B - A and B and Compilation Errors

编程竞赛中的错误修复与团队构建策略
本文讲述了A和B两位程序员在准备编程比赛时遇到的错误修复问题,以及他们在组建训练团队时如何优化成员分配以最大化知识分享的效果。在错误修复中,他们需要找出在两次编译后消失的两个错误。在团队构建中,A主张1个老手带2个新手,B则认为2个老手带1个新手更优。问题转化为在有限的老手和新手中,如何最大化团队数量。

A and B are preparing themselves for programming contests.

B loves to debug his code. But before he runs the solution and starts debugging, he has to first compile the code.

Initially, the compiler displayed n compilation errors, each of them is represented as a positive integer. After some effort, B managed to fix some mistake and then another one mistake.

However, despite the fact that B is sure that he corrected the two errors, he can not understand exactly what compilation errors disappeared — the compiler of the language which B uses shows errors in the new order every time! B is sure that unlike many other programming languages, compilation errors for his programming language do not depend on each other, that is, if you correct one error, the set of other error does not change.

Can you help B find out exactly what two errors he corrected?

Input

The first line of the input contains integer n (3 ≤ n ≤ 105) — the initial number of compilation errors.

The second line contains n space-separated integersa1, a2, ..., an (1 ≤ ai ≤ 109) — the errors the compiler displayed for the first time.

The third line contains n - 1 space-separated integersb1, b2, ..., bn - 1 — the errors displayed at the second compilation. It is guaranteed that the sequence in the third line contains all numbers of the second string except for exactly one.

The fourth line contains n - 2 space-separated integersс1, с2, ..., сn - 2 — the errors displayed at the third compilation. It is guaranteed that the sequence in the fourth line contains all numbers of the third line except for exactly one.

Output

Print two numbers on a single line: the numbers of the compilation errors that disappeared after B made the first and the second correction, respectively.

Sample test(s)
Input
5
1 5 8 123 7
123 7 5 1
5 1 7
Output
8
123
Input
6
1 4 3 3 5 7
3 7 5 4 3
4 3 7 5
Output
1
3

 

题目的大意是:
给你三组数据,要你每次判断出比上一次减少了哪个数。有两种方法,虽说是水题,但是也能学到点什么的。
方法一:
#include<stdio.h>
#include<string.h>
int a[100001],b[100001],c[100001];
int main(){
	int n,i,j,k;
	int sum1,sum2;
	memset(a,0,sizeof(a)); memset(b,0,sizeof(b)); memset(c,0,sizeof(c));
	scanf("%d",&n);
	for(i=1;i<=n;i++)
		scanf("%d",&a[i]);
	for(i=1;i<n;i++)
		scanf("%d",&b[i]);
	for(i=1;i<=n-2;i++)
		scanf("%d",&c[i]);
	sum1=sum2=0;
	#if 1
	for(i=1;i<=n;i++){
		sum1+=a[i];
		sum1-=b[i];
		//printf("%d\n",sum1);
	}
	#endif
	#if 1
	for(i=1;i<=n-1;i++){
		sum2+=b[i];
		sum2-=c[i];
	}
	#endif
	printf("%d\n%d\n",sum1,sum2);
}

//第一种方法,就是加一次第一组的数然后再减掉第二组的数,最后求得的sum1就是第二组缺少的数。同理也可得sum2就是第三组比第二组少的数。
最后输出来就可以了。
 
#include<stdio.h>
#include<algorithm>
#include<iostream>
using namespace std;

int main()
{
	int n;
	int a[100010],b[100010],c[100010];
	while(scanf("%d", &n)!=EOF)
	{
	int i;
		for(i=0;i<n;i++) scanf("%d", &a[i]);
		for(i=0;i<n-1;i++) scanf("%d", &b[i]);
		for(i=0;i<n-2;i++) scanf("%d", &c[i]);
    	sort(a,a+n);
    	sort(b,b+n-1);
    	sort(c,c+n-2);
    	int p=0,l=0;
		for(i=0;i<n-1;i++)
		{	p++;
			if(a[i]!=b[i]) 
			{
				printf("%d\n",a[i]);
				break;
			}
		}
		if(p==i) printf("%d\n",a[p]); 
	
		for(i=0;i<n-1;i++)
		{   	l++;
			if(b[i]!=c[i]) 
			{
				printf("%d\n",b[i]);
				break;
			}
		}
		if(l==i) printf("%d\n",b[l]); 
	}
}

//第二种方法:
就是每次对每组排序,然后如果 a[i]!=b[i]的话,那么就输出a[i],如果全部循环完了,但是还是没发现这种情况,那么就输出最后一个数字a[p];
同理对第三组也是这样。
 
 
C - A and B and Team Training
Crawling in process...Crawling failedTime Limit:1000MS    Memory Limit:262144KB    64bit IO Format:%I64d & %I64u

A and B are preparing themselves for programming contests.

An important part of preparing for a competition is sharing programming knowledge from the experienced members to those who are just beginning to deal with the contests. Therefore, during the next team training A decided to make teams so that newbies are solving problems together with experienced participants.

A believes that the optimal team of three people should consist of one experienced participant and two newbies. Thus, each experienced participant can share the experience with a large number of people.

However, B believes that the optimal team should have two experienced members plus one newbie. Thus, each newbie can gain more knowledge and experience.

As a result, A and B have decided that all the teams during the training session should belong to one of the two types described above. Furthermore, they agree that the total number of teams should be as much as possible.

There are n experienced members and m newbies on the training session. Can you calculate what maximum number of teams can be formed?

Input

The first line contains two integers n and m (0 ≤ n, m ≤ 5·105) — the number of experienced participants and newbies that are present at the training session.

Output

Print the maximum number of teams that can be formed.

Sample test(s)
Input
2 6
Output
2
Input
4 5
Output
3

 

题目的大致意思就是给你两种选队员的方案,一种是选2个新队员1个老队员,第二种是选1个新队员2个老队员。问怎样选择才能使得队伍的数量最大。

实际上就是一个模拟:

#include<stdio.h>
#include<string.h>
int main(){
	int n,m,i,j,k,num=0;
	scanf("%d%d",&n,&m);
	int old,new1;
	old=n; new1=m;
	while(1){
		while(old<=new1&&old>=1&&new1>=2){
			old--;
			new1=new1-2;
			num++;
		}
		while(new1<=old&&new1>=1&&old>=2){
			new1--;
			old=old-2;
			num++;
		}
		if(new1<=0 || old<=0 ||(new1==1&&old==1))  break;
	}
	printf("%d\n",num);
}


 

WARNING: A restricted method in java.lang.System has been called WARNING: java.lang.System::loadLibrary has been called by org.fusesource.hawtjni.runtime.Library in an unnamed module (file:/B:/apache-maven-3.6.0/lib/jansi-1.17.1.jar) WARNING: Use --enable-native-access=ALL-UNNAMED to avoid a warning for callers in this module WARNING: Restricted methods will be blocked in a future release unless native access is enabled WARNING: A terminally deprecated method in sun.misc.Unsafe has been called WARNING: sun.misc.Unsafe::objectFieldOffset has been called by com.google.common.util.concurrent.AbstractFuture$UnsafeAtomicHelper (file:/B:/apache-maven-3.6.0/lib/guava-25.1-android.jar) WARNING: Please consider reporting this to the maintainers of class com.google.common.util.concurrent.AbstractFuture$UnsafeAtomicHelper WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [INFO] Scanning for projects... [INFO] [INFO] --------------------< com.example:stockmanagement >--------------------- [INFO] Building personnel 0.0.1-SNAPSHOT [INFO] --------------------------------[ jar ]--------------------------------- [INFO] [INFO] --- maven-resources-plugin:3.2.0:resources (default-resources) @ stockmanagement --- [INFO] Using 'UTF-8' encoding to copy filtered resources. [INFO] Using 'UTF-8' encoding to copy filtered properties files. [INFO] Copying 1 resource [INFO] Copying 7 resources [INFO] [INFO] --- maven-compiler-plugin:3.8.1:compile (default-compile) @ stockmanagement --- [INFO] Changes detected - recompiling the module! [INFO] Compiling 35 source files to C:\Users\14216\Desktop\ckgl\stockmanagement\target\classes [INFO] ------------------------------------------------------------- [ERROR] COMPILATION ERROR : [INFO] ------------------------------------------------------------- [ERROR] /C:/Users/14216/Desktop/ckgl/stockmanagement/src/main/java/com/example/stockmanagement/stockmanagementApplication.java:[3,25] 程序包com.sun.deploy.si不存在 [ERROR] /C:/Users/14216/Desktop/ckgl/stockmanagement/src/main/java/com/example/stockmanagement/stockmanagementApplication.java:[11,27] 程序包SingleInstanceImpl不存在 [INFO] 2 errors [INFO] ------------------------------------------------------------- [INFO] ------------------------------------------------------------------------ [INFO] BUILD FAILURE [INFO] ------------------------------------------------------------------------ [INFO] Total time: 5.651 s [INFO] Finished at: 2025-06-02T20:01:54+08:00 [INFO] ------------------------------------------------------------------------ [ERROR] Failed to execute goal org.apache.maven.plugins:maven-compiler-plugin:3.8.1:compile (default-compile) on project stockmanagement: Compilation failure: Compilation failure: [ERROR] /C:/Users/14216/Desktop/ckgl/stockmanagement/src/main/java/com/example/stockmanagement/stockmanagementApplication.java:[3,25] 程序包com.sun.deploy.si不存在 [ERROR] /C:/Users/14216/Desktop/ckgl/stockmanagement/src/main/java/com/example/stockmanagement/stockmanagementApplication.java:[11,27] 程序包SingleInstanceImpl不存在 [ERROR] -> [Help 1] [ERROR] [ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch. [ERROR] Re-run Maven using the -X switch to enable full debug logging. [ERROR] [ERROR] For more information about the errors and possible solutions, please read the following articles: [ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException 进程已结束,退出代码1 怎么解决
06-03
PowerShell 7 环境已加载 (版本: 7.5.2) PowerShell 7 环境已加载 (版本: 7.5.2) PS C:\Users\Administrator\Desktop> cd E:\PyTorch_Build\pytorch PS E:\PyTorch_Build\pytorch> .\pytorch_env\Scripts\activate (pytorch_env) PS E:\PyTorch_Build\pytorch> # 退出虚拟环境 (pytorch_env) PS E:\PyTorch_Build\pytorch> deactivate PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 删除旧环境 PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\pytorch_env PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\cuda_env PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 创建新虚拟环境 PS E:\PyTorch_Build\pytorch> python -m venv rtx5070_env PS E:\PyTorch_Build\pytorch> .\rtx5070_env\Scripts\activate (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装基础编译工具 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) Collecting setuptools Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) ERROR: To modify pip, please run the following command: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -m pip install -U pip setuptools wheel ninja cmake [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 安装 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 CUDA 12.x nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 正确更新 pip 和工具链 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python -m pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) Collecting setuptools Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) Installing collected packages: wheel, setuptools, pip, ninja, cmake Attempting uninstall: setuptools Found existing installation: setuptools 65.5.0 Uninstalling setuptools-65.5.0: Successfully uninstalled setuptools-65.5.0 Attempting uninstall: pip Found existing installation: pip 22.3.1 Uninstalling pip-22.3.1: Successfully uninstalled pip-22.3.1 Successfully installed cmake-4.1.0 ninja-1.13.0 pip-25.2 setuptools-80.9.0 wheel-0.45.1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip --version # 应显示 25.2+ pip 25.2 from E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\pip (python 3.10) (rtx5070_env) PS E:\PyTorch_Build\pytorch> cmake --version # 应显示 4.1.0+ cmake version 4.1.0 CMake suite maintained and supported by Kitware (kitware.com/cmake). (rtx5070_env) PS E:\PyTorch_Build\pytorch> ninja --version # 应显示 1.13.0+ 1.13.0.git.kitware.jobserver-pipe-1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 CUDA 12.1 环境变量 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDA_PATH = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:PATH = "$env:CUDA_PATH\bin;" + $env:PATH (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 release 12.1 nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 cuDNN 路径(根据实际安装位置) (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_INCLUDE_DIR = "$env:CUDA_PATH\include" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_LIBRARY = "$env:CUDA_PATH\lib\x64\cudnn.lib" (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting pyyaml Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b5/84/0fa4b06f6d6c958d207620fc60005e241ecedceee58931bb20138e1e5776/PyYAML-6.0.2-cp310-cp310-win_amd64.whl (161 kB) Collecting numpy Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl (12.9 MB) Collecting typing_extensions Using cached https://pypi.tuna.tsinghua.edu.cn/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl (44 kB) Installing collected packages: typing_extensions, pyyaml, numpy Successfully installed numpy-2.2.6 pyyaml-6.0.2 typing_extensions-4.15.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting mkl Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/ae/025174ee141432b974f97ecd2aea529a3bdb547392bde3dd55ce48fe7827/mkl-2025.2.0-py2.py3-none-win_amd64.whl (153.6 MB) Collecting mkl-include Using cached https://pypi.tuna.tsinghua.edu.cn/packages/06/87/3eee37bf95c6b820b6394ad98e50132798514ecda1b2584c71c2c96b973c/mkl_include-2025.2.0-py2.py3-none-win_amd64.whl (1.3 MB) Collecting intel-openmp Using cached https://pypi.tuna.tsinghua.edu.cn/packages/89/ed/13fed53fcc7ea17ff84095e89e63418df91d4eeefdc74454243d529bf5a3/intel_openmp-2025.2.1-py2.py3-none-win_amd64.whl (34.0 MB) Collecting tbb==2022.* (from mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/4e/d2/01e2a93f9c644585088188840bf453f23ed1a2838ec51d5ba1ada1ebca71/tbb-2022.2.0-py3-none-win_amd64.whl (420 kB) Collecting intel-cmplr-lib-ur==2025.2.1 (from intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a8/70/938e81f58886fd4e114d5a5480d98c1396e73e40b7650f566ad0c4395311/intel_cmplr_lib_ur-2025.2.1-py2.py3-none-win_amd64.whl (1.2 MB) Collecting umf==0.11.* (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/33/a0/c8d755f08f50ddd99cb4a29a7e950ced7a0903cb72253e57059063609103/umf-0.11.0-py2.py3-none-win_amd64.whl (231 kB) Collecting tcmlib==1.* (from tbb==2022.*->mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/7b/e30c461a27b97e0090e4db822eeb1d37b310863241f8c3ee56f68df3e76e/tcmlib-1.4.0-py2.py3-none-win_amd64.whl (370 kB) Installing collected packages: tcmlib, mkl-include, umf, tbb, intel-cmplr-lib-ur, intel-openmp, mkl Successfully installed intel-cmplr-lib-ur-2025.2.1 intel-openmp-2025.2.1 mkl-2025.2.0 mkl-include-2025.2.0 tbb-2022.2.0 tcmlib-1.4.0 umf-0.11.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: mkl in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: mkl-include in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: intel-openmp in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.1) Requirement already satisfied: tbb==2022.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from mkl) (2022.2.0) Requirement already satisfied: intel-cmplr-lib-ur==2025.2.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-openmp) (2025.2.1) Requirement already satisfied: umf==0.11.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) (0.11.0) Requirement already satisfied: tcmlib==1.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from tbb==2022.*->mkl) (1.4.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDA=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDNN=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CMAKE_GENERATOR="Ninja" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:MAX_JOBS=8 # 根据 CPU 核心数设置 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 运行编译 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --cmake-only ` >> --cmake-generator="Ninja" ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DTORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" Building wheel torch-2.9.0a0+git2d31c3d option --cmake-generator not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python rtx5070_test.py ============================================================ Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 39, in <module> verify_gpu_support() File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 6, in verify_gpu_support if not torch.cuda.is_available(): AttributeError: module 'torch' has no attribute 'cuda' (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译架构参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:TORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用正确的编译命令 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DCMAKE_GENERATOR="Ninja" ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON Building wheel torch-2.9.0a0+git2d31c3d option -D not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python enhanced_test.py ============================================================ Python 版本: 3.10.10 Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 64, in <module> verify_installation() File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 11, in verify_installation print(f"\nPyTorch 版本: {torch.__version__}") AttributeError: module 'torch' has no attribute '__version__' (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 清除之前的构建 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py clean --all Building wheel torch-2.9.0a0+git2d31c3d E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\setuptools\config\_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated !! ******************************************************************************** Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0). By 2026-Feb-18, you need to update your project and remove deprecated calls or your builds will no longer be supported. See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! corresp(dist, value, root_dir) usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: option --all not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译架构参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:TORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用正确的编译命令(Windows专用) (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --cmake-args="-DCMAKE_CUDA_COMPILER='$env:CUDA_PATH\bin\nvcc.exe' ` >> -DCUDNN_INCLUDE_DIR='$env:CUDNN_INCLUDE_DIR' ` >> -DCUDNN_LIBRARY='$env:CUDNN_LIBRARY' ` >> -DCMAKE_GENERATOR='Ninja' ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON" ` >> --verbose ` >> --jobs=$env:MAX_JOBS Building wheel torch-2.9.0a0+git2d31c3d option --cmake-args not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用 PyTorch 官方构建工具 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install -U setuptools wheel Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (80.9.0) Requirement already satisfied: wheel in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (0.45.1) (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py bdist_wheel Building wheel torch-2.9.0a0+git2d31c3d -- Building version 2.9.0a0+git2d31c3d E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\setuptools\_distutils\_msvccompiler.py:12: UserWarning: _get_vc_env is private; find an alternative (pypa/distutils#340) warnings.warn( -- Checkout nccl release tag: v2.27.5-1 cmake -GNinja -DBUILD_PYTHON=True -DBUILD_TEST=True -DCMAKE_BUILD_TYPE=Release -DCMAKE_GENERATOR=Ninja -DCMAKE_INSTALL_PREFIX=E:\PyTorch_Build\pytorch\torch -DCMAKE_PREFIX_PATH=E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages -DCUDNN_INCLUDE_DIR=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\include -DCUDNN_LIBRARY=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\lib\x64\cudnn.lib -DPython_EXECUTABLE=E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -DPython_NumPy_INCLUDE_DIR=E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\numpy\_core\include -DTORCH_BUILD_VERSION=2.9.0a0+git2d31c3d -DTORCH_CUDA_ARCH_LIST=8.9;9.0;12.0 -DUSE_CUDA=1 -DUSE_CUDNN=1 -DUSE_NUMPY=True E:\PyTorch_Build\pytorch CMake Deprecation Warning at CMakeLists.txt:18 (cmake_policy): The OLD behavior for policy CMP0126 will be removed from a future version of CMake. The cmake-policies(7) manual explains that the OLD behaviors of all policies are deprecated and that a policy should be set to OLD only under specific short-term circumstances. Projects should be ported to the NEW behavior and not rely on setting a policy to OLD. -- The CXX compiler identification is MSVC 19.44.35215.0 -- The C compiler identification is MSVC 19.44.35215.0 -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe - skipped -- Detecting C compile features -- Detecting C compile features - done -- Not forcing any particular BLAS to be found CMake Warning at CMakeLists.txt:425 (message): TensorPipe cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:427 (message): KleidiAI cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:439 (message): Libuv is not installed in current conda env. Set USE_DISTRIBUTED to OFF. Please run command 'conda install -c conda-forge libuv=1.39' to install libuv. -- Performing Test C_HAS_AVX_1 -- Performing Test C_HAS_AVX_1 - Success -- Performing Test C_HAS_AVX2_1 -- Performing Test C_HAS_AVX2_1 - Success -- Performing Test C_HAS_AVX512_1 -- Performing Test C_HAS_AVX512_1 - Success -- Performing Test CXX_HAS_AVX_1 -- Performing Test CXX_HAS_AVX_1 - Success -- Performing Test CXX_HAS_AVX2_1 -- Performing Test CXX_HAS_AVX2_1 - Success -- Performing Test CXX_HAS_AVX512_1 -- Performing Test CXX_HAS_AVX512_1 - Success -- Current compiler supports avx2 extension. Will build perfkernels. -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY - Failed -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY - Failed -- Could not find hardware support for NEON on this machine. -- No OMAP3 processor on this machine. -- No OMAP4 processor on this machine. -- Compiler does not support SVE extension. Will not build perfkernels. CMake Warning at CMakeLists.txt:845 (message): x64 operating system is required for FBGEMM. Not compiling with FBGEMM. Turn this warning off by USE_FBGEMM=OFF. -- Performing Test HAS/UTF_8 -- Performing Test HAS/UTF_8 - Success -- Found CUDA: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 (found version "13.0") -- The CUDA compiler identification is NVIDIA 13.0.48 with host compiler MSVC 19.44.35215.0 -- Detecting CUDA compiler ABI info -- Detecting CUDA compiler ABI info - done -- Check for working CUDA compiler: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe - skipped -- Detecting CUDA compile features -- Detecting CUDA compile features - done -- Found CUDAToolkit: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include (found version "13.0.48") -- PyTorch: CUDA detected: 13.0 -- PyTorch: CUDA nvcc is: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- PyTorch: CUDA toolkit directory: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- PyTorch: Header version is: 13.0 -- Found Python: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter CMake Warning at cmake/public/cuda.cmake:140 (message): Failed to compute shorthash for libnvrtc.so Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUDNN (missing: CUDNN_LIBRARY_PATH CUDNN_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:201 (message): Cannot find cuDNN library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUSPARSELT (missing: CUSPARSELT_LIBRARY_PATH CUSPARSELT_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:226 (message): Cannot find cuSPARSELt library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUDSS (missing: CUDSS_LIBRARY_PATH CUDSS_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:242 (message): Cannot find CUDSS library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- USE_CUFILE is set to 0. Compiling without cuFile support CMake Warning at cmake/public/cuda.cmake:317 (message): pytorch is not compatible with `CMAKE_CUDA_ARCHITECTURES` and will ignore its value. Please configure `TORCH_CUDA_ARCH_LIST` instead. Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Added CUDA NVCC flags for: -gencode;arch=compute_89,code=sm_89;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_120,code=sm_120 CMake Warning at cmake/Dependencies.cmake:95 (message): Not compiling with XPU. Could NOT find SYCL. Suppress this warning with -DUSE_XPU=OFF. Call Stack (most recent call first): CMakeLists.txt:873 (include) -- Building using own protobuf under third_party per request. -- Use custom protobuf build. CMake Warning at cmake/ProtoBuf.cmake:37 (message): Ancient protobuf forces CMake compatibility Call Stack (most recent call first): cmake/ProtoBuf.cmake:87 (custom_protobuf_find) cmake/Dependencies.cmake:107 (include) CMakeLists.txt:873 (include) CMake Deprecation Warning at third_party/protobuf/cmake/CMakeLists.txt:2 (cmake_minimum_required): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. -- -- 3.13.0.0 -- Performing Test CMAKE_HAVE_LIBC_PTHREAD -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed -- Looking for pthread_create in pthreads -- Looking for pthread_create in pthreads - not found -- Looking for pthread_create in pthread -- Looking for pthread_create in pthread - not found -- Found Threads: TRUE -- Caffe2 protobuf include directory: $<BUILD_INTERFACE:E:/PyTorch_Build/pytorch/third_party/protobuf/src>$<INSTALL_INTERFACE:include> -- Trying to find preferred BLAS backend of choice: MKL -- MKL_THREADING = OMP -- Looking for sys/types.h -- Looking for sys/types.h - found -- Looking for stdint.h -- Looking for stdint.h - found -- Looking for stddef.h -- Looking for stddef.h - found -- Check size of void* -- Check size of void* - done -- MKL_THREADING = OMP CMake Warning at cmake/Dependencies.cmake:213 (message): MKL could not be found. Defaulting to Eigen Call Stack (most recent call first): CMakeLists.txt:873 (include) CMake Warning at cmake/Dependencies.cmake:279 (message): Preferred BLAS (MKL) cannot be found, now searching for a general BLAS library Call Stack (most recent call first): CMakeLists.txt:873 (include) -- MKL_THREADING = OMP -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_sequential - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_sequential - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - libiomp5md - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - libiomp5md - pthread] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - pthread] -- Library mkl_intel: not found -- Checking for [mkl - guide - pthread - m] -- Library mkl: not found -- MKL library not found -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Checking for [Accelerate] -- Library Accelerate: BLAS_Accelerate_LIBRARY-NOTFOUND -- Checking for [vecLib] -- Library vecLib: BLAS_vecLib_LIBRARY-NOTFOUND -- Checking for [flexiblas] -- Library flexiblas: BLAS_flexiblas_LIBRARY-NOTFOUND -- Checking for [openblas] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m - gomp] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [libopenblas] -- Library libopenblas: BLAS_libopenblas_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran - pthread] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [acml - gfortran] -- Library acml: BLAS_acml_LIBRARY-NOTFOUND -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Could NOT find Atlas (missing: Atlas_CBLAS_INCLUDE_DIR Atlas_CLAPACK_INCLUDE_DIR Atlas_CBLAS_LIBRARY Atlas_BLAS_LIBRARY Atlas_LAPACK_LIBRARY) -- Checking for [ptf77blas - atlas - gfortran] -- Library ptf77blas: BLAS_ptf77blas_LIBRARY-NOTFOUND -- Checking for [] -- Looking for sgemm_ -- Looking for sgemm_ - not found -- Cannot find a library with BLAS API. Not using BLAS. -- Using pocketfft in directory: E:/PyTorch_Build/pytorch/third_party/pocketfft/ CMake Deprecation Warning at third_party/pthreadpool/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at third_party/FXdiv/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at third_party/cpuinfo/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. -- The ASM compiler identification is MSVC CMake Warning (dev) at rtx5070_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineASMCompiler.cmake:234 (message): Policy CMP194 is not set: MSVC is not an assembler for language ASM. Run "cmake --help-policy CMP194" for policy details. Use the cmake_policy command to set the policy and suppress this warning. Call Stack (most recent call first): third_party/XNNPACK/CMakeLists.txt:18 (PROJECT) This warning is for project developers. Use -Wno-dev to suppress it. -- Found assembler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- Building for XNNPACK_TARGET_PROCESSOR: x86_64 -- Generating microkernels.cmake Duplicate microkernel definition: src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avx256vnni.c and src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avxvnni.c (1th function) Duplicate microkernel definition: src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avxvnni.c and src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-scalar.c No microkernel found in src\reference\binary-elementwise.cc No microkernel found in src\reference\packing.cc No microkernel found in src\reference\unary-elementwise.cc -- Found Git: E:/Program Files/Git/cmd/git.exe (found version "2.51.0.windows.1") -- Google Benchmark version: v1.9.3, normalized to 1.9.3 -- Looking for shm_open in rt -- Looking for shm_open in rt - not found -- Performing Test HAVE_CXX_FLAG_WX -- Performing Test HAVE_CXX_FLAG_WX - Success -- Compiling and running to test HAVE_STD_REGEX -- Performing Test HAVE_STD_REGEX -- success -- Compiling and running to test HAVE_GNU_POSIX_REGEX -- Performing Test HAVE_GNU_POSIX_REGEX -- failed to compile -- Compiling and running to test HAVE_POSIX_REGEX -- Performing Test HAVE_POSIX_REGEX -- failed to compile -- Compiling and running to test HAVE_STEADY_CLOCK -- Performing Test HAVE_STEADY_CLOCK -- success -- Compiling and running to test HAVE_PTHREAD_AFFINITY -- Performing Test HAVE_PTHREAD_AFFINITY -- failed to compile CMake Deprecation Warning at third_party/ittapi/CMakeLists.txt:7 (cmake_minimum_required): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Warning at cmake/Dependencies.cmake:749 (message): FP16 is only cmake-2.8 compatible Call Stack (most recent call first): CMakeLists.txt:873 (include) CMake Deprecation Warning at third_party/FP16/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at third_party/psimd/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. -- Using third party subdirectory Eigen. -- Found Python: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter Development.Module NumPy -- Using third_party/pybind11. -- pybind11 include dirs: E:/PyTorch_Build/pytorch/cmake/../third_party/pybind11/include -- Could NOT find OpenTelemetryApi (missing: OpenTelemetryApi_INCLUDE_DIRS) -- Using third_party/opentelemetry-cpp. -- opentelemetry api include dirs: E:/PyTorch_Build/pytorch/cmake/../third_party/opentelemetry-cpp/api/include -- Could NOT find MPI_C (missing: MPI_C_LIB_NAMES MPI_C_HEADER_DIR MPI_C_WORKS) -- Could NOT find MPI_CXX (missing: MPI_CXX_LIB_NAMES MPI_CXX_HEADER_DIR MPI_CXX_WORKS) -- Could NOT find MPI (missing: MPI_C_FOUND MPI_CXX_FOUND) CMake Warning at cmake/Dependencies.cmake:894 (message): Not compiling with MPI. Suppress this warning with -DUSE_MPI=OFF Call Stack (most recent call first): CMakeLists.txt:873 (include) -- MKL_THREADING = OMP -- Check OMP with lib C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib and flags -openmp:experimental -- MKL_THREADING = OMP -- Check OMP with lib C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib and flags -openmp:experimental -- Found OpenMP_C: -openmp:experimental -- Found OpenMP_CXX: -openmp:experimental -- Found OpenMP: TRUE -- Adding OpenMP CXX_FLAGS: -openmp:experimental -- Will link against OpenMP libraries: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib -- Found nvtx3: E:/PyTorch_Build/pytorch/third_party/NVTX/c/include -- ROCM_PATH environment variable is not set and C:/opt/rocm does not exist. Building without ROCm support. -- Found Python3: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter -- ONNX_PROTOC_EXECUTABLE: $<TARGET_FILE:protobuf::protoc> -- Protobuf_VERSION: Protobuf_VERSION_NOTFOUND Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx_onnx_torch-ml.proto Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx-operators_onnx_torch-ml.proto Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx-data_onnx_torch.proto -- -- ******** Summary ******** -- CMake version : 4.1.0 -- CMake command : E:/PyTorch_Build/pytorch/rtx5070_env/Lib/site-packages/cmake/data/bin/cmake.exe -- System : Windows -- C++ compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- C++ compiler version : 19.44.35215.0 -- CXX flags : /DWIN32 /D_WINDOWS /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL /EHsc /wd26812 -- Build type : Release -- Compile definitions : ONNX_ML=1;ONNXIFI_ENABLE_EXT=1 -- CMAKE_PREFIX_PATH : E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages;E:/Program Files/NVIDIA/CUNND/v9.12;E:\Program Files\NVIDIA\CUNND\v9.12;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CMAKE_INSTALL_PREFIX : E:/PyTorch_Build/pytorch/torch -- CMAKE_MODULE_PATH : E:/PyTorch_Build/pytorch/cmake/Modules;E:/PyTorch_Build/pytorch/cmake/public/../Modules_CUDA_fix -- -- ONNX version : 1.18.0 -- ONNX NAMESPACE : onnx_torch -- ONNX_USE_LITE_PROTO : OFF -- USE_PROTOBUF_SHARED_LIBS : OFF -- ONNX_DISABLE_EXCEPTIONS : OFF -- ONNX_DISABLE_STATIC_REGISTRATION : OFF -- ONNX_WERROR : OFF -- ONNX_BUILD_TESTS : OFF -- BUILD_SHARED_LIBS : OFF -- -- Protobuf compiler : $<TARGET_FILE:protobuf::protoc> -- Protobuf includes : -- Protobuf libraries : -- ONNX_BUILD_PYTHON : OFF -- Found CUDA with FP16 support, compiling with torch.cuda.HalfTensor -- Adding -DNDEBUG to compile flags -- Checking prototype magma_get_sgeqrf_nb for MAGMA_V2 -- Checking prototype magma_get_sgeqrf_nb for MAGMA_V2 - False -- MAGMA not found. Compiling without MAGMA support -- Could not find hardware support for NEON on this machine. -- No OMAP3 processor on this machine. -- No OMAP4 processor on this machine. -- MKL_THREADING = OMP -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_sequential - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_sequential - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - libiomp5md - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - libiomp5md - pthread] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - pthread] -- Library mkl_intel: not found -- Checking for [mkl - guide - pthread - m] -- Library mkl: not found -- MKL library not found -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Checking for [Accelerate] -- Library Accelerate: BLAS_Accelerate_LIBRARY-NOTFOUND -- Checking for [vecLib] -- Library vecLib: BLAS_vecLib_LIBRARY-NOTFOUND -- Checking for [flexiblas] -- Library flexiblas: BLAS_flexiblas_LIBRARY-NOTFOUND -- Checking for [openblas] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m - gomp] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [libopenblas] -- Library libopenblas: BLAS_libopenblas_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran - pthread] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [acml - gfortran] -- Library acml: BLAS_acml_LIBRARY-NOTFOUND -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Could NOT find Atlas (missing: Atlas_CBLAS_INCLUDE_DIR Atlas_CLAPACK_INCLUDE_DIR Atlas_CBLAS_LIBRARY Atlas_BLAS_LIBRARY Atlas_LAPACK_LIBRARY) -- Checking for [ptf77blas - atlas - gfortran] -- Library ptf77blas: BLAS_ptf77blas_LIBRARY-NOTFOUND -- Checking for [] -- Cannot find a library with BLAS API. Not using BLAS. -- LAPACK requires BLAS -- Cannot find a library with LAPACK API. Not using LAPACK. disabling ROCM because NOT USE_ROCM is set -- MIOpen not found. Compiling without MIOpen support disabling MKLDNN because USE_MKLDNN is not set -- {fmt} version: 11.2.0 -- Build type: Release -- Using Kineto with CUPTI support -- Configuring Kineto dependency: -- KINETO_SOURCE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto -- KINETO_BUILD_TESTS = OFF -- KINETO_LIBRARY_TYPE = static -- CUDA_SOURCE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CUDA_INCLUDE_DIRS = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include -- CUPTI_INCLUDE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/include -- CUDA_cupti_LIBRARY = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/lib64/cupti.lib -- Found CUPTI CMake Deprecation Warning at third_party/kineto/libkineto/CMakeLists.txt:7 (cmake_minimum_required): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Warning (dev) at third_party/kineto/libkineto/CMakeLists.txt:15 (find_package): Policy CMP0148 is not set: The FindPythonInterp and FindPythonLibs modules are removed. Run "cmake --help-policy CMP0148" for policy details. Use the cmake_policy command to set the policy and suppress this warning. This warning is for project developers. Use -Wno-dev to suppress it. -- Found PythonInterp: E:/PyTorch_Build/pytorch/rtx5070_env/Scripts/python.exe (found version "3.10.10") -- ROCM_SOURCE_DIR = -- Kineto: FMT_SOURCE_DIR = E:/PyTorch_Build/pytorch/third_party/fmt -- Kineto: FMT_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/fmt/include -- CUPTI_INCLUDE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/include -- ROCTRACER_INCLUDE_DIR = /include/roctracer -- DYNOLOG_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto/third_party/dynolog/ -- IPCFABRIC_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto/third_party/dynolog//dynolog/src/ipcfabric/ -- Configured Kineto -- Performing Test HAS/WD4624 -- Performing Test HAS/WD4624 - Success -- Performing Test HAS/WD4068 -- Performing Test HAS/WD4068 - Success -- Performing Test HAS/WD4067 -- Performing Test HAS/WD4067 - Success -- Performing Test HAS/WD4267 -- Performing Test HAS/WD4267 - Success -- Performing Test HAS/WD4661 -- Performing Test HAS/WD4661 - Success -- Performing Test HAS/WD4717 -- Performing Test HAS/WD4717 - Success -- Performing Test HAS/WD4244 -- Performing Test HAS/WD4244 - Success -- Performing Test HAS/WD4804 -- Performing Test HAS/WD4804 - Success -- Performing Test HAS/WD4273 -- Performing Test HAS/WD4273 - Success -- Performing Test HAS_WNO_STRINGOP_OVERFLOW -- Performing Test HAS_WNO_STRINGOP_OVERFLOW - Failed -- -- Architecture: x64 -- Use the C++ compiler to compile (MI_USE_CXX=ON) -- -- Library name : mimalloc -- Version : 2.2.4 -- Build type : release -- C++ Compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- Compiler flags : /Zc:__cplusplus -- Compiler defines : MI_CMAKE_BUILD_TYPE=release;MI_BUILD_RELEASE -- Link libraries : psapi;shell32;user32;advapi32;bcrypt -- Build targets : static -- CMake Error at CMakeLists.txt:1264 (add_subdirectory): The source directory E:/PyTorch_Build/pytorch/torch/headeronly does not contain a CMakeLists.txt file. -- don't use NUMA -- Looking for backtrace -- Looking for backtrace - not found -- Could NOT find Backtrace (missing: Backtrace_LIBRARY Backtrace_INCLUDE_DIR) -- headers outputs: torch\csrc\inductor\aoti_torch\generated\c_shim_cpu.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_cuda.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_aten.h not found -- sources outputs: -- declarations_yaml outputs: -- Performing Test COMPILER_SUPPORTS_NO_AVX256_SPLIT -- Performing Test COMPILER_SUPPORTS_NO_AVX256_SPLIT - Failed -- Using ATen parallel backend: OMP -- Could NOT find OpenSSL, try to set the path to OpenSSL root folder in the system variable OPENSSL_ROOT_DIR (missing: OPENSSL_CRYPTO_LIBRARY OPENSSL_INCLUDE_DIR) -- Check size of long double -- Check size of long double - done -- Performing Test COMPILER_SUPPORTS_FLOAT128 -- Performing Test COMPILER_SUPPORTS_FLOAT128 - Failed -- Performing Test COMPILER_SUPPORTS_SSE2 -- Performing Test COMPILER_SUPPORTS_SSE2 - Success -- Performing Test COMPILER_SUPPORTS_SSE4 -- Performing Test COMPILER_SUPPORTS_SSE4 - Success -- Performing Test COMPILER_SUPPORTS_AVX -- Performing Test COMPILER_SUPPORTS_AVX - Success -- Performing Test COMPILER_SUPPORTS_FMA4 -- Performing Test COMPILER_SUPPORTS_FMA4 - Success -- Performing Test COMPILER_SUPPORTS_AVX2 -- Performing Test COMPILER_SUPPORTS_AVX2 - Success -- Performing Test COMPILER_SUPPORTS_AVX512F -- Performing Test COMPILER_SUPPORTS_AVX512F - Success -- Found OpenMP_C: -openmp:experimental (found version "2.0") -- Found OpenMP_CXX: -openmp:experimental (found version "2.0") -- Found OpenMP_CUDA: -openmp (found version "2.0") -- Found OpenMP: TRUE (found version "2.0") -- Performing Test COMPILER_SUPPORTS_OPENMP -- Performing Test COMPILER_SUPPORTS_OPENMP - Success -- Performing Test COMPILER_SUPPORTS_OMP_SIMD -- Performing Test COMPILER_SUPPORTS_OMP_SIMD - Failed -- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES -- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES - Failed -- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH -- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH - Failed -- Performing Test COMPILER_SUPPORTS_SYS_GETRANDOM -- Performing Test COMPILER_SUPPORTS_SYS_GETRANDOM - Failed -- Configuring build for SLEEF-v3.8.0 Target system: Windows-10.0.26100 Target processor: AMD64 Host system: Windows-10.0.26100 Host processor: AMD64 Detected C compiler: MSVC @ C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe CMake: 4.1.0 Make program: E:/PyTorch_Build/pytorch/rtx5070_env/Scripts/ninja.exe -- Using option `/D_CRT_SECURE_NO_WARNINGS /D_CRT_NONSTDC_NO_DEPRECATE ` to compile libsleef -- Building shared libs : OFF -- Building static test bins: OFF -- MPFR : LIB_MPFR-NOTFOUND -- GMP : LIBGMP-NOTFOUND -- RT : -- FFTW3 : LIBFFTW3-NOTFOUND -- OPENSSL : -- SDE : SDE_COMMAND-NOTFOUND -- COMPILER_SUPPORTS_OPENMP : FALSE AT_INSTALL_INCLUDE_DIR include/ATen/core core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/aten_interned_strings.h core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/enum_tag.h core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/TensorBody.h -- NVSHMEM not found, not building with NVSHMEM support. CMake Error at torch/CMakeLists.txt:3 (add_subdirectory): The source directory E:/PyTorch_Build/pytorch/torch/csrc does not contain a CMakeLists.txt file. CMake Warning at CMakeLists.txt:1285 (message): Generated cmake files are only fully tested if one builds with system glog, gflags, and protobuf. Other settings may generate files that are not well tested. -- -- ******** Summary ******** -- General: -- CMake version : 4.1.0 -- CMake command : E:/PyTorch_Build/pytorch/rtx5070_env/Lib/site-packages/cmake/data/bin/cmake.exe -- System : Windows -- C++ compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- C++ compiler id : MSVC -- C++ compiler version : 19.44.35215.0 -- Using ccache if found : OFF -- CXX flags : /DWIN32 /D_WINDOWS /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE /wd4624 /wd4068 /wd4067 /wd4267 /wd4661 /wd4717 /wd4244 /wd4804 /wd4273 -- Shared LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Static LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Module LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Build type : Release -- Compile definitions : ONNX_ML=1;ONNXIFI_ENABLE_EXT=1;ONNX_NAMESPACE=onnx_torch;_CRT_SECURE_NO_DEPRECATE=1;USE_EXTERNAL_MZCRC;MINIZ_DISABLE_ZIP_READER_CRC32_CHECKS;EXPORT_AOTI_FUNCTIONS;WIN32_LEAN_AND_MEAN;_UCRT_LEGACY_INFINITY;NOMINMAX;USE_MIMALLOC -- CMAKE_PREFIX_PATH : E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages;E:/Program Files/NVIDIA/CUNND/v9.12;E:\Program Files\NVIDIA\CUNND\v9.12;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CMAKE_INSTALL_PREFIX : E:/PyTorch_Build/pytorch/torch -- USE_GOLD_LINKER : OFF -- -- TORCH_VERSION : 2.9.0 -- BUILD_STATIC_RUNTIME_BENCHMARK: OFF -- BUILD_BINARY : OFF -- BUILD_CUSTOM_PROTOBUF : ON -- Link local protobuf : ON -- BUILD_PYTHON : True -- Python version : 3.10.10 -- Python executable : E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -- Python library : E:/Python310/libs/python310.lib -- Python includes : E:/Python310/Include -- Python site-package : E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages -- BUILD_SHARED_LIBS : ON -- CAFFE2_USE_MSVC_STATIC_RUNTIME : OFF -- BUILD_TEST : True -- BUILD_JNI : OFF -- BUILD_MOBILE_AUTOGRAD : OFF -- BUILD_LITE_INTERPRETER: OFF -- INTERN_BUILD_MOBILE : -- TRACING_BASED : OFF -- USE_BLAS : 0 -- USE_LAPACK : 0 -- USE_ASAN : OFF -- USE_TSAN : OFF -- USE_CPP_CODE_COVERAGE : OFF -- USE_CUDA : 1 -- CUDA static link : OFF -- USE_CUDNN : OFF -- USE_CUSPARSELT : OFF -- USE_CUDSS : OFF -- USE_CUFILE : OFF -- CUDA version : 13.0 -- USE_FLASH_ATTENTION : OFF -- USE_MEM_EFF_ATTENTION : ON -- CUDA root directory : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CUDA library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cuda.lib -- cudart library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cudart.lib -- cublas library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cublas.lib -- cufft library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cufft.lib -- curand library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/curand.lib -- cusparse library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cusparse.lib -- nvrtc : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/nvrtc.lib -- CUDA include path : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include -- NVCC executable : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- CUDA compiler : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- CUDA flags : -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xcompiler /Zc:__cplusplus -Xcompiler /w -w -Xcompiler /FS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch --use-local-env -gencode arch=compute_89,code=sm_89 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --Werror cross-execution-space-call --no-host-device-move-forward --expt-relaxed-constexpr --expt-extended-lambda -Xcompiler=/wd4819,/wd4503,/wd4190,/wd4244,/wd4251,/wd4275,/wd4522 -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -- CUDA host compiler : -- CUDA --device-c : OFF -- USE_TENSORRT : -- USE_XPU : OFF -- USE_ROCM : OFF -- BUILD_NVFUSER : -- USE_EIGEN_FOR_BLAS : ON -- USE_EIGEN_FOR_SPARSE : OFF -- USE_FBGEMM : OFF -- USE_KINETO : ON -- USE_GFLAGS : OFF -- USE_GLOG : OFF -- USE_LITE_PROTO : OFF -- USE_PYTORCH_METAL : OFF -- USE_PYTORCH_METAL_EXPORT : OFF -- USE_MPS : OFF -- CAN_COMPILE_METAL : -- USE_MKL : OFF -- USE_MKLDNN : OFF -- USE_UCC : OFF -- USE_ITT : ON -- USE_XCCL : OFF -- USE_NCCL : OFF -- Found NVSHMEM : -- USE_NNPACK : OFF -- USE_NUMPY : ON -- USE_OBSERVERS : ON -- USE_OPENCL : OFF -- USE_OPENMP : ON -- USE_MIMALLOC : ON -- USE_MIMALLOC_ON_MKL : OFF -- USE_VULKAN : OFF -- USE_PROF : OFF -- USE_PYTORCH_QNNPACK : OFF -- USE_XNNPACK : ON -- USE_DISTRIBUTED : OFF -- Public Dependencies : -- Private Dependencies : Threads::Threads;pthreadpool;cpuinfo;XNNPACK;microkernels-prod;ittnotify;fp16;caffe2::openmp;fmt::fmt-header-only;kineto -- Public CUDA Deps. : -- Private CUDA Deps. : caffe2::curand;caffe2::cufft;caffe2::cublas;fmt::fmt-header-only;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cudart_static.lib;CUDA::cusparse;CUDA::cufft;CUDA::cusolver;ATEN_CUDA_FILES_GEN_LIB -- USE_COREML_DELEGATE : OFF -- BUILD_LAZY_TS_BACKEND : ON -- USE_ROCM_KERNEL_ASSERT : OFF -- Performing Test HAS_WMISSING_PROTOTYPES -- Performing Test HAS_WMISSING_PROTOTYPES - Failed -- Performing Test HAS_WERROR_MISSING_PROTOTYPES -- Performing Test HAS_WERROR_MISSING_PROTOTYPES - Failed -- Configuring incomplete, errors occurred! (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装生成的包 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $wheelPath = Get-ChildItem dist\*.whl | Select-Object -First 1 Get-ChildItem: Cannot find path 'E:\PyTorch_Build\pytorch\dist' because it does not exist. (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install $wheelPath --force-reinstall --no-deps ERROR: You must give at least one requirement to install (see "pip help install") (rtx5070_env) PS E:\PyTorch_Build\pytorch> python diagnostic_test.py ================================================== CUDA Toolkit 验证: ✅ NVCC 版本: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 ✅ NVIDIA-SMI 输出: Mon Sep 1 20:54:10 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.97 Driver Version: 580.97 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Driver-Model | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 5070 WDDM | 00000000:01:00.0 On | N/A | | 0% 35C P3 16W / 250W | 1328MiB / 12227MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 C+G ...yb3d8bbwe\WindowsTerminal.exe N/A | | 0 N/A N/A 1288 C+G ...les\Tencent\Weixin\Weixin.exe N/A | | 0 N/A N/A 1776 C+G C:\Windows\System32\dwm.exe N/A | | 0 N/A N/A 2272 C+G ...t\Edge\Application\msedge.exe N/A | | 0 N/A N/A 3268 C+G ...em32\ApplicationFrameHost.exe N/A | | 0 N/A N/A 7860 C+G C:\Windows\explorer.exe N/A | | 0 N/A N/A 8004 C+G ...indows\System32\ShellHost.exe N/A | | 0 N/A N/A 8156 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 8852 C+G ..._cw5n1h2txyewy\SearchHost.exe N/A | | 0 N/A N/A 8876 C+G ...y\StartMenuExperienceHost.exe N/A | | 0 N/A N/A 10540 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 12380 C+G ...5n1h2txyewy\TextInputHost.exe N/A | | 0 N/A N/A 15340 C+G ...acted\runtime\WeChatAppEx.exe N/A | | 0 N/A N/A 18600 C+G ...ntrolPanel\SystemSettings.exe N/A | +-----------------------------------------------------------------------------------------+ ================================================== ❌ 严重错误发生: Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 116, in <module> check_cuda_toolkit() File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 21, in check_cuda_toolkit cuda_path = os.environ.get('CUDA_PATH', '未设置') NameError: name 'os' is not defined 按 Enter 键退出... (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 卸载现有版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip uninstall -y torch torchvision torchaudio WARNING: Skipping torch as it is not installed. WARNING: Skipping torchvision as it is not installed. WARNING: Skipping torchaudio as it is not installed. (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装支持 RTX 5070 的预编译版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install --pre torch torchvision torchaudio ` >> --index-url https://download.pytorch.org/whl/nightly/cu121 ` >> --no-deps Looking in indexes: https://download.pytorch.org/whl/nightly/cu121 Collecting torch Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.6.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (2456.2 MB) Collecting torchvision Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.20.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (6.2 MB) Collecting torchaudio Using cached https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.5.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (4.2 MB) Installing collected packages: torchaudio, torchvision, torch Successfully installed torch-2.6.0.dev20241112+cu121 torchaudio-2.5.0.dev20241112+cu121 torchvision-0.20.0.dev20241112+cu121 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) Requirement already satisfied: mkl in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: mkl-include in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: intel-openmp in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.1) Requirement already satisfied: tbb==2022.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from mkl) (2022.2.0) Requirement already satisfied: intel-cmplr-lib-ur==2025.2.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-openmp) (2025.2.1) Requirement already satisfied: umf==0.11.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) (0.11.0) Requirement already satisfied: tcmlib==1.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from tbb==2022.*->mkl) (1.4.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 执行诊断测试 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python diagnostic_test.py ================================================== CUDA Toolkit 验证: ✅ NVCC 版本: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 ✅ NVIDIA-SMI 输出: Mon Sep 1 20:55:52 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.97 Driver Version: 580.97 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Driver-Model | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 5070 WDDM | 00000000:01:00.0 On | N/A | | 0% 35C P3 19W / 250W | 1346MiB / 12227MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 C+G ...yb3d8bbwe\WindowsTerminal.exe N/A | | 0 N/A N/A 1288 C+G ...les\Tencent\Weixin\Weixin.exe N/A | | 0 N/A N/A 1776 C+G C:\Windows\System32\dwm.exe N/A | | 0 N/A N/A 2272 C+G ...t\Edge\Application\msedge.exe N/A | | 0 N/A N/A 3268 C+G ...em32\ApplicationFrameHost.exe N/A | | 0 N/A N/A 7860 C+G C:\Windows\explorer.exe N/A | | 0 N/A N/A 8004 C+G ...indows\System32\ShellHost.exe N/A | | 0 N/A N/A 8156 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 8852 C+G ..._cw5n1h2txyewy\SearchHost.exe N/A | | 0 N/A N/A 8876 C+G ...y\StartMenuExperienceHost.exe N/A | | 0 N/A N/A 10540 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 12380 C+G ...5n1h2txyewy\TextInputHost.exe N/A | | 0 N/A N/A 15340 C+G ...acted\runtime\WeChatAppEx.exe N/A | | 0 N/A N/A 18600 C+G ...ntrolPanel\SystemSettings.exe N/A | +-----------------------------------------------------------------------------------------+ ================================================== ❌ 严重错误发生: Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 116, in <module> check_cuda_toolkit() File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 21, in check_cuda_toolkit cuda_path = os.environ.get('CUDA_PATH', '未设置') NameError: name 'os' is not defined 按 Enter 键退出... (rtx5070_env) PS E:\PyTorch_Build\pytorch>
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