cudf: Cannot even import cudf (librmm.so error)
- I am using the latest version of cuDF from conda, built from
master, or built from the latest tagged release. - I have included the following environment details: Linux Distro, Linux Kernel, GPU Model
Linux: Ubuntu 18.04 kernel 4.15.0 miniconda3 python 3.6.6 cudf 0.3.0 gpu GTX 1050 Ti
Problems on getting started to rapids.ai.
Error on loading cudf:
What have I missed?
`--------------------------------------------------------------------------- OSError Traceback (most recent call last) <ipython-input-6-e13365c50bc4> in <module> ----> 1 import cudf
~/miniconda3/lib/python3.6/site-packages/cudf/init.py in <module> 1 # Copyright © 2018, NVIDIA CORPORATION. ----> 2 from cudf import dataframe # noqa: F401 3 4 from cudf.dataframe import DataFrame # noqa: F401 5 from cudf.dataframe import Index # noqa: F401
~/miniconda3/lib/python3.6/site-packages/cudf/dataframe/init.py in <module> ----> 1 from cudf.dataframe import (buffer, dataframe, series, # noqa: F401 2 index, numerical, datetime) # noqa: F401 3 4 from cudf.dataframe.dataframe import DataFrame # noqa: F401 5 from cudf.dataframe.index import (Index, GenericIndex, # noqa: F401
~/miniconda3/lib/python3.6/site-packages/cudf/dataframe/buffer.py in <module> 1 import numpy as np 2 ----> 3 from librmm_cffi import librmm as rmm 4 5 from cudf.utils import cudautils, utils
~/miniconda3/lib/python3.6/site-packages/librmm_cffi/init.py in <module> 43 return path 44 —> 45 librmm_api = ffi.dlopen(_get_lib_name()) 46 librmm = _RMMWrapper(ffi, librmm_api) 47
OSError: cannot load library ‘librmm.so’: libcudart.so.9.2: cannot open shared object file: No such file or directory`
About this issue
- Original URL
- State: closed
- Created 6 years ago
- Reactions: 1
- Comments: 26 (9 by maintainers)
Commits related to this issue
- Merge branch 'branch-0.5' into fix-#441 — committed to kayush2O6/cudf by kayush2O6 6 years ago
Could we re-open this issue. It seems to be resolved by manually post-fixing instructions that are in documentation (using steps described in comments). I run into same issue, but not in a container. Could we include required fixes in readme in installation instructions? so it is clear how to approach error:
Precisely speaking, whatever is necessary but haven’t been mentioned in installation instructions, like extra software to install, source from where to install that software, what to put to LD_LIBRARY_PATH, etc.
@harrism I have cuda toolkit 10.
here are my environment entries export PATH=/usr/local/cuda-10.0/bin${PATH:+:$PATH}} export PATH=/usr/local/MATLAB/bin${PATH:+:$PATH}} export CUDADIR=/usr/local/cuda-10.0 export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} export LD_LIBRARY_PATH=/usr/local/lib${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} export NUMBAPRO_NVVM=/usr/local/cuda-10.0/nvvm/lib64/libnvvm.so export NUMBAPRO_LIBDEVICE=/usr/local/cuda-10.0/nvvm/libdevice
for cudf-cuda100==0.6, I get the following error on import OSError: cannot load library ‘librmm.so’: librmm.so: cannot open shared object file: No such file or directory
for cudf-cuda100==0.5, import is succesful but on creating a dataframe: cudf.DataFrame({‘x’: np.random.rand(100)}) below is returned GDFError: CUDA ERROR. cudaSuccess: no error
@AK-ayush Thanks for the help. I have just discovered I must install “cudatoolkit” package in conda. I had installed “cuda92” package only. It is not clear in the docs.
Now i’m able to start things properly.
Thank you all for the help.
I have just installed cudf from conda, according to the documentation, by runing
$ conda install -c numba -c conda-forge -c nvidia -c rapidsai -c defaults cudf=0.3.0