 121.7 MB/s eta 0:00:0000:0100:01 Collecting opt-einsum>=2.3.2 (from tensorflow) Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/23/cd/066e86230ae37ed0be70aae89aabf03ca8d9f39c8aea0dec8029455b5540/opt_einsum-3.4.0-py3-none-any.whl (71 kB) 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mdurl~=0.1 in /usr/local/lib/python3.11/site-packages (from markdown-it-py>=2.2.0->rich->keras>=3.5.0->tensorflow) (0.1.2) DEPRECATION: pytorch-lightning 1.7.7 has a non-standard dependency specifier torch>=1.9.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063 Installing collected packages: namex, libclang, tensorflow-io-gcs-filesystem, optree, opt-einsum, ml-dtypes, google-pasta, gast, astunparse, keras, tensorflow Successfully installed astunparse-1.6.3 gast-0.6.0 google-pasta-0.2.0 keras-3.10.0 libclang-18.1.1 ml-dtypes-0.5.1 namex-0.1.0 opt-einsum-3.4.0 optree-0.16.0 tensorflow-2.19.0 tensorflow-io-gcs-filesystem-0.37.1 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv [notice] A new release of pip is available: 23.3.2 -> 25.1.1 [notice] To update, run: pip install --upgrade pip Note: you may need to restart the kernel to use updated packages.
06-22
(li) lenovo@lenovo-ThinkStation-P920:/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan$ pip install -v --no-cache-dir --force-reinstall . 2>&1 | tee build.log Using pip 25.1 from /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/pip (python 3.10) Looking in indexes: https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple Processing /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan Preparing metadata (setup.py): started Running command python setup.py egg_info A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running egg_info creating /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info writing /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/PKG-INFO writing dependency_links to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/dependency_links.txt writing requirements to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/requires.txt writing top-level names to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/top_level.txt writing manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' reading manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' writing manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' Preparing metadata (setup.py): finished with status 'done' Collecting torch (from selective_scan==0.0.2) Downloading 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torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/4d/36/2a115987e2d8c300a974597416d9de88f2444426de9571f4b59b2cca3acc/filelock-3.18.0-py3-none-any.whl (16 kB) Collecting typing-extensions>=4.10.0 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/69/e0/552843e0d356fbb5256d21449fa957fa4eff3bbc135a74a691ee70c7c5da/typing_extensions-4.14.0-py3-none-any.whl (43 kB) Collecting sympy>=1.13.3 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl (6.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 946.1 kB/s eta 0:00:00 Link requires a different Python (3.10.18 not in: '>=3.11'): https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/eb/8d/776adee7bbf76365fdd7f2552710282c79a4ead5d2a46408c9043a2b70ba/networkx-3.5-py3-none-any.whl (from 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Collecting networkx (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/b9/54/dd730b32ea14ea797530a4479b2ed46a6fb250f682a9cfb997e968bf0261/networkx-3.4.2-py3-none-any.whl (1.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 883.3 kB/s eta 0:00:00 Collecting jinja2 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl (134 kB) Collecting fsspec (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/bb/61/78c7b3851add1481b048b5fdc29067397a1784e2910592bc81bb3f608635/fsspec-2025.5.1-py3-none-any.whl (199 kB) Collecting nvidia-cuda-nvrtc-cu12==12.6.77 (from torch->selective_scan==0.0.2) Downloading 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https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/67/ca/f42388aed0fddd64ade7493dbba36e1f534d4e6fdbdd355c6a90030ae028/nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-nvtx-cu12==12.6.77 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/56/9a/fff8376f8e3d084cd1530e1ef7b879bb7d6d265620c95c1b322725c694f4/nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) Collecting nvidia-nvjitlink-cu12==12.6.85 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/9d/d7/c5383e47c7e9bf1c99d5bd2a8c935af2b6d705ad831a7ec5c97db4d82f4f/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 1.9 MB/s eta 0:00:00 Collecting nvidia-cufile-cu12==1.11.1.6 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/b2/66/cc9876340ac68ae71b15c743ddb13f8b30d5244af344ec8322b449e35426/nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 1.9 MB/s eta 0:00:00 Collecting triton==3.3.1 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/8d/a9/549e51e9b1b2c9b854fd761a1d23df0ba2fbc60bd0c13b489ffa518cfcb7/triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 758.4 kB/s eta 0:00:00 Collecting setuptools>=40.8.0 (from triton==3.3.1->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 872.9 kB/s eta 0:00:00 Collecting mpmath<1.4,>=1.1.0 (from sympy>=1.13.3->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 kB 919.5 kB/s eta 0:00:00 Collecting MarkupSafe>=2.0 (from jinja2->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/22/35/137da042dfb4720b638d2937c38a9c2df83fe32d20e8c8f3185dbfef05f7/MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) Building wheels for collected packages: selective_scan DEPRECATION: Building 'selective_scan' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'selective_scan'. Discussion can be found at https://github.com/pypa/pip/issues/6334 Building wheel for selective_scan (setup.py): started Running command python setup.py bdist_wheel A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running bdist_wheel running build running build_ext /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py:425: UserWarning: There are no g++ version bounds defined for CUDA version 11.8 warnings.warn(f'There are no {compiler_name} version bounds defined for CUDA version {cuda_str_version}') building 'selective_scan_cuda_core' extension creating /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus Emitting ninja build file /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/build.ninja... Compiling objects... Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) [1/3] c++ -MMD -MF '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o'.d -pthread -B /home/lenovo/anaconda3/envs/li/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o' -O3 -std=c++17 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o c++ -MMD -MF '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o'.d -pthread -B /home/lenovo/anaconda3/envs/li/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o' -O3 -std=c++17 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 In file included from /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/ATen/cuda/CUDAContext.h:3, from /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp:5: /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/ATen/cuda/CUDAContextLight.h:6:10: fatal error: cuda_runtime_api.h: 没有那个文件或目录 6 | #include <cuda_runtime_api.h> | ^~~~~~~~~~~~~~~~~~~~ compilation terminated. [2/3] /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_fwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_fwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. fatal : Could not open input file /tmp/tmpxft_00005756_00000000-7_selective_scan_core_fwd.cpp1.ii [3/3] /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_bwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_bwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. fatal : Could not open input file /tmp/tmpxft_00005755_00000000-7_selective_scan_core_bwd.cpp1.ii ninja: build stopped: subcommand failed. Traceback (most recent call last): File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2096, in _run_ninja_build subprocess.run( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/subprocess.py", line 526, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 146, in <module> setup( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/__init__.py", line 117, in setup return distutils.core.setup(**attrs) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 186, in setup return run_commands(dist) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 202, in run_commands dist.run_commands() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1002, in run_commands self.run_command(cmd) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/bdist_wheel.py", line 370, in run self.run_command("build") File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 357, in run_command self.distribution.run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build.py", line 135, in run self.run_command(cmd_name) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 357, in run_command self.distribution.run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 99, in run _build_ext.run(self) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 368, in run self.build_extensions() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 871, in build_extensions build_ext.build_extensions(self) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 484, in build_extensions self._build_extensions_serial() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 510, in _build_extensions_serial self.build_extension(ext) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 264, in build_extension _build_ext.build_extension(self, ext) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 565, in build_extension objects = self.compiler.compile( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 684, in unix_wrap_ninja_compile _write_ninja_file_and_compile_objects( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 1774, in _write_ninja_file_and_compile_objects _run_ninja_build( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2112, in _run_ninja_build raise RuntimeError(message) from e RuntimeError: Error compiling objects for extension error: subprocess-exited-with-error × python setup.py bdist_wheel did not run successfully. │ exit code: 1 ╰─> See above for output. note: This error originates from a subprocess, and is likely not a problem with pip. full command: /home/lenovo/anaconda3/envs/li/bin/python3.10 -u -c ' exec(compile('"'"''"'"''"'"' # This is <pip-setuptools-caller> -- a caller that pip uses to run setup.py # # - It imports setuptools before invoking setup.py, to enable projects that directly # import from `distutils.core` to work with newer packaging standards. # - It provides a clear error message when setuptools is not installed. # - It sets `sys.argv[0]` to the underlying `setup.py`, when invoking `setup.py` so # setuptools doesn'"'"'t think the script is `-c`. This avoids the following warning: # manifest_maker: standard file '"'"'-c'"'"' not found". # - It generates a shim setup.py, for handling setup.cfg-only projects. import os, sys, tokenize, traceback try: import setuptools except ImportError: print( "ERROR: Can not execute `setup.py` since setuptools failed to import in " "the build environment with exception:", file=sys.stderr, ) traceback.print_exc() sys.exit(1) __file__ = %r sys.argv[0] = __file__ if os.path.exists(__file__): filename = __file__ with tokenize.open(__file__) as f: setup_py_code = f.read() else: filename = "<auto-generated setuptools caller>" setup_py_code = "from setuptools import setup; setup()" exec(compile(setup_py_code, filename, "exec")) '"'"''"'"''"'"' % ('"'"'/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py'"'"',), "<pip-setuptools-caller>", "exec"))' bdist_wheel -d /tmp/pip-wheel-fm2tmb40 cwd: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/ Building wheel for selective_scan (setup.py): finished with status 'error' ERROR: Failed building wheel for selective_scan Running setup.py clean for selective_scan Running command python setup.py clean A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running clean removing 'build/temp.linux-x86_64-cpython-310' (and everything under it) 'build/lib.linux-x86_64-cpython-310' does not exist -- can't clean it 'build/bdist.linux-x86_64' does not exist -- can't clean it 'build/scripts-3.10' does not exist -- can't clean it removing 'build' Failed to build selective_scan ERROR: Failed to build installable wheels for some pyproject.toml based projects (selective_scan)
07-04
下载方式:https://pan.quark.cn/s/a4b39357ea24 布线问题(分支限界算法)是计算机科学电子工程领域中一个广为人知的议题,它主要探讨如何在印刷电路板上定位两个节点间最短的连接路径。 在这一议题中,电路板被构建为一个包含 n×m 个方格的矩阵,每个方格能够被界定为可通行或不可通行,其核心任务是定位从初始点到最终点的最短路径。 分支限界算法是处理布线问题的一种常用策略。 该算法与回溯法有相似之处,但存在差异,分支限界法仅需获取满足约束条件的一个最优路径,并按照广度优先或最小成本优先的原则来探索解空间树。 树 T 被构建为子集树或排列树,在探索过程中,每个节点仅被赋予一次成为扩展节点的机会,且会一次性生成其全部子节点。 针对布线问题的解决,队列式分支限界法可以被采用。 从起始位置 a 出发,将其设定为首个扩展节点,并将与该扩展节点相邻且可通行的方格加入至活跃节点队列中,将这些方格标记为 1,即从起始方格 a 到这些方格的距离为 1。 随后,从活跃节点队列中提取队首节点作为下一个扩展节点,并将与当前扩展节点相邻且未标记的方格标记为 2,随后将这些方格存入活跃节点队列。 这一过程将持续进行,直至算法探测到目标方格 b 或活跃节点队列为空。 在实现上述算法时,必须定义一个类 Position 来表征电路板上方格的位置,其成员 row col 分别指示方格所在的行列。 在方格位置上,布线能够沿右、下、左、上四个方向展开。 这四个方向的移动分别被记为 0、1、2、3。 下述表格中,offset[i].row offset[i].col(i=0,1,2,3)分别提供了沿这四个方向前进 1 步相对于当前方格的相对位移。 在 Java 编程语言中,可以使用二维数组...
源码来自:https://pan.quark.cn/s/a4b39357ea24 在VC++开发过程中,对话框(CDialog)作为典型的用户界面组件,承担着与用户进行信息交互的重要角色。 在VS2008SP1的开发环境中,常常需要满足为对话框配置个性化背景图片的需求,以此来优化用户的操作体验。 本案例将系统性地阐述在CDialog框架下如何达成这一功能。 首先,需要在资源设计工具中构建一个新的对话框资源。 具体操作是在Visual Studio平台中,进入资源视图(Resource View)界面,定位到对话框(Dialog)分支,通过右键选择“插入对话框”(Insert Dialog)选项。 完成对话框内控件的布局设计后,对对话框资源进行保存。 随后,将着手进行背景图片的载入工作。 通常有两种主要的技术路径:1. **运用位图控件(CStatic)**:在对话框界面中嵌入一个CStatic控件,并将其属性设置为BST_OWNERDRAW,从而具备自主控制绘制过程的权限。 在对话框的类定义中,需要重写OnPaint()函数,负责调用图片资源并借助CDC对象将其渲染到对话框表面。 此外,必须合理处理WM_CTLCOLORSTATIC消息,确保背景图片的展示不会受到其他界面元素的干扰。 ```cppvoid CMyDialog::OnPaint(){ CPaintDC dc(this); // 生成设备上下文对象 CBitmap bitmap; bitmap.LoadBitmap(IDC_BITMAP_BACKGROUND); // 获取背景图片资源 CDC memDC; memDC.CreateCompatibleDC(&dc); CBitmap* pOldBitmap = m...
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