NVIDIA
Unable to install Apex
Describe the Bug
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ Using pip 24.0 from /home/un-gpu/py3.10/lib/python3.10/site-packages/pip (python 3.10) Processing /home/un-gpu/Project/apex Running command Preparing metadata (pyproject.toml)
torch.version = 2.4.0+cu118
running dist_info creating /tmp/pip-modern-metadata-n8s_st0m/apex.egg-info writing /tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/PKG-INFO writing dependency_links to /tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/dependency_links.txt writing requirements to /tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/requires.txt writing top-level names to /tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/top_level.txt writing manifest file '/tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/SOURCES.txt' reading manifest file '/tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/SOURCES.txt' adding license file 'LICENSE' writing manifest file '/tmp/pip-modern-metadata-n8s_st0m/apex.egg-info/SOURCES.txt' creating '/tmp/pip-modern-metadata-n8s_st0m/apex-0.1.dist-info' error: invalid command 'bdist_wheel' error: subprocess-exited-with-error
× Preparing metadata (pyproject.toml) 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/un-gpu/py3.10/bin/python3.10 /home/un-gpu/py3.10/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py prepare_metadata_for_build_wheel /tmp/tmpnzqd77yy cwd: /home/un-gpu/Project/apex Preparing metadata (pyproject.toml) ... error error: metadata-generation-failed
× Encountered error while generating package metadata. ╰─> See above for output.
note: This is an issue with the package mentioned above, not pip. hint: See above for details.
Minimal Steps/Code to Reproduce the Bug
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./
Expected Behavior Installing Apex successfully.
Environment /usr/lib/python3.10/runpy.py:126: RuntimeWarning: 'torch.utils.collect_env' found in sys.modules after import of package 'torch.utils', but prior to execution of 'torch.utils.collect_env'; this may result in unpredictable behaviour warn(RuntimeWarning(msg)) Collecting environment information... PyTorch version: 2.4.0+cu118 Is debug build: False CUDA used to build PyTorch: 11.8 ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version: Could not collect CMake version: version 3.29.0 Libc version: glibc-2.31
Python version: 3.10.13 (main, Aug 25 2023, 13:20:03) [GCC 9.4.0] (64-bit runtime) Python platform: Linux-5.15.0-117-generic-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 11.8.89 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1070 GPU 1: NVIDIA GeForce GTX 1070
Nvidia driver version: 550.54.14 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True
CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 12 On-line CPU(s) list: 0-11 Thread(s) per core: 2 Core(s) per socket: 6 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 63 Model name: Intel(R) Core(TM) i7-5930K CPU @ 3.50GHz Stepping: 2 CPU MHz: 1200.000 CPU max MHz: 3700.0000 CPU min MHz: 1200.0000 BogoMIPS: 6999.83 L1d cache: 192 KiB L1i cache: 192 KiB L2 cache: 1.5 MiB L3 cache: 15 MiB NUMA node0 CPU(s): 0-11 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported Vulnerability L1tf: Mitigation; PTE Inversion Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti intel_ppin ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm xsaveopt cqm_llc cqm_occup_llc dtherm ida arat pln pts md_clear flush_l1d
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] pytorch-lightning==2.2.4
[pip3] pytorch-triton==3.0.0+dedb7bdf33
[pip3] torch==2.4.0+cu118
[pip3] torchaudio==2.4.0+cu118
[pip3] torchmetrics==1.4.0
[pip3] torchvision==0.19.0+cu118
[pip3] triton==3.0.0
[conda] blas 1.0 mkl
[conda] mkl 2021.2.0 h06a4308_296
[conda] mkl-service 2.3.0 py38h27cfd23_1
[conda] mkl_fft 1.3.0 py38h42c9631_2
[conda] mkl_random 1.2.1 py38ha9443f7_2
[conda] numpy 1.20.1 py38h93e21f0_0
[conda] numpy-base 1.20.1 py38h7d8b39e_0
[conda] numpydoc 1.1.0 pyhd3eb1b0_1
Maybe you can try this, i solved an non-reason install problem (doing correct steps in apex's readme) using this:
git checkout origin/22.02-parallel-state # or another vesion
python setup.py install --cuda_ext --cpp_ext
pip3 install -v --no-cache-dir ./
It is amazing that apex can't be installed using master branch for some cuda version.
Maybe you can try this, i solved an non-reason install problem (doing correct steps in apex's readme) using this:
git checkout origin/22.02-parallel-state # or another vesion python setup.py install --cuda_ext --cpp_ext pip3 install -v --no-cache-dir ./ It is amazing that apex can't be installed using master branch for some cuda version.
thanks！！！！
