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Please add host CPU architecture as a row in the "Start Locally" configuration matrix #1687

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phs opened this issue Jul 24, 2024 · 0 comments
Open

Please add host CPU architecture as a row in the "Start Locally" configuration matrix #1687

phs opened this issue Jul 24, 2024 · 0 comments

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@phs
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phs commented Jul 24, 2024

📚 Documentation

The matrix I refer to is this, as appearing on https://pytorch.org/get-started/locally/ :

image

It might appear underneath the "Your OS" row, since the available options, as well as the names of the architectures themselves, seem dependent on the host OS.

On Linux, for example, I would hope to see options named x86_64 and aarch64.

The reason I would like to have the host CPU architecture called out is that it seems to affect the supported configurations.

Specifically this one:

  • Stable (2.3.1)
  • Linux
  • Pip
  • Python
  • CUDA 12.1

On x86_64, I can run the chosen command (pip3 install torch torchvision torchaudio) and see that my installed copy of torch really does support CUDA. This is confirmed by looking at the CUDA used to build PyTorch line emitted by python3 -c 'from torch.utils import collect_env; print(collect_env.get_pretty_env_info())' after installing.

+ uname -m
x86_64

+ pip3 install torch torchvision torchaudio
Collecting torch
  Downloading torch-2.4.0-cp310-cp310-manylinux1_x86_64.whl (797.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 797.2/797.2 MB 3.4 MB/s eta 0:00:00
Collecting torchvision
  Downloading torchvision-0.19.0-cp310-cp310-manylinux1_x86_64.whl (7.0 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.0/7.0 MB 5.8 MB/s eta 0:00:00
Collecting torchaudio
  Downloading torchaudio-2.4.0-cp310-cp310-manylinux1_x86_64.whl (3.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.4/3.4 MB 10.3 MB/s eta 0:00:00
Collecting nvidia-cusolver-cu12==11.4.5.107
  Downloading nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 124.2/124.2 MB 17.1 MB/s eta 0:00:00
Collecting nvidia-cusparse-cu12==12.1.0.106
  Downloading nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 196.0/196.0 MB 7.5 MB/s eta 0:00:00
Collecting sympy
  Downloading sympy-1.13.1-py3-none-any.whl (6.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.2/6.2 MB 25.3 MB/s eta 0:00:00
Collecting filelock
  Downloading filelock-3.15.4-py3-none-any.whl (16 kB)
Collecting networkx
  Downloading networkx-3.3-py3-none-any.whl (1.7 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 27.4 MB/s eta 0:00:00
Collecting nvidia-cuda-nvrtc-cu12==12.1.105
  Downloading nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 22.1 MB/s eta 0:00:00
Collecting fsspec
  Downloading fsspec-2024.6.1-py3-none-any.whl (177 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 177.6/177.6 KB 18.2 MB/s eta 0:00:00
Collecting nvidia-curand-cu12==10.3.2.106
  Downloading nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.5/56.5 MB 17.1 MB/s eta 0:00:00
Collecting triton==3.0.0
  Downloading triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (209.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 209.4/209.4 MB 6.9 MB/s eta 0:00:00
Collecting jinja2
  Downloading jinja2-3.1.4-py3-none-any.whl (133 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 133.3/133.3 KB 12.3 MB/s eta 0:00:00
Collecting nvidia-nvtx-cu12==12.1.105
  Downloading nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 99.1/99.1 KB 11.3 MB/s eta 0:00:00
Collecting nvidia-cublas-cu12==12.1.3.1
  Downloading nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 410.6/410.6 MB 5.3 MB/s eta 0:00:00
Collecting nvidia-cufft-cu12==11.0.2.54
  Downloading nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 121.6/121.6 MB 18.2 MB/s eta 0:00:00
Collecting nvidia-nccl-cu12==2.20.5
  Downloading nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 176.2/176.2 MB 15.8 MB/s eta 0:00:00
Collecting nvidia-cuda-runtime-cu12==12.1.105
  Downloading nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 823.6/823.6 KB 22.6 MB/s eta 0:00:00
Collecting typing-extensions>=4.8.0
  Downloading typing_extensions-4.12.2-py3-none-any.whl (37 kB)
Collecting nvidia-cudnn-cu12==9.1.0.70
  Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 664.8/664.8 MB 7.0 MB/s eta 0:00:00
Collecting nvidia-cuda-cupti-cu12==12.1.105
  Downloading nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.1/14.1 MB 17.2 MB/s eta 0:00:00
Collecting nvidia-nvjitlink-cu12
  Downloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl (21.3 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.3/21.3 MB 16.9 MB/s eta 0:00:00
Collecting pillow!=8.3.*,>=5.3.0
  Downloading pillow-10.4.0-cp310-cp310-manylinux_2_28_x86_64.whl (4.5 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4.5/4.5 MB 18.3 MB/s eta 0:00:00
Collecting numpy
  Downloading numpy-2.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (19.5 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.5/19.5 MB 17.6 MB/s eta 0:00:00
Collecting MarkupSafe>=2.0
  Downloading MarkupSafe-2.1.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25 kB)
Collecting mpmath<1.4,>=1.1.0
  Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 19.8 MB/s eta 0:00:00
Installing collected packages: mpmath, typing-extensions, sympy, pillow, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, MarkupSafe, fsspec, filelock, triton, nvidia-cusparse-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch, torchvision, torchaudio
Successfully installed MarkupSafe-2.1.5 filelock-3.15.4 fsspec-2024.6.1 jinja2-3.1.4 mpmath-1.3.0 networkx-3.3 numpy-2.0.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105 pillow-10.4.0 sympy-1.13.1 torch-2.4.0 torchaudio-2.4.0 torchvision-0.19.0 triton-3.0.0 typing-extensions-4.12.2

+ python3 -c 'from torch.utils import collect_env; print(collect_env.get_pretty_env_info())'
PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.10.12 (main, Mar 22 2024, 16:50:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.9.3-76060903-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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
Address sizes:                        39 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               8
On-line CPU(s) list:                  0-7
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Core(TM) i7-10510U CPU @ 1.80GHz
CPU family:                           6
Model:                                142
Thread(s) per core:                   2
Core(s) per socket:                   4
Socket(s):                            1
Stepping:                             12
CPU max MHz:                          4900.0000
CPU min MHz:                          400.0000
BogoMIPS:                             4599.93
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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi md_clear flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            128 KiB (4 instances)
L1i cache:                            128 KiB (4 instances)
L2 cache:                             1 MiB (4 instances)
L3 cache:                             8 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-7
Vulnerability Gather data sampling:   Mitigation; Microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
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:                  Mitigation; Microcode
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==2.0.1
[pip3] torch==2.4.0
[pip3] torchaudio==2.4.0
[pip3] torchvision==0.19.0
[pip3] triton==3.0.0
[conda] Could not collect

If we switch to an aarch64 machine such as an AWS EC2 g5g.xlarge (or my docker runtime emulating aarch64 via qemu), we see CUDA support vanish (CUDA used to build PyTorch: None):

+ uname -m
aarch64

+ pip3 install torch torchvision torchaudio
Collecting torch
  Downloading torch-2.4.0-cp310-cp310-manylinux2014_aarch64.whl (89.8 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.8/89.8 MB 9.0 MB/s eta 0:00:00
Collecting torchvision
  Downloading torchvision-0.19.0-cp310-cp310-manylinux2014_aarch64.whl (14.1 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.1/14.1 MB 14.8 MB/s eta 0:00:00
Collecting torchaudio
  Downloading torchaudio-2.4.0-cp310-cp310-manylinux2014_aarch64.whl (1.7 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 13.5 MB/s eta 0:00:00
Collecting filelock
  Downloading filelock-3.15.4-py3-none-any.whl (16 kB)
Collecting fsspec
  Downloading fsspec-2024.6.1-py3-none-any.whl (177 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 177.6/177.6 KB 6.2 MB/s eta 0:00:00
Collecting networkx
  Downloading networkx-3.3-py3-none-any.whl (1.7 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 13.3 MB/s eta 0:00:00
Collecting sympy
  Downloading sympy-1.13.1-py3-none-any.whl (6.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.2/6.2 MB 8.1 MB/s eta 0:00:00
Collecting jinja2
  Downloading jinja2-3.1.4-py3-none-any.whl (133 kB)
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Collecting typing-extensions>=4.8.0
  Downloading typing_extensions-4.12.2-py3-none-any.whl (37 kB)
Collecting pillow!=8.3.*,>=5.3.0
  Downloading pillow-10.4.0-cp310-cp310-manylinux_2_28_aarch64.whl (4.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4.4/4.4 MB 12.5 MB/s eta 0:00:00
Collecting numpy
  Downloading numpy-2.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (13.9 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.9/13.9 MB 12.7 MB/s eta 0:00:00
Collecting MarkupSafe>=2.0
  Downloading MarkupSafe-2.1.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (26 kB)
Collecting mpmath<1.4,>=1.1.0
  Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 8.8 MB/s eta 0:00:00
Installing collected packages: mpmath, typing-extensions, sympy, pillow, numpy, networkx, MarkupSafe, fsspec, filelock, jinja2, torch, torchvision, torchaudio
Successfully installed MarkupSafe-2.1.5 filelock-3.15.4 fsspec-2024.6.1 jinja2-3.1.4 mpmath-1.3.0 networkx-3.3 numpy-2.0.1 pillow-10.4.0 sympy-1.13.1 torch-2.4.0 torchaudio-2.4.0 torchvision-0.19.0 typing-extensions-4.12.2

+ python3 -c 'from torch.utils import collect_env; print(collect_env.get_pretty_env_info())'
PyTorch version: 2.4.0
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (aarch64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.10.12 (main, Mar 22 2024, 16:50:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.9.3-76060903-generic-aarch64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         aarch64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        39 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               8
On-line CPU(s) list:                  0-7
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Core(TM) i7-10510U CPU @ 1.80GHz
CPU family:                           6
Model:                                142
Thread(s) per core:                   2
Core(s) per cluster:                  4
Socket(s):                            -
Cluster(s):                           1
Stepping:                             12
CPU max MHz:                          4900.0000
CPU min MHz:                          400.0000
BogoMIPS:                             4599.93
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 art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi md_clear flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            128 KiB (4 instances)
L1i cache:                            128 KiB (4 instances)
L2 cache:                             1 MiB (4 instances)
L3 cache:                             8 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-7
Vulnerability Gather data sampling:   Mitigation; Microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
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:                  Mitigation; Microcode
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==2.0.1
[pip3] torch==2.4.0
[pip3] torchaudio==2.4.0
[pip3] torchvision==0.19.0
[conda] Could not collect

Assuming CUDA is not yet supported on aarch64 with this combination, the matrix could have let us know immediately by e.g. switching to compute platform CPU or crossing the other options out.
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