[Bug]: Guided decoding is broken because tokenizers can't be pickled

Your current environment

The output of `python collect_env.py`

```text Collecting environment information... PyTorch version: 2.3.1+cpu Is debug build: False CUDA used to build PyTorch: Could not collect ROCM used to build PyTorch: N/A OS: Fedora release 39 (Thirty Nine) (x86_64) GCC version: (GCC) 13.3.1 20240522 (Red Hat 13.3.1-1) Clang version: 17.0.6 (Fedora 17.0.6-2.fc39) CMake version: version 3.29.6 Libc version: glibc-2.38 Python version: 3.11.8 (main, Mar 27 2024, 15:03:48) [GCC 13.2.1 20231205 (Red Hat 13.2.1-6)] (64-bit runtime) Python platform: Linux-6.7.11-200.fc39.x86_64-x86_64-with-glibc2.38 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce MX330 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 Address sizes: 39 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 8 On-line CPU(s) list: 0-7 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-10510U CPU @ 1.80GHz CPU family: 6 Model: 142 Thread(s) per core: 2 Core(s) per socket: 4 Socket(s): 1 Stepping: 12 CPU(s) scaling MHz: 69% CPU max MHz: 4900.0000 CPU min MHz: 400.0000 BogoMIPS: 4599.93 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 est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid 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 sgx bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 128 KiB (4 instances) L1i cache: 128 KiB (4 instances) L2 cache: 1 MiB (4 instances) L3 cache: 8 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-7 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; Enhanced IBRS 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 Vulnerability Srbds: Mitigation; Microcode Vulnerability Tsx async abort: Not affected Versions of relevant libraries: [pip3] intel_extension_for_pytorch==2.3.100 [pip3] mypy==1.11.1 [pip3] mypy-extensions==1.0.0 [pip3] mypy-protobuf==3.5.0 [pip3] numpy==1.26.4 [pip3] nvidia-nccl-cu12==2.20.5 [pip3] pyzmq==26.1.0 [pip3] torch==2.3.1+cpu [pip3] torchvision==0.18.1+cpu [pip3] transformers==4.43.4 [pip3] triton==2.3.0 [conda] Could not collect ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.5.4@1f26efbb3a5e6dad0b98421dd697167c42a50629 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X 0-7 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

If I run a small model like this python -m vllm.entrypoints.openai.api_server --model gpt2 and call it like this

curl http://localhost:8000/v1/completions   -H "Content-Type: application/json"   -d '{
    "model": "gpt2",
    "prompt": ["An example of a json document: ", "Another example of a json document: "],
    "max_tokens": 100,
    "temperature": 0,
    "guided_decoding_backend": "outlines",
    "response_format": {"type":"json_object"}
  }'

I get the following error in the server log:

Traceback (most recent call last):
  File "/home/mbayser/.pyenv/versions/3.11.8/lib/python3.11/multiprocessing/queues.py", line 244, in _feed
    obj = _ForkingPickler.dumps(obj)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/mbayser/.pyenv/versions/3.11.8/lib/python3.11/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
AttributeError: Can't pickle local object 'get_cached_tokenizer.<locals>.CachedTokenizer'

I've tried to disable frontend multiprocessing, but that only changes the place where the error happens:

Traceback (most recent call last):
  File "/home/mbayser/.pyenv/versions/3.11.8/lib/python3.11/multiprocessing/queues.py", line 244, in _feed
    obj = _ForkingPickler.dumps(obj)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/mbayser/.pyenv/versions/3.11.8/lib/python3.11/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
AttributeError: Can't pickle local object 'get_cached_tokenizer.<locals>.CachedTokenizer'

It seems that some of the refactorings to use multiprocessing have broken the guided decoding feature.

vllm-project / vllm

[Bug]: Guided decoding is broken because tokenizers can't be pickled #7557

Your current environment

🐛 Describe the bug