Build from Source Failed

Mahir_Atmis: <p>I get the following error when I try to build pytorch from source. Any help is appreciated. The detailed log file is provided in the <a href="https://drive.google.com/file/d/1QEVE_Ebzi_IpmCRoroa_ZG_-uUgQc35N/view?usp=sharing" rel="nofollow noopener">link</a>.</p>
<p>Traceback (most recent call last):<br>
File “setup.py”, line 737, in <br>
build_deps()<br>
File “setup.py”, line 316, in build_deps<br>
cmake=cmake)<br>
File “/home/z840/pytorch/tools/build_pytorch_libs.py”, line 62, in build_caffe2<br>
cmake.build(my_env)<br>
File “/home/z840/pytorch/tools/setup_helpers/cmake.py”, line 339, in build<br>
self.run(build_args, my_env)<br>
File “/home/z840/pytorch/tools/setup_helpers/cmake.py”, line 141, in run<br>
check_call(command, cwd=self.build_dir, env=env)<br>
File “/home/z840/miniconda3/envs/p37_build/lib/python3.7/subprocess.py”, line 363, in check_call<br>
raise CalledProcessError(retcode, cmd)<br>
subprocess.CalledProcessError: Command ‘[‘cmake’, ‘–build’, ‘.’, ‘–target’, ‘install’, ‘–config’, ‘Release’, ‘–’, ‘-j’, ‘40’]’ returned non-zero exit status 1.</p>
<p>------------- MY SYSTEM AND CONFIGURATIONS -------<br>
<strong>uname -a</strong><br>
Linux z840-HP-Z840-Workstation 5.3.0-40-generic #32~18.04.1-Ubuntu SMP Mon Feb 3 14:05:59 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux<br>
<strong>nvidia-smi</strong><br>
Thu Mar  5 20:42:56 2020<br>
±----------------------------------------------------------------------------+<br>
| NVIDIA-SMI 435.21       Driver Version: 435.21       CUDA Version: 10.1     |<br>
|-------------------------------±---------------------±---------------------+<br>
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |<br>
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |<br>
|===============================+======================+======================|<br>
|   0  Quadro K4200        Off  | 00000000:04:00.0  On |                  N/A |<br>
| 37%   73C    P0    44W / 110W |    321MiB /  4034MiB |      6%      Default |<br>
±------------------------------±---------------------±---------------------+</p>
<p>±----------------------------------------------------------------------------+<br>
| Processes:                                                       GPU Memory |<br>
|  GPU       PID   Type   Process name                             Usage      |<br>
|=============================================================================|<br>
|    0      1480      G   /usr/lib/xorg/Xorg                           141MiB |<br>
|    0      1732      G   /usr/bin/gnome-shell                         104MiB |<br>
|    0      2229      C   /usr/NX/bin/nxnode.bin                        61MiB |<br>
±----------------------------------------------------------------------------+</p>
<p><strong>The commands I used are:</strong><br>
conda create --name p37_build python=3.7<br>
conda activate p37_build<br>
conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing<br>
git clone --recursive <a href="https://github.com/pytorch/pytorch" rel="nofollow noopener">https://github.com/pytorch/pytorch</a><br>
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/…/"}<br>
export USE_CUDA=1 USE_CUDNN=1 USE_MKLDNN=1<br>
cd pytorch/<br>
python setup.py install 2&gt;&amp;1 &gt; build.log</p>

albanD: <p>There seem to be some errors fiding/compiling cuda files.</p>
<p>Note that a recent change means that you have to run <code>python setup.py clean</code> if you ever installed in this folder before (we are fixing that). Do you see the same thing after cleaning?</p>

Mahir_Atmis: <p>I deleted everything(environments and downloaded pytorch files). Then re-downloaded pytorch and created a new environment with another name. Still getting error messages. The new build log is on the <a href="https://drive.google.com/file/d/1kVwofoXjosf7iQ473E1n0qWs06OfneLm/view?usp=sharing" rel="nofollow noopener">link</a>.<br>
Before starting building, I ran some commands and the results are as follows:<br>
<strong>./bin/x86_64/linux/release/bandwidthTest</strong><br>
[CUDA Bandwidth Test] - Starting…<br>
Running on…</p>
<p>Device 0: Quadro K4200<br>
Quick Mode</p>
<p>Host to Device Bandwidth, 1 Device(s)<br>
PINNED Memory Transfers<br>
Transfer Size (Bytes)	Bandwidth(GB/s)<br>
32000000			6.1</p>
<p>Device to Host Bandwidth, 1 Device(s)<br>
PINNED Memory Transfers<br>
Transfer Size (Bytes)	Bandwidth(GB/s)<br>
32000000			6.6</p>
<p>Device to Device Bandwidth, 1 Device(s)<br>
PINNED Memory Transfers<br>
Transfer Size (Bytes)	Bandwidth(GB/s)<br>
32000000			136.5</p>
<p>Result = PASS</p>
<p>NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.</p>
<p><strong>./bin/x86_64/linux/release/deviceQuery</strong><br>
CUDA Device Query (Runtime API) version (CUDART static linking)</p>
<h2>Detected 1 CUDA Capable device(s)</h2>
<p>Device 0: “Quadro K4200”<br>
CUDA Driver Version / Runtime Version          10.1 / 10.1<br>
CUDA Capability Major/Minor version number:    3.0<br>
Total amount of global memory:                 4034 MBytes (4230086656 bytes)<br>
( 7) Multiprocessors, (192) CUDA Cores/MP:     1344 CUDA Cores<br>
GPU Max Clock rate:                            784 MHz (0.78 GHz)<br>
Memory Clock rate:                             2700 Mhz<br>
Memory Bus Width:                              256-bit<br>
L2 Cache Size:                                 524288 bytes<br>
Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)<br>
Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 layers<br>
Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 2048 layers<br>
Total amount of constant memory:               65536 bytes<br>
Total amount of shared memory per block:       49152 bytes<br>
Total number of registers available per block: 65536<br>
Warp size:                                     32<br>
Maximum number of threads per multiprocessor:  2048<br>
Maximum number of threads per block:           1024<br>
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)<br>
Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)<br>
Maximum memory pitch:                          2147483647 bytes<br>
Texture alignment:                             512 bytes<br>
Concurrent copy and kernel execution:          Yes with 2 copy engine(s)<br>
Run time limit on kernels:                     Yes<br>
Integrated GPU sharing Host Memory:            No<br>
Support host page-locked memory mapping:       Yes<br>
Alignment requirement for Surfaces:            Yes<br>
Device has ECC support:                        Disabled<br>
Device supports Unified Addressing (UVA):      Yes<br>
Device supports Compute Preemption:            No<br>
Supports Cooperative Kernel Launch:            No<br>
Supports MultiDevice Co-op Kernel Launch:      No<br>
Device PCI Domain ID / Bus ID / location ID:   0 / 4 / 0<br>
Compute Mode:<br>
&lt; Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) &gt;</p>
<h2>deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.1, CUDA Runtime Version = 10.1, NumDevs = 1<br>
Result = PASS</h2>
<p><strong>nvcc -V</strong><br>
nvcc: NVIDIA ® Cuda compiler driver<br>
Copyright © 2005-2019 NVIDIA Corporation<br>
Built on Fri_Feb__8_19:08:17_PST_2019<br>
Cuda compilation tools, release 10.1, V10.1.105</p>

albanD: <p>Hi,</p>
<p>I’m afraid the main reason is that the latest officially supported compute capability is 3.5 while your device is 3.0 <img src="https://discuss.pytorch.org/images/emoji/apple/confused.png?v=9" title=":confused:" class="emoji" alt=":confused:"><br>
So I guess we have code in these files that only work for compute capability 3.5+<br>
<a class="mention" href="/u/smth">@smth</a> who should I ping to double check and add a nicer error message here?</p>