parent_child_dict[sample.parent_seq_id].append(sample) KeyError: 4

[Stosan]

Your current environment

PyTorch version: 2.1.2+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux 11 (bullseye) (x86_64) GCC version: (Debian 10.2.1-6) 10.2.1 20210110 Clang version: Could not collect CMake version: version 3.18.4 Libc version: glibc-2.31

Python version: 3.10.13 | packaged by conda-forge | (main, Dec 23 2023, 15:36:39) [GCC 12.3.0] (64-bit runtime) Python platform: Linux-5.10.0-28-cloud-amd64-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 12.3.107 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA L4 Nvidia driver version: 545.23.08 cuDNN version: Could not collect 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 Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 16 On-line CPU(s) list: 0-15 Thread(s) per core: 2 Core(s) per socket: 8 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 85 Model name: Intel(R) Xeon(R) CPU @ 2.20GHz Stepping: 7 CPU MHz: 2200.232 BogoMIPS: 4400.46 Hypervisor vendor: KVM Virtualization type: full L1d cache: 256 KiB L1i cache: 256 KiB L2 cache: 8 MiB L3 cache: 38.5 MiB NUMA node0 CPU(s): 0-15 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Mitigation; Clear CPU buffers; SMT Host state unknown Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown Vulnerability Retbleed: Mitigation; Enhanced IBRS Vulnerability Spec rstack overflow: 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: Mitigation; Clear CPU buffers; SMT Host state unknown Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat avx512_vnni md_clear arch_capabilities

Versions of relevant libraries: [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.26.1 [pip3] onnx==1.15.0 [pip3] onnxruntime==1.15.1 [pip3] torch==2.1.2 [pip3] torchvision==0.16.2 [pip3] triton==2.1.0 [conda] numpy 1.26.4 pypi_0 pypi [conda] pytorch-triton 3.0.0+a9bc1a3647 pypi_0 pypi [conda] torch 2.1.1+cu121 pypi_0 pypi [conda] torchaudio 2.1.1+cu121 pypi_0 pypi [conda] torchvision 0.16.1+cu121 pypi_0 pypi [conda] triton 2.1.0 pypi_0 pypiROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.3.3 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X 0-15 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

Hi everyone. I'm trying to use vLLM on a L4, but I'm facing some problems during multiple requests

I'm trying to run Mistral-7B-Instruct-v0.2 here's my code.

` from langchain_community.llms import VLLM

llm = VLLM(model="mistralai/Mistral-7B-Instruct-v0.2", tokenizer="mistralai/Mistral-7B-Instruct-v0.2", trust_remote_code=True, # mandatory for hf models top_k=10, top_p=0.95, temperature=0.2, gpu_memory_utilization=0.9, max_new_tokens=15000, disable_log_stats=True, max_num_seqs=2, enforce_eager=True, vllm_kwargs={"max_model_len":24000}, tensor_parallel_size=torch.cuda.device_count() ) ` It works great until I send multiple concurrent request and I get:

/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 594, in _process_sequence_group_outputs parent_child_dict[sample.parent_seq_id].append(sample) KeyError: 11

[tim-aftm]

+1

[RodolpheCalvet]

+1

[DarkLight1337]

This seems to be the same issue as #1200