[Bug]: ImportError related to compressed tensors module #7516
Description
Your current environment
The output of `python collect_env.py`
Collecting environment information...
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: version 3.29.2
Libc version: glibc-2.35
Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.10.134-007.ali5000.al8.x86_64-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB
Nvidia driver version: 535.129.03
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.1.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.1.0
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: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 128
On-line CPU(s) list: 0-127
Vendor ID: GenuineIntel
BIOS Vendor ID: Intel(R) Corporation
Model name: Intel(R) Xeon(R) Platinum 8369B CPU @ 2.90GHz
BIOS Model name: Intel(R) Xeon(R) Platinum 8369B CPU @ 2.90GHz
CPU family: 6
Model: 106
Thread(s) per core: 2
Core(s) per socket: 32
Socket(s): 2
Stepping: 6
CPU max MHz: 3500.0000
CPU min MHz: 800.0000
BogoMIPS: 5800.00
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 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 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 3 MiB (64 instances)
L1i cache: 2 MiB (64 instances)
L2 cache: 80 MiB (64 instances)
L3 cache: 96 MiB (2 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-127
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed: 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; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==1.24.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] onnx==1.16.0
[pip3] optree==0.11.0
[pip3] pytorch-quantization==2.1.2
[pip3] pytorch-triton==3.0.0+989adb9a2
[pip3] pyzmq==26.0.3
[pip3] torch==2.4.0
[pip3] torch-tensorrt==2.4.0a0
[pip3] torchvision==0.19.0
[pip3] transformers==4.44.0
[pip3] triton==3.0.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: N/A
vLLM Build Flags:
CUDA Archs: 5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV12 NV12 NV12 NV12 NV12 NV12 NV12 0-127 0 N/A
GPU1 NV12 X NV12 NV12 NV12 NV12 NV12 NV12 0-127 0 N/A
GPU2 NV12 NV12 X NV12 NV12 NV12 NV12 NV12 0-127 0 N/A
GPU3 NV12 NV12 NV12 X NV12 NV12 NV12 NV12 0-127 0 N/A
GPU4 NV12 NV12 NV12 NV12 X NV12 NV12 NV12 0-127 0 N/A
GPU5 NV12 NV12 NV12 NV12 NV12 X NV12 NV12 0-127 0 N/A
GPU6 NV12 NV12 NV12 NV12 NV12 NV12 X NV12 0-127 0 N/A
GPU7 NV12 NV12 NV12 NV12 NV12 NV12 NV12 X 0-127 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
🐛 Describe the bug
I'm building vllm from source with container nvcr.io/nvidia/pytorch:24.05-py3. After pip install -e ., I'm trying import vllm and I got
The error
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/host_home/vllm-fork/vllm/__init__.py", line 3, in <module>
from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
File "/host_home/vllm-fork/vllm/engine/arg_utils.py", line 7, in <module>
from vllm.config import (CacheConfig, DecodingConfig, DeviceConfig,
File "/host_home/vllm-fork/vllm/config.py", line 11, in <module>
from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
File "/host_home/vllm-fork/vllm/model_executor/layers/quantization/__init__.py", line 10, in <module>
from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors import ( # noqa: E501
File "/host_home/vllm-fork/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors.py", line 4, in <module>
from compressed_tensors.config import CompressionFormat
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/__init__.py", line 18, in <module>
from .compressors import *
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/compressors/__init__.py", line 17, in <module>
from .base import Compressor
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/compressors/base.py", line 18, in <module>
from compressed_tensors.quantization import QuantizationConfig
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/quantization/__init__.py", line 21, in <module>
from .lifecycle import *
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/quantization/lifecycle/__init__.py", line 21, in <module>
from .initialize import *
File "/usr/local/lib/python3.10/dist-packages/compressed_tensors/quantization/lifecycle/initialize.py", line 20, in <module>
from accelerate.hooks import add_hook_to_module, remove_hook_from_module
File "/usr/local/lib/python3.10/dist-packages/accelerate/__init__.py", line 16, in <module>
from .accelerator import Accelerator
File "/usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py", line 36, in <module>
from .checkpointing import load_accelerator_state, load_custom_state, save_accelerator_state, save_custom_state
File "/usr/local/lib/python3.10/dist-packages/accelerate/checkpointing.py", line 24, in <module>
from .utils import (
File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/__init__.py", line 190, in <module>
from .bnb import has_4bit_bnb_layers, load_and_quantize_model
File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/bnb.py", line 29, in <module>
from ..big_modeling import dispatch_model, init_empty_weights
File "/usr/local/lib/python3.10/dist-packages/accelerate/big_modeling.py", line 24, in <module>
from .hooks import (
File "/usr/local/lib/python3.10/dist-packages/accelerate/hooks.py", line 30, in <module>
from .utils.other import recursive_getattr
File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/other.py", line 36, in <module>
from .transformer_engine import convert_model
File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/transformer_engine.py", line 21, in <module>
import transformer_engine.pytorch as te
File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/__init__.py", line 6, in <module>
from .module import LayerNormLinear
File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/__init__.py", line 6, in <module>
from .layernorm_linear import LayerNormLinear
File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/layernorm_linear.py", line 13, in <module>
from .. import cpp_extensions as tex
File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/cpp_extensions/__init__.py", line 6, in <module>
from transformer_engine_extensions import *
ImportError: /usr/local/lib/python3.10/dist-packages/transformer_engine_extensions.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN5torch3jit17parseSchemaOrNameERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE
This seems to be introduced by #7277.
There is a workaround chenfei-wu/TaskMatrix#116 (comment), but I'm not sure if transformer-engine is a dependency.