Collecting environment information... ============================== System Info ============================== OS : CentOS Stream 9 (x86_64) GCC version : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-11) Clang version : Could not collect CMake version : version 4.1.0 Libc version : glibc-2.34 ============================== PyTorch Info ============================== PyTorch version : 2.8.0+cu129 Is debug build : False CUDA used to build PyTorch : 12.9 ROCM used to build PyTorch : N/A ============================== Python Environment ============================== Python version : 3.12.11 (main, Aug 14 2025, 00:00:00) [GCC 11.5.0 20240719 (Red Hat 11.5.0-11)] (64-bit runtime) Python platform : Linux-6.4.3-0_fbk15_hardened_2630_gf27365f948db-x86_64-with-glibc2.34 ============================== CUDA / GPU Info ============================== Is CUDA available : True CUDA runtime version : 12.9.86 CUDA_MODULE_LOADING set to : LAZY GPU models and configuration : GPU 0: NVIDIA H100 GPU 1: NVIDIA H100 GPU 2: NVIDIA H100 GPU 3: NVIDIA H100 GPU 4: NVIDIA H100 GPU 5: NVIDIA H100 GPU 6: NVIDIA H100 GPU 7: NVIDIA H100 Nvidia driver version : 550.90.07 cuDNN version : Probably one of the following: /usr/lib64/libcudnn.so.9.12.0 /usr/lib64/libcudnn_adv.so.9.12.0 /usr/lib64/libcudnn_cnn.so.9.12.0 /usr/lib64/libcudnn_engines_precompiled.so.9.12.0 /usr/lib64/libcudnn_engines_runtime_compiled.so.9.12.0 /usr/lib64/libcudnn_graph.so.9.12.0 /usr/lib64/libcudnn_heuristic.so.9.12.0 /usr/lib64/libcudnn_ops.so.9.12.0 HIP runtime version : N/A MIOpen runtime version : N/A Is XNNPACK available : True ============================== CPU Info ============================== Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 368 On-line CPU(s) list: 0-367 Vendor ID: AuthenticAMD Model name: AMD EPYC 9654 96-Core Processor CPU family: 25 Model: 17 Thread(s) per core: 1 Core(s) per socket: 368 Socket(s): 1 Stepping: 1 BogoMIPS: 4792.79 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 rep_good nopl cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx512_bf16 clzero xsaveerptr wbnoinvd arat npt lbrv nrip_save tsc_scale vmcb_clean flushbyasid pausefilter pfthreshold v_vmsave_vmload vgif vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm flush_l1d arch_capabilities Virtualization: AMD-V Hypervisor vendor: KVM Virtualization type: full L1d cache: 23 MiB (368 instances) L1i cache: 23 MiB (368 instances) L2 cache: 184 MiB (368 instances) L3 cache: 16 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-367 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 Retbleed: Not affected Vulnerability Spec store bypass: Vulnerable Vulnerability Spectre v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers Vulnerability Spectre v2: Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected ============================== Versions of relevant libraries ============================== [pip3] numpy==2.2.6 [pip3] nvidia-cublas-cu12==12.9.1.4 [pip3] nvidia-cuda-cupti-cu12==12.9.79 [pip3] nvidia-cuda-nvrtc-cu12==12.9.86 [pip3] nvidia-cuda-runtime-cu12==12.9.79 [pip3] nvidia-cudnn-cu12==9.10.2.21 [pip3] nvidia-cufft-cu12==11.4.1.4 [pip3] nvidia-cufile-cu12==1.14.1.1 [pip3] nvidia-curand-cu12==10.3.10.19 [pip3] nvidia-cusolver-cu12==11.7.5.82 [pip3] nvidia-cusparse-cu12==12.5.10.65 [pip3] nvidia-cusparselt-cu12==0.7.1 [pip3] nvidia-nccl-cu12==2.27.3 [pip3] nvidia-nvjitlink-cu12==12.9.86 [pip3] nvidia-nvtx-cu12==12.9.79 [pip3] pyzmq==27.1.0 [pip3] torch==2.8.0+cu129 [pip3] torchaudio==2.8.0+cu129 [pip3] torchvision==0.23.0+cu129 [pip3] transformers==4.56.2 [pip3] triton==3.4.0 [conda] Could not collect ============================== vLLM Info ============================== ROCM Version : Could not collect vLLM Version : 0.11.0rc2.dev39+gb1ded114b (git sha: b1ded114b) vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 0-367 0 N/A GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 0-367 0 N/A GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 0-367 0 N/A GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 0-367 0 N/A GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 0-367 0 N/A GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 0-367 0 N/A GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 0-367 0 N/A GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X 0-367 0 N/A Legend: X = Self SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI) NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU) PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge) PIX = Connection traversing at most a single PCIe bridge NV# = Connection traversing a bonded set of # NVLinks ============================== Environment Variables ============================== CUDA_CACHE_PATH=/data/users/myuan/.nv/ComputeCache CUDA_INCLUDE_DIRS=/usr/local/cuda-12.9/include PYTORCH_SRC=/home/myuan/src/pytorch CUDA_NVCC_EXECUTABLE=/home/myuan/ccache/cuda/nvcc LD_LIBRARY_PATH=/usr/local/cuda-12.9/lib64: CUDA_CUDART_LIBRARY=/usr/local/cuda-12.9/lib64/libcudart.so CUDA_HOME=/usr/local/cuda-12.9 CUDA_HOME=/usr/local/cuda-12.9 PYTORCH_NVML_BASED_CUDA_CHECK=1 TORCHINDUCTOR_COMPILE_THREADS=1 CUDA_MODULE_LOADING=LAZY