[BUG: mistralai/mamba-codestral-7B-v0.1 AttributeError: 'Mamba2' object has no attribute 'dconv'

[s-natsubori]

Python -VV

Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]

Pip Freeze

absl-py==2.0.0
accelerate==0.28.0
aiohttp @ file:///rapids/aiohttp-3.8.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=df72ac063b97837a80d80dec8d54c241af059cc9bb42c4de68bd5b61ceb37caa
aiorwlock==1.3.0
aiosignal @ file:///rapids/aiosignal-1.3.1-py3-none-any.whl#sha256=f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17
annotated-types==0.5.0
antlr4-python3-runtime==4.9.3
anyio==4.4.0
apex @ file:///opt/pytorch/apex
argilla==1.24.0
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
asttokens==2.4.0
astunparse==1.6.3
async-timeout @ file:///rapids/async_timeout-4.0.3-py3-none-any.whl#sha256=7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028
asyncio==3.4.3
attrs==23.1.0
audioread==3.0.1
av==12.2.0
backcall==0.2.0
backoff==2.2.1
beautifulsoup4==4.12.2
bleach==6.0.0
blis==0.7.11
cachetools==5.3.1
catalogue==2.0.10
causal-conv1d==1.4.0
certifi==2023.7.22
cffi==1.16.0
charset-normalizer @ file:///rapids/charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad
click @ file:///rapids/click-8.1.6-py3-none-any.whl#sha256=fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5
cloudpathlib==0.15.1
cloudpickle @ file:///rapids/cloudpickle-2.2.1-py3-none-any.whl#sha256=61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f
cmake==3.27.6
coloredlogs==15.0.1
comm==0.1.4
compel==2.0.2
confection==0.1.3
contourpy==1.1.1
controlnet_aux==0.0.7
cssselect==1.2.0
ctranslate2==4.3.1
cubinlinker @ file:///rapids/cubinlinker-0.3.0%2B2.gce0680b-cp310-cp310-linux_x86_64.whl#sha256=8cff93be2d63d7db8f1d15fc72cf813abe3d8fd31c35be439e3fb6b7b4c89f76
cuda-python @ file:///rapids/cuda_python-12.2.0rc5%2B5.g84845d1-cp310-cp310-linux_x86_64.whl#sha256=19bb8c6dd62e976182ff183aab18d2c9f0a698add93a1037f2cbaa5d0f739d9d
cudf @ file:///rapids/cudf-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=12228d0949a6be3a7a383262f77c37372d48e02e57c4d0b8ed3763ced4d26ccb
cugraph @ file:///rapids/cugraph-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=209757e66f1ef51a5bace52774f9fc5575cdc6a00e11287ca8f0be78f57a9661
cugraph-dgl @ file:///rapids/cugraph_dgl-23.8.0-py3-none-any.whl#sha256=ef49cc4464b39aa686b97faa50186bd104cf965a7b7215c7ffb7b94011b6bcea
cugraph-service-client @ file:///rapids/cugraph_service_client-23.8.0-py3-none-any.whl#sha256=54d3f0367285be37ed4166483e4402e71e6a4747fb55e5a32a6ca9abfe264cb5
cugraph-service-server @ file:///rapids/cugraph_service_server-23.8.0-py3-none-any.whl#sha256=1fd5d70166ff9023c2b451f63e1a4a25c0e55e018811fc1549f52dffb7a422f6
cuml @ file:///rapids/cuml-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=f9209e5d1e2c765a4bc0b2955e4bc29016b9c4186b7e0512553f3fff879bf697
cupy-cuda12x @ file:///rapids/cupy_cuda12x-12.1.0-cp310-cp310-linux_x86_64.whl#sha256=840d1f4560436be5aaa9b6071d4947a391ab8c7b4810f035fc7815d43c29ed6d
cycler==0.12.1
cymem==2.0.8
Cython==3.0.3
dask @ file:///rapids/dask-2023.7.1-py3-none-any.whl#sha256=8ca3969805dd1cceee66f1138f103fba6fbaf22ba488f15b2382b4579ee39f02
dask-cuda @ file:///rapids/dask_cuda-23.8.0-py3-none-any.whl#sha256=68d2bef0df1307a28a0306e3501d63e6d19994d8bbe5e5dccd8b0967bcca8d30
dask-cudf @ file:///rapids/dask_cudf-23.8.0-py3-none-any.whl#sha256=8783c9089041462b8a4418d8645db2a7b2bc32c4c4b1800512f387d466ee1f16
dataclasses-json==0.6.7
datasets==2.19.2
debugpy==1.8.0
decorator==5.1.1
defusedxml==0.7.1
Deprecated==1.2.14
diffusers==0.29.0
dill==0.3.8
diskcache==5.6.3
distributed @ file:///rapids/distributed-2023.7.1-py3-none-any.whl#sha256=1237f8ae11baa9f80070329a33f9d5af32da5c272a98bab088c9b0578c2d816e
distro==1.9.0
dm-tree==0.1.8
docstring_parser==0.16
einops==0.7.0
exceptiongroup==1.1.3
execnet==2.0.2
executing==2.0.0
expecttest==0.1.3
fastapi==0.110.0
faster-whisper==1.0.2
fastjsonschema==2.18.1
fastrlock @ file:///rapids/fastrlock-0.8.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_24_x86_64.whl#sha256=d6c53abeae3f9a55b5c65824cec9df59159fa50e8fa800a5c6e8de42b2219c28
feedfinder2==0.0.4
feedparser==6.0.11
ffmpeg-python==0.2.0
filelock==3.12.4
fire==0.6.0
flash-attn @ https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.9.post1/flash_attn-2.5.9.post1+cu122torch2.3cxx11abiFALSE-cp310-cp310-linux_x86_64.whl#sha256=5022ba11d48bf74926da9c16260f4ea2b9bb7f4e29bdb4bd6e1383ad1c55d16f
flatbuffers==24.3.25
fonttools==4.43.1
frozenlist @ file:///rapids/frozenlist-1.4.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=6918d49b1f90821e93069682c06ffde41829c346c66b721e65a5c62b4bab0300
fsspec @ file:///rapids/fsspec-2023.6.0-py3-none-any.whl#sha256=1cbad1faef3e391fba6dc005ae9b5bdcbf43005c9167ce78c915549c352c869a
fugashi==1.3.1
future==1.0.0
gast==0.5.4
google-auth==2.23.2
google-auth-oauthlib==0.4.6
graphsurgeon @ file:///workspace/TensorRT-8.6.1.6/graphsurgeon/graphsurgeon-0.4.6-py2.py3-none-any.whl#sha256=0fbadaefbbe6e9920b9f814ae961c4a279be602812edf3ed7fb9cc6f8f4809fe
greenlet==3.0.3
grpcio==1.59.0
h11==0.14.0
httpcore==1.0.5
httptools==0.6.1
httpx==0.26.0
huggingface-hub==0.24.0
humanfriendly==10.0
hypothesis==5.35.1
idna==3.4
imageio==2.34.2
importlib-metadata @ file:///rapids/importlib_metadata-6.8.0-py3-none-any.whl#sha256=3ebb78df84a805d7698245025b975d9d67053cd94c79245ba4b3eb694abe68bb
iniconfig==2.0.0
intel-openmp==2021.4.0
interegular==0.3.3
ipykernel==6.25.2
ipython==8.16.1
ipython-genutils==0.2.0
ja-sentence-segmenter==0.0.2
jedi==0.19.1
jieba3k==0.35.1
Jinja2==3.1.2
joblib==1.3.2
json5==0.9.14
jsonpatch==1.33
jsonpointer==3.0.0
jsonschema==4.21.1
jsonschema-specifications==2023.7.1
jupyter-tensorboard @ git+https://github.com/cliffwoolley/jupyter_tensorboard.git@ffa7e26138b82549453306e06b535a9ac36db17a
jupyter_client==8.3.1
jupyter_core==5.3.2
jupyterlab==2.3.2
jupyterlab-pygments==0.2.2
jupyterlab-server==1.2.0
jupytext==1.15.2
kiwisolver==1.4.5
langchain==0.2.3
langchain-community==0.2.4
langchain-core==0.2.5
langchain-openai==0.1.8
langchain-text-splitters==0.2.1
langcodes==3.3.0
langsmith==0.1.92
lark==1.1.9
lazy_loader==0.4
librosa==0.9.2
llvmlite @ file:///rapids/llvmlite-0.40.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=bbd5e82cc990e5a3e343a3bf855c26fdfe3bfae55225f00efd01c05bbda79918
lm-format-enforcer==0.10.1
locket @ file:///rapids/locket-1.0.0-py2.py3-none-any.whl#sha256=b6c819a722f7b6bd955b80781788e4a66a55628b858d347536b7e81325a3a5e3
lxml==5.2.1
lxml_html_clean==0.1.1
-e git+https://github.com/state-spaces/mamba@c0a00bd1808881831ddf43206c69362d4df90cf7#egg=mamba_ssm
Markdown==3.4.4
markdown-it-py==3.0.0
MarkupSafe==2.1.3
marshmallow==3.21.3
matplotlib==3.8.0
matplotlib-inline==0.1.6
mdit-py-plugins==0.4.0
mdurl==0.1.2
mediapipe==0.10.8
mistral_common==1.3.1
mistral_inference==1.3.0
mistune==3.0.2
mkl==2021.1.1
mkl-devel==2021.1.1
mkl-include==2021.1.1
mock==5.1.0
monotonic==1.6
mpmath==1.3.0
msgpack @ file:///rapids/msgpack-1.0.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=e42b9594cc3bf4d838d67d6ed62b9e59e201862a25e9a157019e171fbe672dd3
multidict @ file:///rapids/multidict-6.0.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=36c63aaa167f6c6b04ef2c85704e93af16c11d20de1d133e39de6a0e84582a93
multiprocess==0.70.16
murmurhash==1.0.10
mypy-extensions==1.0.0
nbclient==0.8.0
nbconvert==7.9.2
nbformat==5.9.2
nest-asyncio==1.5.8
networkx==3.3
newspaper3k==0.2.8
ninja==1.11.1.1
nltk==3.8.1
notebook==6.4.10
numba @ file:///rapids/numba-0.57.1%2B1.g5fba9aa8f-cp310-cp310-linux_x86_64.whl#sha256=348d18dbb5ce363133fa7d033ae804b5440bf51778395f08b337a9ca6ac98e53
numpy==1.23.5
nvfuser==0.0.20+gitunknown
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==8.9.2.26
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-dali-cuda120==1.30.0
nvidia-ml-py==12.555.43
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.5.82
nvidia-nvtx-cu12==12.1.105
nvidia-pyindex==1.0.9
nvtx @ file:///rapids/nvtx-0.2.5-cp310-cp310-linux_x86_64.whl#sha256=b8024910cace4d07e6c9677eaf3be1b3e626fa1923ec6e3c7e5d3fdca053c9c9
oauthlib==3.2.2
omegaconf==2.3.0
onnx @ file:///opt/pytorch/pytorch/third_party/onnx
onnxruntime==1.18.1
openai==1.35.15
opencv @ file:///opencv-4.7.0/modules/python/package
opencv-contrib-python==4.10.0.84
opencv-python==4.10.0.84
orjson==3.10.6
outlines==0.0.46
packaging==23.2
pandas @ file:///rapids/pandas-1.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=7a0a56cef15fd1586726dace5616db75ebcfec9179a3a55e78f72c5639fa2a23
pandocfilters==1.5.0
parso==0.8.3
partd @ file:///rapids/partd-1.4.0-py3-none-any.whl#sha256=7a63529348cf0dff14b986db641cd1b83c16b5cb9fc647c2851779db03282ef8
pathy==0.10.2
pexpect==4.8.0
pickleshare==0.7.5
Pillow==10.1.0
platformdirs==3.11.0
pluggy==1.3.0
ply @ file:///rapids/ply-3.11-py2.py3-none-any.whl#sha256=096f9b8350b65ebd2fd1346b12452efe5b9607f7482813ffca50c22722a807ce
polygraphy==0.49.0
pooch==1.7.0
preshed==3.0.9
prettytable==3.9.0
prometheus-fastapi-instrumentator==7.0.0
prometheus_client==0.20.0
prompt-toolkit==3.0.39
protobuf==3.20.3
psutil @ file:///rapids/psutil-5.9.4-cp310-abi3-linux_x86_64.whl#sha256=e711cfad802fd4061d559d17e9f175e866551434c3418af2925881a3e5f3440e
ptxcompiler @ file:///rapids/ptxcompiler-0.8.1%2B1.g2cb1b35-cp310-cp310-linux_x86_64.whl#sha256=461049ad74511c8d923967e1826861a0d9a2bcee0cfcf3ebc338fc48b3ecc724
ptyprocess==0.7.0
pure-eval==0.2.2
py-cpuinfo==9.0.0
pyairports==2.1.1
pyarrow==17.0.0
pyarrow-hotfix==0.6
pyasn1==0.5.0
pyasn1-modules==0.3.0
pybind11==2.11.1
pybind11-global==2.11.1
pycocotools @ git+https://github.com/nvidia/cocoapi.git@fa44301f7a8b3f95a9f2751d19bfd735b0f6c65d#subdirectory=PythonAPI
pycountry==24.6.1
pycparser==2.21
pydantic==2.6.1
pydantic_core==2.16.2
Pygments==2.16.1
pylibcugraph @ file:///rapids/pylibcugraph-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=8327053f864ed56bf0d0d8fb69a2291ca1e044fa1f447e63b85b29bf72102c74
pylibcugraphops @ file:///rapids/pylibcugraphops-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=17364a79cda63c9f6c62ef6f2bd37151a9e70539f6d60e43fb26ab40e163bba2
pylibraft @ file:///rapids/pylibraft-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=f74580fec4d0e1603f9b3027da33d915ce07a37d2790c28b1d784d133e90a6d2
pynvml @ file:///rapids/pynvml-11.4.1-py3-none-any.whl#sha256=d27be542cd9d06558de18e2deffc8022ccd7355bc7382255d477038e7e424c6c
pyparsing==3.1.1
pytest==7.4.2
pytest-flakefinder==1.1.0
pytest-rerunfailures==12.0
pytest-shard==0.1.2
pytest-xdist==3.3.1
python-dateutil==2.8.2
python-dotenv==1.0.1
python-hostlist==1.23.0
python-multipart==0.0.9
pytorch-quantization==2.1.2
pytz @ file:///rapids/pytz-2023.3-py2.py3-none-any.whl#sha256=a151b3abb88eda1d4e34a9814df37de2a80e301e68ba0fd856fb9b46bfbbbffb
PyYAML==6.0
pyzmq==25.1.1
raft-dask @ file:///rapids/raft_dask-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=9464bd2889aff217d63f2ff804f06328123119e72745399900315fc85f4d6b7e
ray==2.32.0
redis==5.0.3
referencing==0.30.2
regex==2023.10.3
requests==2.32.3
requests-file==2.1.0
requests-oauthlib==1.3.1
resampy==0.4.2
rich==13.7.1
rmm @ file:///rapids/rmm-23.8.0-cp310-cp310-linux_x86_64.whl#sha256=11e3bc42ddfa51f8293ddb37fb006e4dd59fc20534e8f027b5453c8d00fa089f
rpds-py==0.10.4
rsa==4.9
safetensors==0.4.3
scikit-image==0.24.0
scikit-learn @ file:///rapids/scikit_learn-1.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=184a42842a4e698ffa4d849b6019de50a77a0aa24d26afa28fa49c9190bb144b
scipy @ file:///rapids/scipy-1.11.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=366a6a937110d80dca4f63b3f5b00cc89d36f678b2d124a01067b154e692bab1
Send2Trash==1.8.2
sentence-transformers==3.0.1
sentencepiece==0.2.0
sgmllib3k==1.0.0
simple_parsing==0.1.5
six==1.16.0
smart-open==6.4.0
sniffio==1.3.1
sortedcontainers==2.4.0
sounddevice==0.4.7
soundfile==0.12.1
soupsieve==2.5
spacy==3.7.1
spacy-legacy==3.0.12
spacy-loggers==1.0.5
sphinx-glpi-theme==0.3
SQLAlchemy==2.0.31
srsly==2.4.8
stack-data==0.6.3
starlette==0.36.3
sympy==1.12
tabulate==0.9.0
tbb==2021.10.0
tblib @ file:///rapids/tblib-2.0.0-py3-none-any.whl#sha256=9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a
tenacity==8.5.0
tensorboard==2.9.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorrt @ file:///workspace/TensorRT-8.6.1.6/python/tensorrt-8.6.1-cp310-none-linux_x86_64.whl#sha256=2684b4772cb16088184266728a0668f5dac14e66f088c4ccff2096ccb222d74c
termcolor==2.4.0
terminado==0.17.1
thinc==8.2.1
thread6==0.2.0
threadpoolctl==3.2.0
thriftpy2 @ file:///rapids/thriftpy2-0.4.16-cp310-cp310-linux_x86_64.whl#sha256=3b41ffe57f0a10ee592e06b4843e37ae1bc7f0309a2478f0bf1368ede2ad4ed4
tifffile==2024.7.2
tiktoken==0.7.0
timm==1.0.7
tinycss2==1.2.1
tinysegmenter==0.3
tldextract==5.1.2
tokenizers==0.19.1
toml==0.10.2
tomli==2.0.1
toolz @ file:///rapids/toolz-0.12.0-py3-none-any.whl#sha256=2059bd4148deb1884bb0eb770a3cde70e7f954cfbbdc2285f1f2de01fd21eb6f
torch==2.3.0
torch-tensorrt @ file:///opt/pytorch/torch_tensorrt/dist/torch_tensorrt-0.0.0-cp310-cp310-linux_x86_64.whl#sha256=239cc59958283c8fd764ec360b93adf63db94d231c6dbae3212736187d1c1f21
torchdata @ file:///opt/pytorch/data
torchtext @ file:///opt/pytorch/text
torchvision==0.18.0
tornado==6.3.3
tqdm==4.66.2
traitlets==5.9.0
transformers==4.42.4
treelite @ file:///rapids/treelite-3.2.0-cp310-cp310-linux_x86_64.whl#sha256=7627a3fed44ce1dda4c35ce707cca4b6108d74a661997c0451be59d03f2155ca
treelite-runtime @ file:///rapids/treelite_runtime-3.2.0-cp310-cp310-linux_x86_64.whl#sha256=085ec1ba71007d357ecebb493c490133c20778cd51d8662a0a10d1dc56b1623e
triton==2.3.0
typer==0.9.0
types-dataclasses==0.6.6
typing==3.7.4.3
typing-inspect==0.9.0
typing_extensions==4.12.2
ucx-py @ file:///rapids/ucx_py-0.33.0-cp310-cp310-linux_x86_64.whl#sha256=55d9f5f80627ba1f00577fca41ecd6ab8c72cc518e392a078d108b7dbd809c1e
uff @ file:///workspace/TensorRT-8.6.1.6/uff/uff-0.6.9-py2.py3-none-any.whl#sha256=618a3f812d491f0d3c4f2e38b99e03217ca37b206db14cee079f2bf681eb4fe3
unidic-lite==1.0.8
urllib3 @ file:///rapids/urllib3-1.26.16-py2.py3-none-any.whl#sha256=8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f
uvicorn==0.30.1
uvloop==0.19.0
vllm==0.5.0
vllm-flash-attn==2.5.9
wasabi==1.1.2
watchfiles==0.22.0
wcwidth==0.2.8
weasel==0.3.2
webencodings==0.5.1
websockets==12.0
Werkzeug==3.0.0
wrapt==1.14.1
xdoctest==1.0.2
xformers==0.0.26.post1
xgboost @ file:///rapids/xgboost-1.7.5-cp310-cp310-linux_x86_64.whl#sha256=56f29fb999f8272bf8498ecbaf0659de4becf693b96a545f0e52f627270cf80d
xxhash==3.4.1
yarl @ file:///rapids/yarl-1.9.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=891c0e3ec5ec881541f6c5113d8df0315ce5440e244a716b95f2525b7b9f3608
zict @ file:///rapids/zict-3.0.0-py2.py3-none-any.whl#sha256=5796e36bd0e0cc8cf0fbc1ace6a68912611c1dbd74750a3f3026b9b9d6a327ae
zipp @ file:///rapids/zipp-3.16.2-py3-none-any.whl#sha256=679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0

Reproduction Steps

mistral-chat $LLM_MODEL --instruct --max_tokens 256
$LLM_MODEL is mamba-codestral-7B-v0.1 folder

Traceback (most recent call last):
  File "/usr/local/bin/mistral-chat", line 8, in <module>
    sys.exit(mistral_chat())
  File "/usr/local/lib/python3.10/dist-packages/mistral_inference/main.py", line 203, in mistral_chat
    fire.Fire(interactive)
  File "/usr/local/lib/python3.10/dist-packages/fire/core.py", line 143, in Fire
    component_trace = _Fire(component, args, parsed_flag_args, context, name)
  File "/usr/local/lib/python3.10/dist-packages/fire/core.py", line 477, in _Fire
    component, remaining_args = _CallAndUpdateTrace(
  File "/usr/local/lib/python3.10/dist-packages/fire/core.py", line 693, in _CallAndUpdateTrace
    component = fn(*varargs, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/mistral_inference/main.py", line 117, in interactive
    generated_tokens, _ = generate_fn(  # type: ignore[operator]
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/mistral_inference/generate.py", line 21, in generate_mamba
    output = model.model.generate(
  File "/usr/local/setup/mamba/mamba_ssm/utils/generation.py", line 260, in generate
    output = decode(
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/usr/local/setup/mamba/mamba_ssm/utils/generation.py", line 221, in decode
    scores.append(get_logits(sequences[-1], inference_params))
  File "/usr/local/setup/mamba/mamba_ssm/utils/generation.py", line 184, in get_logits
    logits = model(
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/setup/mamba/mamba_ssm/models/mixer_seq_simple.py", line 279, in forward
    hidden_states = self.backbone(input_ids, inference_params=inference_params, **mixer_kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/setup/mamba/mamba_ssm/models/mixer_seq_simple.py", line 194, in forward
    hidden_states, residual = layer(
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/setup/mamba/mamba_ssm/modules/block.py", line 67, in forward
    hidden_states = self.mixer(hidden_states, inference_params=inference_params, **mixer_kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/setup/mamba/mamba_ssm/modules/mamba2.py", line 233, in forward
    self.conv1d(xBC.transpose(1, 2)).transpose(1, 2)[:, -(self.dconv - 1):]
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1709, in __getattr__
    raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Mamba2' object has no attribute 'dconv'. Did you mean: 'd_conv'?

Expected Behavior

chat output

Additional Context

I install mistral-inference and causal-conv1d from pip
mamba-ssm build from github source. (2.2.2 )
because it raise Undefined Symbol Error.

Suggested Solutions

No response