No executable after building vllm from source with CPU support

[parkesorgua]

Your current environment

PyTorch version: 2.3.1+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04 LTS (x86_64)
GCC version: (Ubuntu 13.2.0-23ubuntu4) 13.2.0
Clang version: Could not collect
CMake version: version 3.29.6
Libc version: glibc-2.39

Python version: 3.9.19 (main, May  6 2024, 19:43:03)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-36-generic-x86_64-with-glibc2.39
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:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               6
On-line CPU(s) list:                  0-5
Vendor ID:                            AuthenticAMD
Model name:                           AMD Ryzen 5 4500U with Radeon Graphics
CPU family:                           23
Model:                                96
Thread(s) per core:                   1
Core(s) per socket:                   6
Socket(s):                            1
Stepping:                             1
Frequency boost:                      enabled
CPU(s) scaling MHz:                   73%
CPU max MHz:                          2375.0000
CPU min MHz:                          1400.0000
BogoMIPS:                             4741.01
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca
Virtualization:                       AMD-V
L1d cache:                            192 KiB (6 instances)
L1i cache:                            192 KiB (6 instances)
L2 cache:                             3 MiB (6 instances)
L3 cache:                             8 MiB (2 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-5
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT disabled
Vulnerability Spec rstack overflow:   Mitigation; SMT disabled
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; Retpolines; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] torch==2.3.1+cpu
[pip3] transformers==4.43.0.dev0
[pip3] triton==2.3.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] torch                     2.3.1+cpu                pypi_0    pypi
[conda] transformers              4.43.0.dev0              pypi_0    pypi
[conda] triton                    2.3.0                    pypi_0    pypi
ROCM Version: 6.1.40093-bd86f1708
Neuron SDK Version: N/A
vLLM Version: 0.5.0.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect

How you are installing vllm

sudo apt-get update  -y
sudo apt-get install -y gcc-12 g++-12
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12

pip install --upgrade pip
pip install wheel packaging ninja "setuptools>=49.4.0" numpy
pip install -v -r requirements-cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu
VLLM_TARGET_DEVICE=cpu python setup.py install

Information about the Issue

I am trying to run small quantized model on my notebook. As I understood to run on CPU building from source required. I have followed instructions on https://docs.vllm.ai/en/latest/getting_started/cpu-installation.html. After running VLLM_TARGET_DEVICE=cpu python setup.py install no binary found in build folder only 3 other folders:

bdist.linux-x86_64
lib.linux-x86_64-cpython-39
temp.linux-x86_64-cpython-39

How to build vllm from source to get binary file?

Actual behaviour

3 folders, but no executable

Expected behavior

executable file in build folder

[parkesorgua]

Tried pip install -e . got an error No ROCm runtime is found, using ROCM_HOME='/opt/rocm-6.1.2, while rocminfo displays Runtime Version: 1.13

[parkesorgua]

Figured out my cpu supports Rocm. Hardcoded rocm in setup.py. Now observing another error Your installed Caffe2 version uses CUDA but I cannot find the CUDA

[lhtin]

Figured out my cpu supports Rocm. Hardcoded rocm in setup.py. Now observing another error Your installed Caffe2 version uses CUDA but I cannot find the CUDA

Encountered the same problem when run VLLM_TARGET_DEVICE=cpu pip install -e .. Do you have any new progress on this error?

      -- The CXX compiler identification is GNU 12.3.0
      -- Detecting CXX compiler ABI info
      -- Detecting CXX compiler ABI info - done
      -- Check for working CXX compiler: /usr/bin/c++ - skipped
      -- Detecting CXX compile features
      -- Detecting CXX compile features - done
      -- Build type: RelWithDebInfo
      -- Target device: cpu
      -- Target device: 123
      -- Found Python: /usr/bin/python3 (found version "3.10.12") found components: Interpreter Development.Module Development.SABIModule
      -- Found python matching: /usr/bin/python3.
      CUDA_TOOLKIT_ROOT_DIR not found or specified
      -- Could NOT find CUDA (missing: CUDA_TOOLKIT_ROOT_DIR CUDA_NVCC_EXECUTABLE CUDA_INCLUDE_DIRS CUDA_CUDART_LIBRARY)
      CMake Warning at /tmp/pip-build-env-mn104v5q/overlay/local/lib/python3.10/dist-packages/torch/share/cmake/Caffe2/public/cuda.cmake:31 (message):
        Caffe2: CUDA cannot be found.  Depending on whether you are building Caffe2
        or a Caffe2 dependent library, the next warning / error will give you more
        info.
      Call Stack (most recent call first):
        /tmp/pip-build-env-mn104v5q/overlay/local/lib/python3.10/dist-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:87 (include)
        /tmp/pip-build-env-mn104v5q/overlay/local/lib/python3.10/dist-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
        CMakeLists.txt:69 (find_package)

      CMake Error at /tmp/pip-build-env-mn104v5q/overlay/local/lib/python3.10/dist-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:91 (message):
        Your installed Caffe2 version uses CUDA but I cannot find the CUDA
        libraries.  Please set the proper CUDA prefixes and / or install CUDA.
      Call Stack (most recent call first):
        /tmp/pip-build-env-mn104v5q/overlay/local/lib/python3.10/dist-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
        CMakeLists.txt:69 (find_package)

[parkesorgua]

It is not patched yet. Try docker image.

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[cdoern]

still hitting this.