[Bug]: Speculative decoding interferes with CPU-only execution

[NickLucche]

Your current environment

The output of `python collect_env.py`

Collecting environment information...
INFO 09-19 11:58:02 importing.py:10] Triton not installed; certain GPU-related functions will not be available.
PyTorch version: 2.4.0+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Fedora Linux 40 (Workstation Edition) (x86_64)
GCC version: (GCC) 14.2.1 20240801 (Red Hat 14.2.1-1)
Clang version: 18.1.8 (Fedora 18.1.8-1.fc40)
CMake version: version 3.28.2
Libc version: glibc-2.39

Python version: 3.12.6 (main, Sep  9 2024, 00:00:00) [GCC 14.2.1 20240801 (Red Hat 14.2.1-1)] (64-bit runtime)
Python platform: Linux-6.10.9-200.fc40.x86_64-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:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               16
On-line CPU(s) list:                  0-15
Vendor ID:                            GenuineIntel
Model name:                           12th Gen Intel(R) Core(TM) i7-1270P
CPU family:                           6
Model:                                154
Thread(s) per core:                   2
Core(s) per socket:                   12
Socket(s):                            1
Stepping:                             3
CPU(s) scaling MHz:                   67%
CPU max MHz:                          4800.0000
CPU min MHz:                          400.0000
BogoMIPS:                             4992.00
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 tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr ibt flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            448 KiB (12 instances)
L1i cache:                            640 KiB (12 instances)
L2 cache:                             9 MiB (6 instances)
L3 cache:                             18 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-15
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: Mitigation; Clear Register File
Vulnerability Retbleed:               Not affected
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 BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] pyzmq==26.2.0
[pip3] torch==2.4.0+cpu
[pip3] torchvision==0.19.0+cpu
[pip3] transformers==4.44.2
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.1.post2@1b6de8352b878348974b3f117cbb68ed18daa609
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect

Model Input Dumps

No response

🐛 Describe the bug

As far as I know, speculative decoding isn't (rightfully) implemented on CPU, as the SpecDecodeWorker in only instantiated in GPUExecutor.
Nevertheless, when enabling spec decoding on a cpu build, parameter n appears to be ignored and only 1 completion is returned.

Here's a simple snippet to quickly reproduce the issue:

import argparse
from typing import List, Tuple

from vllm import EngineArgs, LLMEngine, RequestOutput, SamplingParams
from vllm.utils import FlexibleArgumentParser


def create_test_prompts() -> List[Tuple[str, SamplingParams]]:
    """Create a list of test prompts with their sampling parameters."""
    return [
        ("A robot may not injure a human being",
         SamplingParams(temperature=0.1, n=2, top_p=0.8, seed=42)),
        ("To be or not to be,",
         SamplingParams(temperature=0.1, n=2, top_p=0.8, seed=42)),
    ]


def process_requests(engine: LLMEngine,
                     test_prompts: List[Tuple[str, SamplingParams]]):
    """Continuously process a list of prompts and handle the outputs."""
    request_id = 0

    while test_prompts or engine.has_unfinished_requests():
        if test_prompts:
            prompt, sampling_params = test_prompts.pop(0)
            engine.add_request(str(request_id), prompt, sampling_params)
            request_id += 1

        request_outputs: List[RequestOutput] = engine.step()

        for request_output in request_outputs:
            if request_output.finished:
                print(request_output.request_id, request_output.prompt, [o.text for o in request_output.outputs],'\n\n\n\n','='*30)


def initialize_engine(args: argparse.Namespace) -> LLMEngine:
    """Initialize the LLMEngine from the command line arguments."""
    engine_args = EngineArgs.from_cli_args(args)
    return LLMEngine.from_engine_args(engine_args)


def main(args: argparse.Namespace):
    """Main function that sets up and runs the prompt processing."""
    engine = initialize_engine(args)
    test_prompts = create_test_prompts()
    process_requests(engine, test_prompts)


if __name__ == '__main__':
    parser = FlexibleArgumentParser(
        description='Demo on using the LLMEngine class directly')
    parser = EngineArgs.add_cli_args(parser)
    args = parser.parse_args()
    main(args)

Run with

# regular expected behavior
python bug.py  --model TinyLlama/TinyLlama-1.1B-Chat-v0.6 \
   --seed 44 --use-v2-block-manager 
 
# n ignored
python bug.py  --model TinyLlama/TinyLlama-1.1B-Chat-v0.6 \
   --seed 44 --use-v2-block-manager --speculative_model TinyLlama/TinyLlama-1.1B-Chat-v0.6 \
   --num_speculative_tokens 5

PS: I also think we should log something when spec decoding is enabled on CPU to point out it's ignored, just like CUDA graphs and a ton of other features.

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