Closed
Description
Describe the bug
Up untill a few days ago NUMBA CUDA was working fine on google colab.
Apparantly google colab got updated from CUDA 12.1 to CUDA 12.4 and now NUMBA CUDA no longer works and gives the CUDA_ERROR_UNSUPPORTED_PTX_VERSION error. (it apparently needs 8.5 but only 8.4 is available.
Steps/Code to reproduce bug
The following simple example doesn't even work:
`from numba import cuda
import numpy as np
@cuda.jit
def increment_by_one(an_array):
pos = cuda.grid(1)
if pos < an_array.size:
an_array[pos] += 1
an_array = np.zeros(10)
increment_by_one[16,16](an_array)`
Expected behavior
I would expect this sample to run however it fails with the following error:
/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py:536: NumbaPerformanceWarning: Grid size 16 will likely result in GPU under-utilization due to low occupancy.
warn(NumbaPerformanceWarning(msg))
ERROR:numba.cuda.cudadrv.driver:Call to cuLinkAddData results in CUDA_ERROR_UNSUPPORTED_PTX_VERSION
---------------------------------------------------------------------------
CudaAPIError Traceback (most recent call last)
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/cudadrv/driver.py](https://localhost:8080/#) in add_ptx(self, ptx, name)
2806 try:
-> 2807 driver.cuLinkAddData(self.handle, enums.CU_JIT_INPUT_PTX,
2808 ptxbuf, len(ptx), namebuf, 0, None, None)
10 frames
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/cudadrv/driver.py](https://localhost:8080/#) in safe_cuda_api_call(*args)
303 retcode = libfn(*args)
--> 304 self._check_ctypes_error(fname, retcode)
305
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/cudadrv/driver.py](https://localhost:8080/#) in _check_ctypes_error(self, fname, retcode)
371 self._detect_fork()
--> 372 raise CudaAPIError(retcode, msg)
373
CudaAPIError: [222] Call to cuLinkAddData results in CUDA_ERROR_UNSUPPORTED_PTX_VERSION
During handling of the above exception, another exception occurred:
LinkerError Traceback (most recent call last)
[<ipython-input-1-577f16a0e5d0>](https://localhost:8080/#) in <cell line: 0>()
9
10 an_array = np.zeros(10)
---> 11 increment_by_one[16,16](an_array)
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py](https://localhost:8080/#) in __call__(self, *args)
537
538 def __call__(self, *args):
--> 539 return self.dispatcher.call(args, self.griddim, self.blockdim,
540 self.stream, self.sharedmem)
541
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py](https://localhost:8080/#) in call(self, args, griddim, blockdim, stream, sharedmem)
679 kernel = next(iter(self.overloads.values()))
680 else:
--> 681 kernel = _dispatcher.Dispatcher._cuda_call(self, *args)
682
683 kernel.launch(args, griddim, blockdim, stream, sharedmem)
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py](https://localhost:8080/#) in _compile_for_args(self, *args, **kws)
687 assert not kws
688 argtypes = [self.typeof_pyval(a) for a in args]
--> 689 return self.compile(tuple(argtypes))
690
691 def typeof_pyval(self, val):
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py](https://localhost:8080/#) in compile(self, sig)
932 kernel = _Kernel(self.py_func, argtypes, **self.targetoptions)
933 # We call bind to force codegen, so that there is a cubin to cache
--> 934 kernel.bind()
935 self._cache.save_overload(sig, kernel)
936
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/dispatcher.py](https://localhost:8080/#) in bind(self)
195 Force binding to current CUDA context
196 """
--> 197 self._codelibrary.get_cufunc()
198
199 @property
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/codegen.py](https://localhost:8080/#) in get_cufunc(self)
212 return cufunc
213
--> 214 cubin = self.get_cubin(cc=device.compute_capability)
215 module = ctx.create_module_image(cubin)
216
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/codegen.py](https://localhost:8080/#) in get_cubin(self, cc)
186 else:
187 ptx = self.get_asm_str(cc=cc)
--> 188 linker.add_ptx(ptx.encode())
189
190 for path in self._linking_files:
[/usr/local/lib/python3.11/dist-packages/numba_cuda/numba/cuda/cudadrv/driver.py](https://localhost:8080/#) in add_ptx(self, ptx, name)
2808 ptxbuf, len(ptx), namebuf, 0, None, None)
2809 except CudaAPIError as e:
-> 2810 raise LinkerError("%s\n%s" % (e, self.error_log))
2811
2812 def add_file(self, path, kind):
LinkerError: [222] Call to cuLinkAddData results in CUDA_ERROR_UNSUPPORTED_PTX_VERSION
ptxas application ptx input, line 9; fatal : Unsupported .version 8.5; current version is '8.4'
Environment details (please complete the following information):
- Environment location: Google colab
- Method of numba-cuda install: Buildin Google colab.
- When running !numba -s it shows the following:
System info:
--------------------------------------------------------------------------------
__Time Stamp__
Report started (local time) : 2025-02-01 12:26:38.262020
UTC start time : 2025-02-01 12:26:38.262024
Running time (s) : 1.580988
__Hardware Information__
Machine : x86_64
CPU Name : skylake-avx512
CPU Count : 2
Number of accessible CPUs : 2
List of accessible CPUs cores : 0 1
CFS Restrictions (CPUs worth of runtime) : None
CPU Features : 64bit adx aes avx avx2 avx512bw
avx512cd avx512dq avx512f avx512vl
bmi bmi2 clflushopt clwb cmov
crc32 cx16 cx8 f16c fma fsgsbase
fxsr invpcid lzcnt mmx movbe
pclmul popcnt prfchw rdrnd rdseed
rtm sahf sse sse2 sse3 sse4.1
sse4.2 ssse3 xsave xsavec xsaveopt
xsaves
Memory Total (MB) : 12978
Memory Available (MB) : 11409
__OS Information__
Platform Name : Linux-6.1.85+-x86_64-with-glibc2.35
Platform Release : 6.1.85+
OS Name : Linux
OS Version : #1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
OS Specific Version : ?
Libc Version : glibc 2.35
__Python Information__
Python Compiler : GCC 11.4.0
Python Implementation : CPython
Python Version : 3.11.11
Python Locale : en_US.UTF-8
__Numba Toolchain Versions__
Numba Version : 0.60.0
llvmlite Version : 0.43.0
__LLVM Information__
LLVM Version : 14.0.6
__CUDA Information__
CUDA Device Initialized : True
CUDA Driver Version : 12.4
CUDA Runtime Version : 12.5
CUDA NVIDIA Bindings Available : True
CUDA NVIDIA Bindings In Use : False
CUDA Minor Version Compatibility Available : False
CUDA Minor Version Compatibility Needed : True
CUDA Minor Version Compatibility In Use : False
CUDA Detect Output:
Found 1 CUDA devices
id 0 b'Tesla T4' [SUPPORTED]
Compute Capability: 7.5
PCI Device ID: 4
PCI Bus ID: 0
UUID: GPU-76ec7180-6602-1397-f389-5561412bb3e9
Watchdog: Disabled
FP32/FP64 Performance Ratio: 32
Summary:
1/1 devices are supported
CUDA Libraries Test Output:
Finding driver from candidates:
libcuda.so
libcuda.so.1
/usr/lib/libcuda.so
/usr/lib/libcuda.so.1
/usr/lib64/libcuda.so
/usr/lib64/libcuda.so.1
Using loader <class 'ctypes.CDLL'>
Trying to load driver... ok
Loaded from libcuda.so
Mapped libcuda.so paths:
/usr/lib64-nvidia/libcuda.so.550.54.15
Finding nvvm from System
Located at /usr/local/cuda/nvvm/lib64/libnvvm.so.4.0.0
Trying to open library... ok
Finding nvrtc from System
Located at /usr/local/cuda/lib64/libnvrtc.so.12.5.82
Trying to open library... ok
Finding cudart from System
Located at /usr/local/cuda/lib64/libcudart.so.12.5.82
Trying to open library... ok
Finding cudadevrt from System
Located at /usr/local/cuda/lib64/libcudadevrt.a
Checking library... ok
Finding libdevice from System
Located at /usr/local/cuda/nvvm/libdevice/libdevice.10.bc
Checking library... ok
__NumPy Information__
NumPy Version : 1.26.4
NumPy Supported SIMD features : ('MMX', 'SSE', 'SSE2', 'SSE3', 'SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2', 'AVX512F', 'AVX512CD', 'AVX512VL', 'AVX512BW', 'AVX512DQ', 'AVX512_SKX')
NumPy Supported SIMD dispatch : ('SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2', 'AVX512F', 'AVX512CD', 'AVX512_KNL', 'AVX512_KNM', 'AVX512_SKX', 'AVX512_CLX', 'AVX512_CNL', 'AVX512_ICL')
NumPy Supported SIMD baseline : ('SSE', 'SSE2', 'SSE3')
NumPy AVX512_SKX support detected : True
__SVML Information__
SVML State, config.USING_SVML : False
SVML Library Loaded : False
llvmlite Using SVML Patched LLVM : True
SVML Operational : False
__Threading Layer Information__
TBB Threading Layer Available : True
+-->TBB imported successfully.
OpenMP Threading Layer Available : True
+-->Vendor: GNU
Workqueue Threading Layer Available : True
+-->Workqueue imported successfully.
__Numba Environment Variable Information__
None found.
__Conda Information__
Conda not available.
__Installed Packages__
Package Version
---------------------------------- -------------------
absl-py 1.4.0
accelerate 1.2.1
aiohappyeyeballs 2.4.4
aiohttp 3.11.11
aiosignal 1.3.2
alabaster 1.0.0
albucore 0.0.19
albumentations 1.4.20
ale-py 0.10.1
altair 5.5.0
annotated-types 0.7.0
anyio 3.7.1
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
array_record 0.6.0
arviz 0.20.0
astropy 6.1.7
astropy-iers-data 0.2025.1.27.0.32.44
astunparse 1.6.3
atpublic 4.1.0
attrs 25.1.0
audioread 3.0.1
autograd 1.7.0
babel 2.16.0
backcall 0.2.0
beautifulsoup4 4.12.3
bigframes 1.34.0
bigquery-magics 0.5.0
bleach 6.2.0
blinker 1.9.0
blis 0.7.11
blosc2 3.0.0
bokeh 3.6.2
Bottleneck 1.4.2
bqplot 0.12.44
branca 0.8.1
CacheControl 0.14.2
cachetools 5.5.1
catalogue 2.0.10
certifi 2024.12.14
cffi 1.17.1
chardet 5.2.0
charset-normalizer 3.4.1
chex 0.1.88
clarabel 0.9.0
click 8.1.8
cloudpathlib 0.20.0
cloudpickle 3.1.1
cmake 3.31.4
cmdstanpy 1.2.5
colorcet 3.1.0
colorlover 0.3.0
colour 0.1.5
community 1.0.0b1
confection 0.1.5
cons 0.4.6
contourpy 1.3.1
cramjam 2.9.1
cryptography 43.0.3
cuda-python 12.6.0
cudf-cu12 24.12.0
cufflinks 0.17.3
cupy-cuda12x 13.3.0
cvxopt 1.3.2
cvxpy 1.6.0
cycler 0.12.1
cyipopt 1.5.0
cymem 2.0.11
Cython 3.0.11
dask 2024.10.0
datascience 0.17.6
db-dtypes 1.4.0
dbus-python 1.2.18
debugpy 1.8.0
decorator 4.4.2
defusedxml 0.7.1
Deprecated 1.2.18
diffusers 0.32.2
distro 1.9.0
dlib 19.24.2
dm-tree 0.1.8
docker-pycreds 0.4.0
docstring_parser 0.16
docutils 0.21.2
dopamine_rl 4.1.2
duckdb 1.1.3
earthengine-api 1.4.6
easydict 1.13
editdistance 0.8.1
eerepr 0.1.0
einops 0.8.0
en-core-web-sm 3.7.1
entrypoints 0.4
et_xmlfile 2.0.0
etils 1.11.0
etuples 0.3.9
eval_type_backport 0.2.2
Farama-Notifications 0.0.4
fastai 2.7.18
fastcore 1.7.28
fastdownload 0.0.7
fastjsonschema 2.21.1
fastprogress 1.0.3
fastrlock 0.8.3
filelock 3.17.0
firebase-admin 6.6.0
Flask 3.1.0
flatbuffers 25.1.24
flax 0.10.2
folium 0.19.4
fonttools 4.55.7
frozendict 2.4.6
frozenlist 1.5.0
fsspec 2024.10.0
future 1.0.0
gast 0.6.0
gcsfs 2024.10.0
GDAL 3.6.4
gdown 5.2.0
geemap 0.35.1
gensim 4.3.3
geocoder 1.38.1
geographiclib 2.0
geopandas 1.0.1
geopy 2.4.1
gin-config 0.5.0
gitdb 4.0.12
GitPython 3.1.44
glob2 0.7
google 2.0.3
google-ai-generativelanguage 0.6.15
google-api-core 2.19.2
google-api-python-client 2.155.0
google-auth 2.27.0
google-auth-httplib2 0.2.0
google-auth-oauthlib 1.2.1
google-cloud-aiplatform 1.74.0
google-cloud-bigquery 3.25.0
google-cloud-bigquery-connection 1.17.0
google-cloud-bigquery-storage 2.27.0
google-cloud-bigtable 2.28.1
google-cloud-core 2.4.1
google-cloud-datastore 2.20.2
google-cloud-firestore 2.19.0
google-cloud-functions 1.19.0
google-cloud-iam 2.17.0
google-cloud-language 2.16.0
google-cloud-pubsub 2.25.0
google-cloud-resource-manager 1.14.0
google-cloud-spanner 3.51.0
google-cloud-storage 2.19.0
google-cloud-translate 3.19.0
google-colab 1.0.0
google-crc32c 1.6.0
google-genai 0.3.0
google-generativeai 0.8.4
google-pasta 0.2.0
google-resumable-media 2.7.2
googleapis-common-protos 1.66.0
googledrivedownloader 0.4
graphviz 0.20.3
greenlet 3.1.1
grpc-google-iam-v1 0.14.0
grpc-interceptor 0.15.4
grpcio 1.70.0
grpcio-status 1.62.3
gspread 6.1.4
gspread-dataframe 4.0.0
gym 0.25.2
gym-notices 0.0.8
gymnasium 1.0.0
h11 0.14.0
h5netcdf 1.5.0
h5py 3.12.1
highspy 1.9.0
holidays 0.65
holoviews 1.20.0
html5lib 1.1
httpcore 1.0.7
httpimport 1.4.0
httplib2 0.22.0
httpx 0.28.1
huggingface-hub 0.27.1
humanize 4.11.0
hyperopt 0.2.7
ibis-framework 9.2.0
idna 3.10
imageio 2.36.1
imageio-ffmpeg 0.6.0
imagesize 1.4.1
imbalanced-learn 0.13.0
imgaug 0.4.0
immutabledict 4.2.1
importlib_metadata 8.6.1
importlib_resources 6.5.2
imutils 0.5.4
inflect 7.5.0
iniconfig 2.0.0
intel-cmplr-lib-ur 2025.0.4
intel-openmp 2025.0.4
ipyevents 2.0.2
ipyfilechooser 0.6.0
ipykernel 5.5.6
ipyleaflet 0.19.2
ipyparallel 8.8.0
ipython 7.34.0
ipython-genutils 0.2.0
ipython-sql 0.5.0
ipytree 0.2.2
ipywidgets 7.7.1
itsdangerous 2.2.0
jax 0.4.33
jax-cuda12-pjrt 0.4.33
jax-cuda12-plugin 0.4.33
jaxlib 0.4.33
jeepney 0.7.1
jellyfish 1.1.0
jieba 0.42.1
Jinja2 3.1.5
jiter 0.8.2
joblib 1.4.2
jsonpatch 1.33
jsonpickle 4.0.1
jsonpointer 3.0.0
jsonschema 4.23.0
jsonschema-specifications 2024.10.1
jupyter-client 6.1.12
jupyter-console 6.1.0
jupyter_core 5.7.2
jupyter-leaflet 0.19.2
jupyter-server 1.24.0
jupyterlab_pygments 0.3.0
jupyterlab_widgets 3.0.13
kaggle 1.6.17
kagglehub 0.3.6
keras 3.8.0
keras-hub 0.18.1
keras-nlp 0.18.1
keyring 23.5.0
kiwisolver 1.4.8
langchain 0.3.16
langchain-core 0.3.32
langchain-text-splitters 0.3.5
langcodes 3.5.0
langsmith 0.3.2
language_data 1.3.0
launchpadlib 1.10.16
lazr.restfulclient 0.14.4
lazr.uri 1.0.6
lazy_loader 0.4
libclang 18.1.1
libcudf-cu12 24.12.0
libkvikio-cu12 24.12.1
librosa 0.10.2.post1
lightgbm 4.5.0
linkify-it-py 2.0.3
llvmlite 0.43.0
locket 1.0.0
logical-unification 0.4.6
lxml 5.3.0
marisa-trie 1.2.1
Markdown 3.7
markdown-it-py 3.0.0
MarkupSafe 3.0.2
matplotlib 3.10.0
matplotlib-inline 0.1.7
matplotlib-venn 1.1.1
mdit-py-plugins 0.4.2
mdurl 0.1.2
miniKanren 1.0.3
missingno 0.5.2
mistune 3.1.1
mizani 0.13.1
mkl 2025.0.1
ml-dtypes 0.4.1
mlxtend 0.23.4
more-itertools 10.5.0
moviepy 1.0.3
mpmath 1.3.0
msgpack 1.1.0
multidict 6.1.0
multipledispatch 1.0.0
multitasking 0.0.11
murmurhash 1.0.12
music21 9.3.0
namex 0.0.8
narwhals 1.24.1
natsort 8.4.0
nbclassic 1.2.0
nbclient 0.10.2
nbconvert 7.16.6
nbformat 5.10.4
ndindex 1.9.2
nest-asyncio 1.6.0
networkx 3.4.2
nibabel 5.3.2
nltk 3.9.1
notebook 6.5.5
notebook_shim 0.2.4
numba 0.60.0
numba-cuda 0.0.17.1
numexpr 2.10.2
numpy 1.26.4
nvidia-cublas-cu12 12.5.3.2
nvidia-cuda-cupti-cu12 12.5.82
nvidia-cuda-nvcc-cu12 12.5.82
nvidia-cuda-nvrtc-cu12 12.5.82
nvidia-cuda-runtime-cu12 12.5.82
nvidia-cudnn-cu12 9.3.0.75
nvidia-cufft-cu12 11.2.3.61
nvidia-curand-cu12 10.3.6.82
nvidia-cusolver-cu12 11.6.3.83
nvidia-cusparse-cu12 12.5.1.3
nvidia-nccl-cu12 2.21.5
nvidia-nvcomp-cu12 4.1.0.6
nvidia-nvjitlink-cu12 12.5.82
nvidia-nvtx-cu12 12.4.127
nvtx 0.2.10
nx-cugraph-cu12 24.12.0
oauth2client 4.1.3
oauthlib 3.2.2
openai 1.59.9
opencv-contrib-python 4.10.0.84
opencv-python 4.10.0.84
opencv-python-headless 4.11.0.86
openpyxl 3.1.5
opentelemetry-api 1.16.0
opentelemetry-sdk 1.16.0
opentelemetry-semantic-conventions 0.37b0
opt_einsum 3.4.0
optax 0.2.4
optree 0.14.0
orbax-checkpoint 0.6.4
orjson 3.10.15
osqp 0.6.7.post3
packaging 24.2
pandas 2.2.2
pandas-datareader 0.10.0
pandas-gbq 0.26.1
pandas-stubs 2.2.2.240909
pandocfilters 1.5.1
panel 1.6.0
param 2.2.0
parso 0.8.4
parsy 2.1
partd 1.4.2
pathlib 1.0.1
patsy 1.0.1
peewee 3.17.8
peft 0.14.0
pexpect 4.9.0
pickleshare 0.7.5
pillow 11.1.0
pip 24.1.2
platformdirs 4.3.6
plotly 5.24.1
plotnine 0.14.5
pluggy 1.5.0
ply 3.11
polars 1.9.0
pooch 1.8.2
portpicker 1.5.2
preshed 3.0.9
prettytable 3.13.0
proglog 0.1.10
progressbar2 4.5.0
prometheus_client 0.21.1
promise 2.3
prompt_toolkit 3.0.50
propcache 0.2.1
prophet 1.1.6
proto-plus 1.26.0
protobuf 4.25.6
psutil 5.9.5
psycopg2 2.9.10
ptyprocess 0.7.0
py-cpuinfo 9.0.0
py4j 0.10.9.7
pyarrow 17.0.0
pyasn1 0.6.1
pyasn1_modules 0.4.1
pycocotools 2.0.8
pycparser 2.22
pydantic 2.10.6
pydantic_core 2.27.2
pydata-google-auth 1.9.1
pydot 3.0.4
pydotplus 2.0.2
PyDrive 1.3.1
PyDrive2 1.21.3
pyerfa 2.0.1.5
pygame 2.6.1
pygit2 1.16.0
Pygments 2.18.0
PyGObject 3.42.1
PyJWT 2.10.1
pylibcudf-cu12 24.12.0
pylibcugraph-cu12 24.12.0
pylibraft-cu12 24.12.0
pymc 5.19.1
pymystem3 0.2.0
pynvjitlink-cu12 0.5.0
pyogrio 0.10.0
Pyomo 6.8.2
PyOpenGL 3.1.9
pyOpenSSL 24.2.1
pyparsing 3.2.1
pyperclip 1.9.0
pyproj 3.7.0
pyshp 2.3.1
PySocks 1.7.1
pyspark 3.5.4
pytensor 2.26.4
pytest 8.3.4
python-apt 0.0.0
python-box 7.3.2
python-dateutil 2.8.2
python-louvain 0.16
python-slugify 8.0.4
python-snappy 0.7.3
python-utils 3.9.1
pytz 2024.2
pyviz_comms 3.0.4
PyYAML 6.0.2
pyzmq 24.0.1
qdldl 0.1.7.post5
ratelim 0.1.6
referencing 0.36.2
regex 2024.11.6
requests 2.32.3
requests-oauthlib 1.3.1
requests-toolbelt 1.0.0
requirements-parser 0.9.0
rich 13.9.4
rmm-cu12 24.12.1
rpds-py 0.22.3
rpy2 3.4.2
rsa 4.9
safetensors 0.5.2
scikit-image 0.25.1
scikit-learn 1.6.1
scipy 1.13.1
scooby 0.10.0
scs 3.2.7.post2
seaborn 0.13.2
SecretStorage 3.3.1
Send2Trash 1.8.3
sentence-transformers 3.3.1
sentencepiece 0.2.0
sentry-sdk 2.20.0
setproctitle 1.3.4
setuptools 75.1.0
shap 0.46.0
shapely 2.0.6
shellingham 1.5.4
simple-parsing 0.1.7
six 1.17.0
sklearn-compat 0.1.3
sklearn-pandas 2.2.0
slicer 0.0.8
smart-open 7.1.0
smmap 5.0.2
sniffio 1.3.1
snowballstemmer 2.2.0
soundfile 0.13.1
soupsieve 2.6
soxr 0.5.0.post1
spacy 3.7.5
spacy-legacy 3.0.12
spacy-loggers 1.0.5
spanner-graph-notebook 1.0.9
Sphinx 8.1.3
sphinxcontrib-applehelp 2.0.0
sphinxcontrib-devhelp 2.0.0
sphinxcontrib-htmlhelp 2.1.0
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 2.0.0
sphinxcontrib-serializinghtml 2.0.0
SQLAlchemy 2.0.37
sqlglot 25.6.1
sqlparse 0.5.3
srsly 2.5.1
stanio 0.5.1
statsmodels 0.14.4
stringzilla 3.11.3
sympy 1.13.1
tables 3.10.2
tabulate 0.9.0
tbb 2022.0.0
tcmlib 1.2.0
tenacity 9.0.0
tensorboard 2.18.0
tensorboard-data-server 0.7.2
tensorflow 2.18.0
tensorflow-datasets 4.9.7
tensorflow-hub 0.16.1
tensorflow-io-gcs-filesystem 0.37.1
tensorflow-metadata 1.16.1
tensorflow-probability 0.24.0
tensorflow-text 2.18.1
tensorstore 0.1.71
termcolor 2.5.0
terminado 0.18.1
text-unidecode 1.3
textblob 0.17.1
tf_keras 2.18.0
tf-slim 1.1.0
thinc 8.2.5
threadpoolctl 3.5.0
tifffile 2025.1.10
timm 1.0.14
tinycss2 1.4.0
tokenizers 0.21.0
toml 0.10.2
toolz 0.12.1
torch 2.5.1+cu124
torchaudio 2.5.1+cu124
torchsummary 1.5.1
torchvision 0.20.1+cu124
tornado 6.4.2
tqdm 4.67.1
traitlets 5.7.1
traittypes 0.2.1
transformers 4.47.1
triton 3.1.0
tweepy 4.14.0
typeguard 4.4.1
typer 0.15.1
types-pytz 2024.2.0.20241221
types-setuptools 75.8.0.20250110
typing_extensions 4.12.2
tzdata 2025.1
tzlocal 5.2
uc-micro-py 1.0.3
umf 0.9.1
uritemplate 4.1.1
urllib3 2.3.0
vega-datasets 0.9.0
wadllib 1.3.6
wandb 0.19.5
wasabi 1.1.3
wcwidth 0.2.13
weasel 0.4.1
webcolors 24.11.1
webencodings 0.5.1
websocket-client 1.8.0
websockets 14.2
Werkzeug 3.1.3
wheel 0.45.1
widgetsnbextension 3.6.10
wordcloud 1.9.4
wrapt 1.17.2
xarray 2025.1.1
xarray-einstats 0.8.0
xgboost 2.1.3
xlrd 2.0.1
xyzservices 2025.1.0
yarl 1.18.3
yellowbrick 1.5
yfinance 0.2.52
zipp 3.21.0
zstandard 0.23.0
No errors reported.
__Warning log__
Warning: Conda not available.
Error was [Errno 2] No such file or directory: 'conda'
Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_quota_us
Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_period_us
--------------------------------------------------------------------------------
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!nvidia-smi shows:
Sat Feb 1 12:37:12 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.54.15 Driver Version: 550.54.15 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |
| N/A 69C P0 30W / 70W | 102MiB / 15360MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
+-----------------------------------------------------------------------------------------+
Additional context
Add any other context about the problem here.
Updating COLAB to the lastest numba version didn't solve the problem
Crossposted to the Google COLAB GITHUB bug page (link)