[Bug]: bnb quant load error

[theobjectivedad]

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PyTorch version: 2.3.0+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 3.29.3
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-6.5.0-35-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000
GPU 2: NVIDIA RTX A6000
GPU 3: NVIDIA RTX A6000

Nvidia driver version: 535.171.04
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:                      48 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             64
On-line CPU(s) list:                0-63
Vendor ID:                          AuthenticAMD
Model name:                         AMD Ryzen Threadripper PRO 5975WX 32-Cores
CPU family:                         25
Model:                              8
Thread(s) per core:                 2
Core(s) per socket:                 32
Socket(s):                          1
Stepping:                           2
Frequency boost:                    enabled
CPU max MHz:                        7006.6401
CPU min MHz:                        1800.0000
BogoMIPS:                           7186.60
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Virtualization:                     AMD-V
L1d cache:                          1 MiB (32 instances)
L1i cache:                          1 MiB (32 instances)
L2 cache:                           16 MiB (32 instances)
L3 cache:                           128 MiB (4 instances)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-63
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 rstack overflow: Vulnerable: Safe RET, no microcode
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; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.3.0
[pip3] triton==2.3.0
[conda] Could not collect ROCM Version: Could not collect
Aphrodite Version: 0.5.3
Aphrodite Build Flags:
CUDA Archs: 6.1 7.0 7.5 8.0 8.6 8.9 9.0+PTX; ROCm: Disabled

Additionally:

transformers==4.40.0 bitsandbytes==0.43.1

🐛 Describe the bug

When loading CommandR+ (bnb/4bit) with the following command:

docker run -it -d --name=eleanor-aphrodite-main --restart=unless-stopped --shm-size=15g --ulimit memlock=-1 --ipc=host --entrypoint=python3 --gpus="device=0,1,2,3" --publish=7800:8000 --volume=/mnt/archive/models:/models:ro --health-cmd=timeout 5 bash -c 'cat < /dev/null > /dev/tcp/localhost/8000' --health-start-period=240s --health-interval=15s --health-timeout=8s --health-retries=3 --env=RAY_DEDUP_LOGS=1 --env=APHRODITE_ENGINE_ITERATION_TIMEOUT_S=120 quay.io/theobjectivedad/aphrodite:latest -m aphrodite.endpoints.openai.api_server --model /models/c4ai-command-r-plus-4bit --served-model-name c4ai-command-r-plus-4bit --quantization bnb --context-shift --tensor-parallel-size 4 --gpu-memory-utilization 0.90 --kv-cache-dtype auto --load-format safetensors --tokenizer-mode auto --dtype auto --response-role gpt --port 8000 --host 0.0.0.0

I get this error:

INFO: Tailing logs for eleanor-aphrodite-main. Press CTRL+C to stop.
Traceback (most recent call last):
  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/app/aphrodite-engine/aphrodite/endpoints/openai/api_server.py", line 562, in <module>
    run_server(args)
  File "/app/aphrodite-engine/aphrodite/endpoints/openai/api_server.py", line 519, in run_server
    engine = AsyncAphrodite.from_engine_args(engine_args)
  File "/app/aphrodite-engine/aphrodite/engine/async_aphrodite.py", line 340, in from_engine_args
    engine_config = engine_args.create_engine_config()
  File "/app/aphrodite-engine/aphrodite/engine/args_tools.py", line 539, in create_engine_config
    model_config = ModelConfig(
  File "/app/aphrodite-engine/aphrodite/common/config.py", line 145, in __init__
    self._verify_quantization()
  File "/app/aphrodite-engine/aphrodite/common/config.py", line 215, in _verify_quantization
    raise ValueError(
ValueError: Quantization method specified in the model config (bitsandbytes) does not match the quantization method specified in the `quantization` argument (bnb).

The image was build from main on 6/11/2024.

As indicated in the error message, omitting --quantization bnb doesn't seem to have any effect, I the error is from reading the model's config.json file:

...
  "quantization_config": {
    "_load_in_4bit": true,
    "_load_in_8bit": false,
    "bnb_4bit_compute_dtype": "bfloat16",
    "bnb_4bit_quant_storage": "uint8",
    "bnb_4bit_quant_type": "fp4",
    "bnb_4bit_use_double_quant": true,
    "llm_int8_enable_fp32_cpu_offload": false,
    "llm_int8_has_fp16_weight": false,
    "llm_int8_skip_modules": null,
    "llm_int8_threshold": 6.0,
    "load_in_4bit": true,
    "load_in_8bit": false,
    "quant_method": "bitsandbytes"
  },
...

Some notes I took looking into this a little deeper...

• The actual error is being triggered here, and is basically assuming quantization_config.quant_method in the model's config.json would be bnb ... I'm sure this changed at some point in transformers
• In _verify_quantization() , we may want to keep bnb and add bitsandbytes to maintain compatibility and reduce confusion.
• Additionally, there are some default values in the same method that get set when loading a model in 4/8 bit mode via bnb
• The transformers config doc is here, I'm still searching to see exactly when this change was made (not that it matters much)

Lastly, I'm hesitant to fly solo and just submit a PR on this one since the current bnb quant config is pretty tightly integrated into aphrodite/quantization/bitsandbytes.py, not sure on the best way to proceed.