pytorch - 💡(How to fix) Fix `torch.cuda.get_device_capability()` provides wrong version recommendation [1 comments, 2 participants]

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pytorch/pytorch#182250Fetched 2026-05-04 04:57:58
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Fix Action

Fix / Workaround

CPU: Architektur: x86_64 CPU Operationsmodus: 32-bit, 64-bit Byte-Reihenfolge: Little Endian Adressgrößen: 46 bits physical, 48 bits virtual CPU(s): 64 Liste der Online-CPU(s): 0-63 Thread(s) pro Kern: 2 Kern(e) pro Socket: 16 Sockel: 2 NUMA-Knoten: 2 Anbieterkennung: GenuineIntel Prozessorfamilie: 6 Modell: 85 Modellname: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz Stepping: 7 CPU MHz: 1237.698 Maximale Taktfrequenz der CPU: 3900,0000 Minimale Taktfrequenz der CPU: 1000,0000 BogoMIPS: 4600.00 Virtualisierung: VT-x L1d Cache: 1 MiB L1i Cache: 1 MiB L2 Cache: 32 MiB L3 Cache: 44 MiB NUMA-Knoten0 CPU(s): 0-15,32-47 NUMA-Knoten1 CPU(s): 16-31,48-63 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Retbleed: Mitigation; Enhanced IBRS 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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled Markierungen: 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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

CPU: Architektur: x86_64 CPU Operationsmodus: 32-bit, 64-bit Byte-Reihenfolge: Little Endian Adressgrößen: 46 bits physical, 48 bits virtual CPU(s): 64 Liste der Online-CPU(s): 0-63 Thread(s) pro Kern: 2 Kern(e) pro Socket: 16 Sockel: 2 NUMA-Knoten: 2 Anbieterkennung: GenuineIntel Prozessorfamilie: 6 Modell: 85 Modellname: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz Stepping: 7 CPU MHz: 1000.049 Maximale Taktfrequenz der CPU: 3900,0000 Minimale Taktfrequenz der CPU: 1000,0000 BogoMIPS: 4600.00 Virtualisierung: VT-x L1d Cache: 1 MiB L1i Cache: 1 MiB L2 Cache: 32 MiB L3 Cache: 44 MiB NUMA-Knoten0 CPU(s): 0-15,32-47 NUMA-Knoten1 CPU(s): 16-31,48-63 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Retbleed: Mitigation; Enhanced IBRS 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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled Markierungen: 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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Code Example

Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8

---

import torch
torch.cuda.get_device_capability()

---

[project]
name = "test-torch-2-11"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
    "torch>=2.11.0",
    "torchvision>=0.21.0",
]

[[tool.uv.index]]
name = "pytorch-cu126"
url = "https://download.pytorch.org/whl/cu126"
explicit = true

[tool.uv.sources]
torch = [
  { index = "pytorch-cu126", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]
torchvision = [
  { index = "pytorch-cu126", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]

---

Collecting environment information...
/home/matti/test/test_torch_2.7/.venv/lib/python3.12/site-packages/torch/cuda/__init__.py:371: UserWarning: Found GPU0 Tesla V100-PCIE-32GB which is of compute capability (CC) 7.0.
The following list shows the CCs this version of PyTorch was built for and the hardware CCs it supports:
- 7.5 which supports hardware CC >=7.5,<8.0
- 8.0 which supports hardware CC >=8.0,<9.0 except {8.7}
- 8.6 which supports hardware CC >=8.6,<9.0 except {8.7}
- 9.0 which supports hardware CC >=9.0,<10.0
- 10.0 which supports hardware CC >=10.0,<11.0 except {10.1}
- 12.0 which supports hardware CC >=12.0,<13.0
Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8
  _warn_unsupported_code(d, device_cc, code_ccs)
/home/matti/test/test_torch_2.7/.venv/lib/python3.12/site-packages/torch/cuda/__init__.py:371: UserWarning: Found GPU1 Tesla V100-PCIE-32GB which is of compute capability (CC) 7.0.
The following list shows the CCs this version of PyTorch was built for and the hardware CCs it supports:
- 7.5 which supports hardware CC >=7.5,<8.0
- 8.0 which supports hardware CC >=8.0,<9.0 except {8.7}
- 8.6 which supports hardware CC >=8.6,<9.0 except {8.7}
- 9.0 which supports hardware CC >=9.0,<10.0
- 10.0 which supports hardware CC >=10.0,<11.0 except {10.1}
- 12.0 which supports hardware CC >=12.0,<13.0
Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8
  _warn_unsupported_code(d, device_cc, code_ccs)
PyTorch version: 2.11.0+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 8.4.0-3ubuntu2) 8.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.12.3 (main, Apr 15 2024, 18:25:56) [Clang 17.0.6 ] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration:
GPU 0: Tesla V100-PCIE-32GB
GPU 1: Tesla V100-PCIE-32GB

Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A

CPU:
Architektur:                        x86_64
CPU Operationsmodus:                32-bit, 64-bit
Byte-Reihenfolge:                   Little Endian
Adressgrößen:                       46 bits physical, 48 bits virtual
CPU(s):                             64
Liste der Online-CPU(s):            0-63
Thread(s) pro Kern:                 2
Kern(e) pro Socket:                 16
Sockel:                             2
NUMA-Knoten:                        2
Anbieterkennung:                    GenuineIntel
Prozessorfamilie:                   6
Modell:                             85
Modellname:                         Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz
Stepping:                           7
CPU MHz:                            1237.698
Maximale Taktfrequenz der CPU:      3900,0000
Minimale Taktfrequenz der CPU:      1000,0000
BogoMIPS:                           4600.00
Virtualisierung:                    VT-x
L1d Cache:                          1 MiB
L1i Cache:                          1 MiB
L2 Cache:                           32 MiB
L3 Cache:                           44 MiB
NUMA-Knoten0 CPU(s):                0-15,32-47
NUMA-Knoten1 CPU(s):                16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        KVM: Mitigation: Split huge pages
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Mitigation; Enhanced IBRS
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; TSX disabled
Markierungen:                       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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect

---

Collecting environment information...
PyTorch version: 2.11.0+cu126
Is debug build: False
CUDA used to build PyTorch: 12.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 8.4.0-3ubuntu2) 8.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.12.3 (main, Apr 15 2024, 18:25:56) [Clang 17.0.6 ] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration:
GPU 0: Tesla V100-PCIE-32GB
GPU 1: Tesla V100-PCIE-32GB

Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A

CPU:
Architektur:                        x86_64
CPU Operationsmodus:                32-bit, 64-bit
Byte-Reihenfolge:                   Little Endian
Adressgrößen:                       46 bits physical, 48 bits virtual
CPU(s):                             64
Liste der Online-CPU(s):            0-63
Thread(s) pro Kern:                 2
Kern(e) pro Socket:                 16
Sockel:                             2
NUMA-Knoten:                        2
Anbieterkennung:                    GenuineIntel
Prozessorfamilie:                   6
Modell:                             85
Modellname:                         Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz
Stepping:                           7
CPU MHz:                            1000.049
Maximale Taktfrequenz der CPU:      3900,0000
Minimale Taktfrequenz der CPU:      1000,0000
BogoMIPS:                           4600.00
Virtualisierung:                    VT-x
L1d Cache:                          1 MiB
L1i Cache:                          1 MiB
L2 Cache:                           32 MiB
L3 Cache:                           44 MiB
NUMA-Knoten0 CPU(s):                0-15,32-47
NUMA-Knoten1 CPU(s):                16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        KVM: Mitigation: Split huge pages
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Mitigation; Enhanced IBRS
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; TSX disabled
Markierungen:                       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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect
RAW_BUFFERClick to expand / collapse

🐛 Describe the bug

When executing the code from below on a system with a V100 the recommendation states:

Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8

But the installed version is cu128. I tested the same approach with cu126 and the warning is not displayed.

import torch
torch.cuda.get_device_capability()

Versions

Version switched via pyproject.toml:

[project]
name = "test-torch-2-11"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
    "torch>=2.11.0",
    "torchvision>=0.21.0",
]

[[tool.uv.index]]
name = "pytorch-cu126"
url = "https://download.pytorch.org/whl/cu126"
explicit = true

[tool.uv.sources]
torch = [
  { index = "pytorch-cu126", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]
torchvision = [
  { index = "pytorch-cu126", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]

with 2.11.0+cu128:

Collecting environment information...
/home/matti/test/test_torch_2.7/.venv/lib/python3.12/site-packages/torch/cuda/__init__.py:371: UserWarning: Found GPU0 Tesla V100-PCIE-32GB which is of compute capability (CC) 7.0.
The following list shows the CCs this version of PyTorch was built for and the hardware CCs it supports:
- 7.5 which supports hardware CC >=7.5,<8.0
- 8.0 which supports hardware CC >=8.0,<9.0 except {8.7}
- 8.6 which supports hardware CC >=8.6,<9.0 except {8.7}
- 9.0 which supports hardware CC >=9.0,<10.0
- 10.0 which supports hardware CC >=10.0,<11.0 except {10.1}
- 12.0 which supports hardware CC >=12.0,<13.0
Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8
  _warn_unsupported_code(d, device_cc, code_ccs)
/home/matti/test/test_torch_2.7/.venv/lib/python3.12/site-packages/torch/cuda/__init__.py:371: UserWarning: Found GPU1 Tesla V100-PCIE-32GB which is of compute capability (CC) 7.0.
The following list shows the CCs this version of PyTorch was built for and the hardware CCs it supports:
- 7.5 which supports hardware CC >=7.5,<8.0
- 8.0 which supports hardware CC >=8.0,<9.0 except {8.7}
- 8.6 which supports hardware CC >=8.6,<9.0 except {8.7}
- 9.0 which supports hardware CC >=9.0,<10.0
- 10.0 which supports hardware CC >=10.0,<11.0 except {10.1}
- 12.0 which supports hardware CC >=12.0,<13.0
Please follow the instructions at https://pytorch.org/get-started/locally/ to install a PyTorch release that supports one of these CUDA versions: 12.6, 12.8
  _warn_unsupported_code(d, device_cc, code_ccs)
PyTorch version: 2.11.0+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 8.4.0-3ubuntu2) 8.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.12.3 (main, Apr 15 2024, 18:25:56) [Clang 17.0.6 ] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration:
GPU 0: Tesla V100-PCIE-32GB
GPU 1: Tesla V100-PCIE-32GB

Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A

CPU:
Architektur:                        x86_64
CPU Operationsmodus:                32-bit, 64-bit
Byte-Reihenfolge:                   Little Endian
Adressgrößen:                       46 bits physical, 48 bits virtual
CPU(s):                             64
Liste der Online-CPU(s):            0-63
Thread(s) pro Kern:                 2
Kern(e) pro Socket:                 16
Sockel:                             2
NUMA-Knoten:                        2
Anbieterkennung:                    GenuineIntel
Prozessorfamilie:                   6
Modell:                             85
Modellname:                         Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz
Stepping:                           7
CPU MHz:                            1237.698
Maximale Taktfrequenz der CPU:      3900,0000
Minimale Taktfrequenz der CPU:      1000,0000
BogoMIPS:                           4600.00
Virtualisierung:                    VT-x
L1d Cache:                          1 MiB
L1i Cache:                          1 MiB
L2 Cache:                           32 MiB
L3 Cache:                           44 MiB
NUMA-Knoten0 CPU(s):                0-15,32-47
NUMA-Knoten1 CPU(s):                16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        KVM: Mitigation: Split huge pages
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Mitigation; Enhanced IBRS
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; TSX disabled
Markierungen:                       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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect

with 2.11.0+cu126:

Collecting environment information...
PyTorch version: 2.11.0+cu126
Is debug build: False
CUDA used to build PyTorch: 12.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 8.4.0-3ubuntu2) 8.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.12.3 (main, Apr 15 2024, 18:25:56) [Clang 17.0.6 ] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration:
GPU 0: Tesla V100-PCIE-32GB
GPU 1: Tesla V100-PCIE-32GB

Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A

CPU:
Architektur:                        x86_64
CPU Operationsmodus:                32-bit, 64-bit
Byte-Reihenfolge:                   Little Endian
Adressgrößen:                       46 bits physical, 48 bits virtual
CPU(s):                             64
Liste der Online-CPU(s):            0-63
Thread(s) pro Kern:                 2
Kern(e) pro Socket:                 16
Sockel:                             2
NUMA-Knoten:                        2
Anbieterkennung:                    GenuineIntel
Prozessorfamilie:                   6
Modell:                             85
Modellname:                         Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz
Stepping:                           7
CPU MHz:                            1000.049
Maximale Taktfrequenz der CPU:      3900,0000
Minimale Taktfrequenz der CPU:      1000,0000
BogoMIPS:                           4600.00
Virtualisierung:                    VT-x
L1d Cache:                          1 MiB
L1i Cache:                          1 MiB
L2 Cache:                           32 MiB
L3 Cache:                           44 MiB
NUMA-Knoten0 CPU(s):                0-15,32-47
NUMA-Knoten1 CPU(s):                16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        KVM: Mitigation: Split huge pages
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Mitigation; Enhanced IBRS
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; TSX disabled
Markierungen:                       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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx 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 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect

cc @ptrblck @msaroufim @eqy @jerryzh168 @tinglvv @nWEIdia

extent analysis

TL;DR

The warning about unsupported CUDA versions can be resolved by installing a PyTorch release that supports one of the recommended CUDA versions, such as 12.6 or 12.8, which is compatible with the Tesla V100-PCIE-32GB GPU.

Guidance

  • The issue arises from a mismatch between the CUDA version used to build PyTorch and the compute capability of the Tesla V100-PCIE-32GB GPU.
  • To resolve the warning, install a PyTorch version that supports CUDA 12.6, such as 2.11.0+cu126, as it is compatible with the GPU's compute capability.
  • Verify the fix by checking the PyTorch version and CUDA support after installation.
  • If the warning persists, ensure that the CUDA runtime version is compatible with the PyTorch version.

Example

No code changes are required, but the PyTorch version needs to be updated. For example, use 2.11.0+cu126 instead of 2.11.0+cu128 in the pyproject.toml file:

dependencies = [
    "torch>=2.11.0+cu126",
    "torchvision>=0.21.0",
]

Notes

The fix assumes that the Tesla V100-PCIE-32GB GPU is the only GPU being used. If multiple GPUs with different compute capabilities are being used, a different PyTorch version may be required.

Recommendation

Apply the workaround by installing a PyTorch version that supports CUDA 12.6, such as 2.11.0+cu126, to resolve the warning and ensure compatibility with the Tesla V100-PCIE-32GB GPU.

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