Cuml: [BUG] Example Colab notebook: AttributeError: module 'cudf' has no attribute '_lib'
Describe the bug
EDIT: At the time of writing I didn't realize cuML and cuDF are in different repo's. The error appears whether one executes import cuml and/or import cudf, but since it seems to be cuDF-specific, perhaps this bug report should be closed & a new one started in the cuDF repo instead?
I'm really excited to try out your package!
I just opened a Feature Request about speeding up the install on the example Colab notebook, and the install finished (seemingly successfully) a few minutes after I submitted that FR.
So then I executed the next cell, with the cuDF example, and got:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-a95ca25217db> in <module>()
----> 1 import cudf
2 import io, requests
3
4 # download CSV file from GitHub
5 url="https://github.com/plotly/datasets/raw/master/tips.csv"
2 frames
/usr/local/lib/python3.6/site-packages/cudf/core/dataframe.py in <module>()
22
23 import cudf
---> 24 import cudf._lib as libcudf
25 import cudf._libxx as libcudfxx
26 from cudf._libxx.null_mask import MaskState, create_null_mask
AttributeError: module 'cudf' has no attribute '_lib'
Skipping that cell and running the cuML example cell produced the exact same error at the same line of code (line 24 in dataframe.py).
Steps/Code to reproduce bug
See above. Open (a fresh instance of) your example Colab notebook, save a copy of it to Drive, and try to run the cells in sequence. The second and third code cells produce the same error shown above.
Expected behavior
That I would see...whatever the intended output is supposed to be. Not an AttributeError.
Environment details (please complete the following information):
Environment location: Cloud(Google Colab)
Linux Distro/Architecture:
!cat /etc/os-release: says it's Ubuntu 18.04.3 LTS (Bionic Beaver)GPU Model/Driver: Tesla P100-PCIE-16GB. and driver 418.67
CUDA: 10.1
Here's the output from !nvidia-smi:
Sat May 30 03:33:48 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.82 Driver Version: 418.67 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla P100-PCIE... Off | 00000000:00:04.0 Off | 0 |
| N/A 44C P0 27W / 250W | 0MiB / 16280MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
- Method of cuDF & cuML install: conda, via your
rapidsai-csp-utils/colab/rapids-colab.shscript.
See output log below.
Additional context
Here's a log of the output from the install cell:
Cloning into 'rapidsai-csp-utils'...
remote: Enumerating objects: 103, done.
remote: Counting objects: 100% (103/103), done.
remote: Compressing objects: 100% (101/101), done.
remote: Total 103 (delta 21), reused 14 (delta 1), pack-reused 0
Receiving objects: 100% (103/103), 30.32 KiB | 378.00 KiB/s, done.
Resolving deltas: 100% (21/21), done.
PLEASE READ
********************************************************************************************************
Changes:
1. Now that most people have migrated, we have rem0ved the migration notice.
2. default stable version is now 0.13. Nightly is now 0.14
3. You can now declare your RAPIDS version as a CLI option and skip the user prompts (ex: '0.13' or '0.14', between 0.11 to 0.14, without the quotes):
"!bash rapidsai-csp-utils/colab/rapids-colab.sh <version/label>"
Examples: '!bash rapidsai-csp-utils/colab/rapids-colab.sh 0.13', or '!bash rapidsai-csp-utils/colab/rapids-colab.sh stable', or '!bash rapidsai-csp-utils/colab/rapids-colab.sh s'
'!bash rapidsai-csp-utils/colab/rapids-colab.sh 0.14, or '!bash rapidsai-csp-utils/colab/rapids-colab.sh nightly', or '!bash rapidsai-csp-utils/colab/rapids-colab.sh n'
Enjoy using RAPIDS!
Starting to prep Colab for install RAPIDS Version 0.13 stable
Checking for GPU type:
***********************************************************************
Woo! Your instance has the right kind of GPU, a 'Tesla P100-PCIE-16GB'!
***********************************************************************
Removing conflicting packages, will replace with RAPIDS compatible versions
Uninstalling xgboost-0.90:
Successfully uninstalled xgboost-0.90
Uninstalling dask-2.12.0:
Successfully uninstalled dask-2.12.0
Uninstalling distributed-1.25.3:
Successfully uninstalled distributed-1.25.3
Installing conda
--2020-05-30 03:34:12-- https://repo.continuum.io/miniconda/Miniconda3-4.5.4-Linux-x86_64.sh
Resolving repo.continuum.io (repo.continuum.io)... 104.18.201.79, 104.18.200.79, 2606:4700::6812:c84f, ...
Connecting to repo.continuum.io (repo.continuum.io)|104.18.201.79|:443... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: https://repo.anaconda.com/miniconda/Miniconda3-4.5.4-Linux-x86_64.sh [following]
--2020-05-30 03:34:12-- https://repo.anaconda.com/miniconda/Miniconda3-4.5.4-Linux-x86_64.sh
Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.130.3, 104.16.131.3, 2606:4700::6810:8303, ...
Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.130.3|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 58468498 (56M) [application/x-sh]
Saving to: ‘Miniconda3-4.5.4-Linux-x86_64.sh’
Miniconda3-4.5.4-Li 100%[===================>] 55.76M 100MB/s in 0.6s
2020-05-30 03:34:12 (100 MB/s) - ‘Miniconda3-4.5.4-Linux-x86_64.sh’ saved [58468498/58468498]
PREFIX=/usr/local
installing: python-3.6.5-hc3d631a_2 ...
Python 3.6.5 :: Anaconda, Inc.
installing: ca-certificates-2018.03.07-0 ...
installing: conda-env-2.6.0-h36134e3_1 ...
installing: libgcc-ng-7.2.0-hdf63c60_3 ...
installing: libstdcxx-ng-7.2.0-hdf63c60_3 ...
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installing: ncurses-6.1-hf484d3e_0 ...
installing: openssl-1.0.2o-h20670df_0 ...
installing: tk-8.6.7-hc745277_3 ...
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installing: yaml-0.1.7-had09818_2 ...
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installing: sqlite-3.23.1-he433501_0 ...
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installing: requests-2.18.4-py36he2e5f8d_1 ...
installing: conda-4.5.4-py36_0 ...
installation finished.
WARNING:
You currently have a PYTHONPATH environment variable set. This may cause
unexpected behavior when running the Python interpreter in Miniconda3.
For best results, please verify that your PYTHONPATH only points to
directories of packages that are compatible with the Python interpreter
in Miniconda3: /usr/local
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.5.4
latest version: 4.8.3
Please update conda by running
$ conda update -n base conda
## Package Plan ##
environment location: /usr/local
added / updated specs:
- openssl
- python=3.6
The following packages will be downloaded:
package | build
---------------------------|-----------------
ld_impl_linux-64-2.34 | h53a641e_4 616 KB conda-forge
certifi-2020.4.5.1 | py36h9f0ad1d_0 151 KB conda-forge
tk-8.6.10 | hed695b0_0 3.2 MB conda-forge
libgcc-ng-9.2.0 | h24d8f2e_2 8.2 MB conda-forge
libgomp-9.2.0 | h24d8f2e_2 816 KB conda-forge
ncurses-6.1 | hf484d3e_1002 1.3 MB conda-forge
sqlite-3.30.1 | hcee41ef_0 2.0 MB conda-forge
libstdcxx-ng-9.2.0 | hdf63c60_2 4.5 MB conda-forge
_libgcc_mutex-0.1 | conda_forge 3 KB conda-forge
pip-20.1.1 | py_1 1.1 MB conda-forge
_openmp_mutex-4.5 | 0_gnu 435 KB conda-forge
ca-certificates-2020.4.5.1 | hecc5488_0 146 KB conda-forge
python-3.6.10 |h8356626_1011_cpython 34.1 MB conda-forge
openssl-1.1.1g | h516909a_0 2.1 MB conda-forge
zlib-1.2.11 | h516909a_1006 105 KB conda-forge
libffi-3.2.1 | he1b5a44_1007 47 KB conda-forge
python_abi-3.6 | 1_cp36m 4 KB conda-forge
readline-8.0 | hf8c457e_0 441 KB conda-forge
wheel-0.34.2 | py_1 24 KB conda-forge
setuptools-47.1.1 | py36h9f0ad1d_0 642 KB conda-forge
xz-5.2.5 | h516909a_0 430 KB conda-forge
------------------------------------------------------------
Total: 60.2 MB
The following NEW packages will be INSTALLED:
_libgcc_mutex: 0.1-conda_forge conda-forge
_openmp_mutex: 4.5-0_gnu conda-forge
ld_impl_linux-64: 2.34-h53a641e_4 conda-forge
libgomp: 9.2.0-h24d8f2e_2 conda-forge
python_abi: 3.6-1_cp36m conda-forge
The following packages will be UPDATED:
ca-certificates: 2018.03.07-0 --> 2020.4.5.1-hecc5488_0 conda-forge
certifi: 2018.4.16-py36_0 --> 2020.4.5.1-py36h9f0ad1d_0 conda-forge
libffi: 3.2.1-hd88cf55_4 --> 3.2.1-he1b5a44_1007 conda-forge
libgcc-ng: 7.2.0-hdf63c60_3 --> 9.2.0-h24d8f2e_2 conda-forge
libstdcxx-ng: 7.2.0-hdf63c60_3 --> 9.2.0-hdf63c60_2 conda-forge
ncurses: 6.1-hf484d3e_0 --> 6.1-hf484d3e_1002 conda-forge
openssl: 1.0.2o-h20670df_0 --> 1.1.1g-h516909a_0 conda-forge
pip: 10.0.1-py36_0 --> 20.1.1-py_1 conda-forge
python: 3.6.5-hc3d631a_2 --> 3.6.10-h8356626_1011_cpython conda-forge
readline: 7.0-ha6073c6_4 --> 8.0-hf8c457e_0 conda-forge
setuptools: 39.2.0-py36_0 --> 47.1.1-py36h9f0ad1d_0 conda-forge
sqlite: 3.23.1-he433501_0 --> 3.30.1-hcee41ef_0 conda-forge
tk: 8.6.7-hc745277_3 --> 8.6.10-hed695b0_0 conda-forge
wheel: 0.31.1-py36_0 --> 0.34.2-py_1 conda-forge
xz: 5.2.4-h14c3975_4 --> 5.2.5-h516909a_0 conda-forge
zlib: 1.2.11-ha838bed_2 --> 1.2.11-h516909a_1006 conda-forge
Downloading and Extracting Packages
ld_impl_linux-64-2.3 | 616 KB | : 100% 1.0/1 [00:00<00:00, 5.22it/s]
certifi-2020.4.5.1 | 151 KB | : 100% 1.0/1 [00:00<00:00, 15.76it/s]
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Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Installing RAPIDS 0.13 packages from the stable release channel
Please standby, this will take a few minutes...
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.5.4
latest version: 4.8.3
Please update conda by running
$ conda update -n base conda
## Package Plan ##
environment location: /usr/local
added / updated specs:
- cudatoolkit=10.0
- cudf=0.13
- cugraph
- cuml
- cusignal
- cuspatial
- dask-cudf
- gcsfs
- pynvml
- python=3.6
- xgboost=1.0.2dev.rapidsai0.13
The following packages will be downloaded:
package | build
---------------------------|-----------------
sortedcontainers-2.1.0 | py_0 25 KB conda-forge
requests-2.23.0 | pyh8c360ce_2 47 KB conda-forge
gflags-2.2.2 | he1b5a44_1002 175 KB conda-forge
boost-cpp-1.70.0 | h8e57a91_2 21.1 MB conda-forge
distributed-2.17.0 | py36h9f0ad1d_0 1.0 MB conda-forge
pyarrow-0.15.0 | py36h8b68381_1 3.2 MB conda-forge
dask-core-2.17.2 | py_0 613 KB conda-forge
numpy-1.17.5 | py36h95a1406_0 5.2 MB conda-forge
psutil-5.7.0 | py36h8c4c3a4_1 324 KB conda-forge
xorg-renderproto-0.11.1 | h14c3975_1002 8 KB conda-forge
lz4-c-1.8.3 | he1b5a44_1001 187 KB conda-forge
xorg-libsm-1.2.3 | h84519dc_1000 25 KB conda-forge
nccl-2.5.7.1 | hd6f8bf8_0 96.6 MB conda-forge
cuml-0.13.0 | cuda10.0_py36_0 9.2 MB rapidsai/label/main
jpeg-9c | h14c3975_1001 251 KB conda-forge
freetype-2.10.2 | he06d7ca_0 905 KB conda-forge
typing_extensions-3.7.4.2 | py_0 25 KB conda-forge
pillow-7.1.2 | py36h8328e55_0 656 KB conda-forge
libhwloc-2.1.0 | h3c4fd83_0 2.7 MB conda-forge
boost-1.70.0 | py36h9de70de_1 337 KB conda-forge
pandas-0.25.3 | py36hb3f55d8_0 11.4 MB conda-forge
ucx-py-0.13.0+g9d06c3a | py36_0 287 KB rapidsai/label/main
thrift-cpp-0.12.0 | hf3afdfd_1004 2.4 MB conda-forge
xorg-xproto-7.0.31 | h14c3975_1007 72 KB conda-forge
libopenblas-0.3.7 | h5ec1e0e_6 7.6 MB conda-forge
parquet-cpp-1.5.1 | 2 3 KB conda-forge
libllvm8-8.0.1 | hc9558a2_0 23.2 MB conda-forge
pynvml-8.0.4 | py_0 31 KB conda-forge
freexl-1.0.5 | h14c3975_1002 43 KB conda-forge
olefile-0.46 | py_0 31 KB conda-forge
pyasn1-modules-0.2.7 | py_0 60 KB conda-forge
xorg-libxdmcp-1.1.3 | h516909a_0 18 KB conda-forge
contextvars-2.4 | py_0 11 KB conda-forge
nvstrings-0.13.0 | py36_0 129 KB rapidsai/label/main
brotli-1.0.7 | he1b5a44_1002 1.0 MB conda-forge
libxml2-2.9.10 | hee79883_0 1.3 MB conda-forge
cugraph-0.13.0 | py36_0 7.3 MB rapidsai/label/main
expat-2.2.9 | he1b5a44_2 191 KB conda-forge
xorg-libx11-1.6.9 | h516909a_0 918 KB conda-forge
fontconfig-2.13.1 | h86ecdb6_1001 340 KB conda-forge
double-conversion-3.1.5 | he1b5a44_2 85 KB conda-forge
icu-64.2 | he1b5a44_1 12.6 MB conda-forge
pcre-8.44 | he1b5a44_0 261 KB conda-forge
librmm-0.13.0 | cuda10.0_0 70 KB rapidsai/label/main
fastavro-0.23.4 | py36h8c4c3a4_0 415 KB conda-forge
fastrlock-0.4 |py36h831f99a_1001 32 KB conda-forge
toolz-0.10.0 | py_0 46 KB conda-forge
rsa-4.0 | py_0 27 KB conda-forge
libtiff-4.1.0 | hfc65ed5_0 595 KB conda-forge
cloudpickle-1.4.1 | py_0 24 KB conda-forge
libkml-1.3.0 | h4fcabce_1010 643 KB conda-forge
py-xgboost-1.0.2dev.rapidsai0.13| cuda10.0py36_6 100 KB rapidsai/label/main
llvmlite-0.32.0 | py36hfa65bc7_0 323 KB conda-forge
python-dateutil-2.8.1 | py_0 220 KB conda-forge
tornado-6.0.4 | py36h8c4c3a4_1 639 KB conda-forge
uriparser-0.9.3 | he1b5a44_1 49 KB conda-forge
cytoolz-0.10.1 | py36h516909a_0 431 KB conda-forge
pixman-0.38.0 | h516909a_1003 594 KB conda-forge
snappy-1.1.8 | he1b5a44_1 39 KB conda-forge
markupsafe-1.1.1 | py36h8c4c3a4_1 26 KB conda-forge
cusignal-0.13.0 | py36_0 67 KB rapidsai/label/main
hdf5-1.10.5 |nompi_h3c11f04_1104 3.1 MB conda-forge
libgdal-2.4.4 | h5439ffd_1 18.6 MB conda-forge
libcudf-0.13.0 | cuda10.0_0 136.5 MB rapidsai/label/main
libblas-3.8.0 | 14_openblas 10 KB conda-forge
json-c-0.13.1 | hbfbb72e_1002 76 KB conda-forge
geos-3.8.1 | he1b5a44_0 1.0 MB conda-forge
c-ares-1.15.0 | h516909a_1001 100 KB conda-forge
liblapack-3.8.0 | 14_openblas 10 KB conda-forge
cudatoolkit-10.0.130 | 0 380.0 MB nvidia
curl-7.69.1 | h33f0ec9_0 137 KB conda-forge
google-auth-oauthlib-0.4.1 | py_2 18 KB conda-forge
numba-0.49.1 | py36h830a2c2_0 3.5 MB conda-forge
libnvstrings-0.13.0 | cuda10.0_0 29.6 MB rapidsai/label/main
bzip2-1.0.8 | h516909a_2 396 KB conda-forge
scikit-learn-0.23.1 | py36h0e1014b_0 6.8 MB conda-forge
tzcode-2020a | h516909a_0 425 KB conda-forge
poppler-data-0.4.9 | 1 3.4 MB conda-forge
pyyaml-5.1.2 | py36h516909a_0 184 KB conda-forge
locket-0.2.0 | py_2 6 KB conda-forge
xorg-libxrender-0.9.10 | h516909a_1002 31 KB conda-forge
threadpoolctl-2.1.0 | pyh5ca1d4c_0 15 KB conda-forge
arrow-cpp-0.15.0 | py36h090bef1_2 18.1 MB conda-forge
blinker-1.4 | py_1 13 KB conda-forge
rmm-0.13.0 | py36_0 687 KB rapidsai/label/main
gettext-0.19.8.1 | hc5be6a0_1002 3.6 MB conda-forge
brotlipy-0.7.0 |py36h8c4c3a4_1000 346 KB conda-forge
grpc-cpp-1.23.0 | h18db393_0 4.5 MB conda-forge
partd-1.1.0 | py_0 17 KB conda-forge
xorg-libice-1.0.10 | h516909a_0 57 KB conda-forge
postgresql-12.2 | h8573dbc_1 5.0 MB conda-forge
urllib3-1.25.9 | py_0 92 KB conda-forge
cachetools-4.1.0 | py_1 12 KB conda-forge
cairo-1.16.0 | hcf35c78_1003 1.5 MB conda-forge
libpq-12.2 | h5513abc_1 2.6 MB conda-forge
scipy-1.4.1 | py36h2d22cac_3 18.9 MB conda-forge
libcuml-0.13.0 | cuda10.0_0 51.6 MB rapidsai/label/main
libdap4-3.20.6 | h1d1bd15_0 18.2 MB conda-forge
pyjwt-1.7.1 | py_0 17 KB conda-forge
dask-2.17.2 | py_0 4 KB conda-forge
openjpeg-2.3.1 | h981e76c_3 475 KB conda-forge
gcsfs-0.6.2 | py_0 19 KB conda-forge
tblib-1.6.0 | py_0 14 KB conda-forge
libcblas-3.8.0 | 14_openblas 10 KB conda-forge
oauthlib-3.0.1 | py_0 82 KB conda-forge
bokeh-2.0.1 | py36h9f0ad1d_0 6.8 MB conda-forge
libcuspatial-0.13.0 | cuda10.0_0 1.7 MB rapidsai/label/main
libprotobuf-3.8.0 | h8b12597_0 4.7 MB conda-forge
libevent-2.1.10 | h72c5cf5_0 1.3 MB conda-forge
cupy-7.5.0 | py36h273e724_0 18.1 MB conda-forge
libspatialite-4.3.0a | h2482549_1038 3.1 MB conda-forge
click-7.1.2 | pyh9f0ad1d_0 64 KB conda-forge
libnetcdf-4.7.4 |nompi_h9f9fd6a_101 1.3 MB conda-forge
libssh2-1.9.0 | hab1572f_2 298 KB conda-forge
cuspatial-0.13.0 | py36_0 1.7 MB rapidsai/label/main
xgboost-1.0.2dev.rapidsai0.13| cuda10.0py36_6 12 KB rapidsai/label/main
xorg-xextproto-7.3.0 | h14c3975_1002 27 KB conda-forge
re2-2020.04.01 | he1b5a44_0 438 KB conda-forge
joblib-0.15.1 | py_0 202 KB conda-forge
jinja2-2.11.2 | pyh9f0ad1d_0 93 KB conda-forge
geotiff-1.5.1 | h05acad5_10 279 KB conda-forge
proj-7.0.0 | h966b41f_4 3.7 MB conda-forge
pyopenssl-19.1.0 | py_1 47 KB conda-forge
glib-2.64.3 | h6f030ca_0 3.4 MB conda-forge
zict-2.0.0 | py_0 10 KB conda-forge
pthread-stubs-0.4 | h14c3975_1001 5 KB conda-forge
heapdict-1.0.1 | py_0 7 KB conda-forge
google-auth-1.14.3 | pyh9f0ad1d_0 54 KB conda-forge
krb5-1.17.1 | h2fd8d38_0 1.5 MB conda-forge
libcumlprims-0.13.0 | cuda10.0_0 3.3 MB nvidia
xorg-libxext-1.3.4 | h516909a_0 51 KB conda-forge
requests-oauthlib-1.2.0 | py_0 19 KB conda-forge
libuuid-2.32.1 | h14c3975_1000 26 KB conda-forge
giflib-5.2.1 | h516909a_2 80 KB conda-forge
xorg-libxau-1.0.9 | h14c3975_0 13 KB conda-forge
hdf4-4.2.13 | hf30be14_1003 964 KB conda-forge
ucx-1.7.0+g9d06c3a | cuda10.0_0 8.2 MB rapidsai/label/main
fsspec-0.6.3 | py_0 48 KB conda-forge
pyasn1-0.4.8 | py_0 53 KB conda-forge
zstd-1.4.3 | h3b9ef0a_0 935 KB conda-forge
libxgboost-1.0.2dev.rapidsai0.13| cuda10.0_6 21.9 MB rapidsai/label/main
xorg-kbproto-1.0.7 | h14c3975_1002 26 KB conda-forge
packaging-20.4 | pyh9f0ad1d_0 32 KB conda-forge
cudnn-7.6.0 | cuda10.0_0 216.6 MB nvidia
msgpack-python-1.0.0 | py36hdb11119_1 91 KB conda-forge
cudf-0.13.0 | py36_0 32.6 MB rapidsai/label/main
libgfortran-ng-7.5.0 | hdf63c60_6 1.7 MB conda-forge
dask-cudf-0.13.0 | py36_0 76 KB rapidsai/label/main
pytz-2020.1 | pyh9f0ad1d_0 227 KB conda-forge
libcugraph-0.13.0 | cuda10.0_0 40.0 MB rapidsai/label/main
pyparsing-2.4.7 | pyh9f0ad1d_0 60 KB conda-forge
cfitsio-3.470 | h3eac812_5 1.3 MB conda-forge
libpng-1.6.37 | hed695b0_1 308 KB conda-forge
kealib-1.4.13 | hec59c27_0 172 KB conda-forge
poppler-0.67.0 | h14e79db_8 8.9 MB conda-forge
cryptography-2.9.2 | py36h45558ae_0 613 KB conda-forge
dlpack-0.2 | he1b5a44_1 13 KB conda-forge
immutables-0.14 | py36h8c4c3a4_0 68 KB conda-forge
gdal-2.4.4 | py36hbb8311d_1 1.2 MB conda-forge
libxcb-1.13 | h14c3975_1002 396 KB conda-forge
glog-0.4.0 | h49b9bf7_3 104 KB conda-forge
decorator-4.4.2 | py_0 11 KB conda-forge
libiconv-1.15 | h516909a_1006 2.0 MB conda-forge
xerces-c-3.2.2 | h8412b87_1004 1.7 MB conda-forge
libcurl-7.69.1 | hf7181ac_0 573 KB conda-forge
------------------------------------------------------------
Total: 1.29 GB
The following NEW packages will be INSTALLED:
arrow-cpp: 0.15.0-py36h090bef1_2 conda-forge
blinker: 1.4-py_1 conda-forge
bokeh: 2.0.1-py36h9f0ad1d_0 conda-forge
boost: 1.70.0-py36h9de70de_1 conda-forge
boost-cpp: 1.70.0-h8e57a91_2 conda-forge
brotli: 1.0.7-he1b5a44_1002 conda-forge
brotlipy: 0.7.0-py36h8c4c3a4_1000 conda-forge
bzip2: 1.0.8-h516909a_2 conda-forge
c-ares: 1.15.0-h516909a_1001 conda-forge
cachetools: 4.1.0-py_1 conda-forge
cairo: 1.16.0-hcf35c78_1003 conda-forge
cfitsio: 3.470-h3eac812_5 conda-forge
click: 7.1.2-pyh9f0ad1d_0 conda-forge
cloudpickle: 1.4.1-py_0 conda-forge
contextvars: 2.4-py_0 conda-forge
cudatoolkit: 10.0.130-0 nvidia
cudf: 0.13.0-py36_0 rapidsai/label/main
cudnn: 7.6.0-cuda10.0_0 nvidia
cugraph: 0.13.0-py36_0 rapidsai/label/main
cuml: 0.13.0-cuda10.0_py36_0 rapidsai/label/main
cupy: 7.5.0-py36h273e724_0 conda-forge
curl: 7.69.1-h33f0ec9_0 conda-forge
cusignal: 0.13.0-py36_0 rapidsai/label/main
cuspatial: 0.13.0-py36_0 rapidsai/label/main
cytoolz: 0.10.1-py36h516909a_0 conda-forge
dask: 2.17.2-py_0 conda-forge
dask-core: 2.17.2-py_0 conda-forge
dask-cudf: 0.13.0-py36_0 rapidsai/label/main
decorator: 4.4.2-py_0 conda-forge
distributed: 2.17.0-py36h9f0ad1d_0 conda-forge
dlpack: 0.2-he1b5a44_1 conda-forge
double-conversion: 3.1.5-he1b5a44_2 conda-forge
expat: 2.2.9-he1b5a44_2 conda-forge
fastavro: 0.23.4-py36h8c4c3a4_0 conda-forge
fastrlock: 0.4-py36h831f99a_1001 conda-forge
fontconfig: 2.13.1-h86ecdb6_1001 conda-forge
freetype: 2.10.2-he06d7ca_0 conda-forge
freexl: 1.0.5-h14c3975_1002 conda-forge
fsspec: 0.6.3-py_0 conda-forge
gcsfs: 0.6.2-py_0 conda-forge
gdal: 2.4.4-py36hbb8311d_1 conda-forge
geos: 3.8.1-he1b5a44_0 conda-forge
geotiff: 1.5.1-h05acad5_10 conda-forge
gettext: 0.19.8.1-hc5be6a0_1002 conda-forge
gflags: 2.2.2-he1b5a44_1002 conda-forge
giflib: 5.2.1-h516909a_2 conda-forge
glib: 2.64.3-h6f030ca_0 conda-forge
glog: 0.4.0-h49b9bf7_3 conda-forge
google-auth: 1.14.3-pyh9f0ad1d_0 conda-forge
google-auth-oauthlib: 0.4.1-py_2 conda-forge
grpc-cpp: 1.23.0-h18db393_0 conda-forge
hdf4: 4.2.13-hf30be14_1003 conda-forge
hdf5: 1.10.5-nompi_h3c11f04_1104 conda-forge
heapdict: 1.0.1-py_0 conda-forge
icu: 64.2-he1b5a44_1 conda-forge
immutables: 0.14-py36h8c4c3a4_0 conda-forge
jinja2: 2.11.2-pyh9f0ad1d_0 conda-forge
joblib: 0.15.1-py_0 conda-forge
jpeg: 9c-h14c3975_1001 conda-forge
json-c: 0.13.1-hbfbb72e_1002 conda-forge
kealib: 1.4.13-hec59c27_0 conda-forge
krb5: 1.17.1-h2fd8d38_0 conda-forge
libblas: 3.8.0-14_openblas conda-forge
libcblas: 3.8.0-14_openblas conda-forge
libcudf: 0.13.0-cuda10.0_0 rapidsai/label/main
libcugraph: 0.13.0-cuda10.0_0 rapidsai/label/main
libcuml: 0.13.0-cuda10.0_0 rapidsai/label/main
libcumlprims: 0.13.0-cuda10.0_0 nvidia
libcurl: 7.69.1-hf7181ac_0 conda-forge
libcuspatial: 0.13.0-cuda10.0_0 rapidsai/label/main
libdap4: 3.20.6-h1d1bd15_0 conda-forge
libevent: 2.1.10-h72c5cf5_0 conda-forge
libgdal: 2.4.4-h5439ffd_1 conda-forge
libgfortran-ng: 7.5.0-hdf63c60_6 conda-forge
libhwloc: 2.1.0-h3c4fd83_0 conda-forge
libiconv: 1.15-h516909a_1006 conda-forge
libkml: 1.3.0-h4fcabce_1010 conda-forge
liblapack: 3.8.0-14_openblas conda-forge
libllvm8: 8.0.1-hc9558a2_0 conda-forge
libnetcdf: 4.7.4-nompi_h9f9fd6a_101 conda-forge
libnvstrings: 0.13.0-cuda10.0_0 rapidsai/label/main
libopenblas: 0.3.7-h5ec1e0e_6 conda-forge
libpng: 1.6.37-hed695b0_1 conda-forge
libpq: 12.2-h5513abc_1 conda-forge
libprotobuf: 3.8.0-h8b12597_0 conda-forge
librmm: 0.13.0-cuda10.0_0 rapidsai/label/main
libspatialite: 4.3.0a-h2482549_1038 conda-forge
libssh2: 1.9.0-hab1572f_2 conda-forge
libtiff: 4.1.0-hfc65ed5_0 conda-forge
libuuid: 2.32.1-h14c3975_1000 conda-forge
libxcb: 1.13-h14c3975_1002 conda-forge
libxgboost: 1.0.2dev.rapidsai0.13-cuda10.0_6 rapidsai/label/main
libxml2: 2.9.10-hee79883_0 conda-forge
llvmlite: 0.32.0-py36hfa65bc7_0 conda-forge
locket: 0.2.0-py_2 conda-forge
lz4-c: 1.8.3-he1b5a44_1001 conda-forge
markupsafe: 1.1.1-py36h8c4c3a4_1 conda-forge
msgpack-python: 1.0.0-py36hdb11119_1 conda-forge
nccl: 2.5.7.1-hd6f8bf8_0 conda-forge
numba: 0.49.1-py36h830a2c2_0 conda-forge
numpy: 1.17.5-py36h95a1406_0 conda-forge
nvstrings: 0.13.0-py36_0 rapidsai/label/main
oauthlib: 3.0.1-py_0 conda-forge
olefile: 0.46-py_0 conda-forge
openjpeg: 2.3.1-h981e76c_3 conda-forge
packaging: 20.4-pyh9f0ad1d_0 conda-forge
pandas: 0.25.3-py36hb3f55d8_0 conda-forge
parquet-cpp: 1.5.1-2 conda-forge
partd: 1.1.0-py_0 conda-forge
pcre: 8.44-he1b5a44_0 conda-forge
pillow: 7.1.2-py36h8328e55_0 conda-forge
pixman: 0.38.0-h516909a_1003 conda-forge
poppler: 0.67.0-h14e79db_8 conda-forge
poppler-data: 0.4.9-1 conda-forge
postgresql: 12.2-h8573dbc_1 conda-forge
proj: 7.0.0-h966b41f_4 conda-forge
psutil: 5.7.0-py36h8c4c3a4_1 conda-forge
pthread-stubs: 0.4-h14c3975_1001 conda-forge
py-xgboost: 1.0.2dev.rapidsai0.13-cuda10.0py36_6 rapidsai/label/main
pyarrow: 0.15.0-py36h8b68381_1 conda-forge
pyasn1: 0.4.8-py_0 conda-forge
pyasn1-modules: 0.2.7-py_0 conda-forge
pyjwt: 1.7.1-py_0 conda-forge
pynvml: 8.0.4-py_0 conda-forge
pyparsing: 2.4.7-pyh9f0ad1d_0 conda-forge
python-dateutil: 2.8.1-py_0 conda-forge
pytz: 2020.1-pyh9f0ad1d_0 conda-forge
pyyaml: 5.1.2-py36h516909a_0 conda-forge
re2: 2020.04.01-he1b5a44_0 conda-forge
requests-oauthlib: 1.2.0-py_0 conda-forge
rmm: 0.13.0-py36_0 rapidsai/label/main
rsa: 4.0-py_0 conda-forge
scikit-learn: 0.23.1-py36h0e1014b_0 conda-forge
scipy: 1.4.1-py36h2d22cac_3 conda-forge
snappy: 1.1.8-he1b5a44_1 conda-forge
sortedcontainers: 2.1.0-py_0 conda-forge
tblib: 1.6.0-py_0 conda-forge
threadpoolctl: 2.1.0-pyh5ca1d4c_0 conda-forge
thrift-cpp: 0.12.0-hf3afdfd_1004 conda-forge
toolz: 0.10.0-py_0 conda-forge
tornado: 6.0.4-py36h8c4c3a4_1 conda-forge
typing_extensions: 3.7.4.2-py_0 conda-forge
tzcode: 2020a-h516909a_0 conda-forge
ucx: 1.7.0+g9d06c3a-cuda10.0_0 rapidsai/label/main
ucx-py: 0.13.0+g9d06c3a-py36_0 rapidsai/label/main
uriparser: 0.9.3-he1b5a44_1 conda-forge
xerces-c: 3.2.2-h8412b87_1004 conda-forge
xgboost: 1.0.2dev.rapidsai0.13-cuda10.0py36_6 rapidsai/label/main
xorg-kbproto: 1.0.7-h14c3975_1002 conda-forge
xorg-libice: 1.0.10-h516909a_0 conda-forge
xorg-libsm: 1.2.3-h84519dc_1000 conda-forge
xorg-libx11: 1.6.9-h516909a_0 conda-forge
xorg-libxau: 1.0.9-h14c3975_0 conda-forge
xorg-libxdmcp: 1.1.3-h516909a_0 conda-forge
xorg-libxext: 1.3.4-h516909a_0 conda-forge
xorg-libxrender: 0.9.10-h516909a_1002 conda-forge
xorg-renderproto: 0.11.1-h14c3975_1002 conda-forge
xorg-xextproto: 7.3.0-h14c3975_1002 conda-forge
xorg-xproto: 7.0.31-h14c3975_1007 conda-forge
zict: 2.0.0-py_0 conda-forge
zstd: 1.4.3-h3b9ef0a_0 conda-forge
The following packages will be UPDATED:
cryptography: 2.2.2-py36h14c3975_0 --> 2.9.2-py36h45558ae_0 conda-forge
pyopenssl: 18.0.0-py36_0 --> 19.1.0-py_1 conda-forge
requests: 2.18.4-py36he2e5f8d_1 --> 2.23.0-pyh8c360ce_2 conda-forge
urllib3: 1.22-py36hbe7ace6_0 --> 1.25.9-py_0 conda-forge
Downloading and Extracting Packages
sortedcontainers-2.1 | 25 KB | : 100% 1.0/1 [00:00<00:00, 8.29it/s]
requests-2.23.0 | 47 KB | : 100% 1.0/1 [00:00<00:00, 20.18it/s]
gflags-2.2.2 | 175 KB | : 100% 1.0/1 [00:00<00:00, 10.03it/s]
boost-cpp-1.70.0 | 21.1 MB | : 100% 1.0/1 [00:12<00:00, 12.98s/it]
distributed-2.17.0 | 1.0 MB | : 100% 1.0/1 [00:00<00:00, 2.06it/s]
pyarrow-0.15.0 | 3.2 MB | : 100% 1.0/1 [00:01<00:00, 1.28s/it]
dask-core-2.17.2 | 613 KB | : 100% 1.0/1 [00:00<00:00, 3.25it/s]
numpy-1.17.5 | 5.2 MB | : 100% 1.0/1 [00:01<00:00, 1.60s/it]
psutil-5.7.0 | 324 KB | : 100% 1.0/1 [00:00<00:00, 6.66it/s]
xorg-renderproto-0.1 | 8 KB | : 100% 1.0/1 [00:00<00:00, 25.85it/s]
lz4-c-1.8.3 | 187 KB | : 100% 1.0/1 [00:00<00:00, 10.63it/s]
xorg-libsm-1.2.3 | 25 KB | : 100% 1.0/1 [00:00<00:00, 25.13it/s]
nccl-2.5.7.1 | 96.6 MB | : 100% 1.0/1 [00:14<00:00, 14.34s/it]
cuml-0.13.0 | 9.2 MB | : 100% 1.0/1 [00:03<00:00, 3.83s/it]
jpeg-9c | 251 KB | : 100% 1.0/1 [00:00<00:00, 10.18it/s]
freetype-2.10.2 | 905 KB | : 100% 1.0/1 [00:00<00:00, 4.25it/s]
typing_extensions-3. | 25 KB | : 100% 1.0/1 [00:00<00:00, 28.36it/s]
pillow-7.1.2 | 656 KB | : 100% 1.0/1 [00:00<00:00, 4.66it/s]
libhwloc-2.1.0 | 2.7 MB | : 100% 1.0/1 [00:00<00:00, 1.83it/s]
boost-1.70.0 | 337 KB | : 100% 1.0/1 [00:00<00:00, 4.47it/s]
pandas-0.25.3 | 11.4 MB | : 100% 1.0/1 [00:03<00:00, 3.63s/it]
ucx-py-0.13.0+g9d06c | 287 KB | : 100% 1.0/1 [00:01<00:00, 1.41s/it]
thrift-cpp-0.12.0 | 2.4 MB | : 100% 1.0/1 [00:00<00:00, 1.73it/s]
xorg-xproto-7.0.31 | 72 KB | : 100% 1.0/1 [00:00<00:00, 16.14it/s]
libopenblas-0.3.7 | 7.6 MB | : 100% 1.0/1 [00:01<00:00, 1.68s/it]
parquet-cpp-1.5.1 | 3 KB | : 100% 1.0/1 [00:00<00:00, 31.59it/s]
libllvm8-8.0.1 | 23.2 MB | : 100% 1.0/1 [00:04<00:00, 4.70s/it]
pynvml-8.0.4 | 31 KB | : 100% 1.0/1 [00:00<00:00, 22.53it/s]
freexl-1.0.5 | 43 KB | : 100% 1.0/1 [00:00<00:00, 23.50it/s]
olefile-0.46 | 31 KB | : 100% 1.0/1 [00:00<00:00, 19.80it/s]
pyasn1-modules-0.2.7 | 60 KB | : 100% 1.0/1 [00:00<00:00, 11.66it/s]
xorg-libxdmcp-1.1.3 | 18 KB | : 100% 1.0/1 [00:00<00:00, 26.87it/s]
contextvars-2.4 | 11 KB | : 100% 1.0/1 [00:00<00:00, 25.40it/s]
nvstrings-0.13.0 | 129 KB | : 100% 1.0/1 [00:01<00:00, 5.54s/it]
brotli-1.0.7 | 1.0 MB | : 100% 1.0/1 [00:00<00:00, 4.57it/s]
libxml2-2.9.10 | 1.3 MB | : 100% 1.0/1 [00:00<00:00, 1.97it/s]
cugraph-0.13.0 | 7.3 MB | : 100% 1.0/1 [00:02<00:00, 2.26s/it]
expat-2.2.9 | 191 KB | : 100% 1.0/1 [00:00<00:00, 13.42it/s]
xorg-libx11-1.6.9 | 918 KB | : 100% 1.0/1 [00:00<00:00, 3.52it/s]
fontconfig-2.13.1 | 340 KB | : 100% 1.0/1 [00:00<00:00, 7.31it/s]
double-conversion-3. | 85 KB | : 100% 1.0/1 [00:00<00:00, 16.39it/s]
icu-64.2 | 12.6 MB | : 100% 1.0/1 [00:02<00:00, 2.42s/it]
pcre-8.44 | 261 KB | : 100% 1.0/1 [00:00<00:00, 11.27it/s]
librmm-0.13.0 | 70 KB | : 100% 1.0/1 [00:00<00:00, 1.24it/s]
fastavro-0.23.4 | 415 KB | : 100% 1.0/1 [00:00<00:00, 7.36it/s]
fastrlock-0.4 | 32 KB | : 100% 1.0/1 [00:00<00:00, 26.87it/s]
toolz-0.10.0 | 46 KB | : 100% 1.0/1 [00:00<00:00, 19.76it/s]
rsa-4.0 | 27 KB | : 100% 1.0/1 [00:00<00:00, 20.46it/s]
libtiff-4.1.0 | 595 KB | : 100% 1.0/1 [00:00<00:00, 6.06it/s]
cloudpickle-1.4.1 | 24 KB | : 100% 1.0/1 [00:00<00:00, 23.40it/s]
libkml-1.3.0 | 643 KB | : 100% 1.0/1 [00:00<00:00, 4.10it/s]
py-xgboost-1.0.2dev. | 100 KB | : 100% 1.0/1 [00:00<00:00, 2.70it/s]
llvmlite-0.32.0 | 323 KB | : 100% 1.0/1 [00:00<00:00, 7.34it/s]
python-dateutil-2.8. | 220 KB | : 100% 1.0/1 [00:00<00:00, 13.63it/s]
tornado-6.0.4 | 639 KB | : 100% 1.0/1 [00:00<00:00, 3.43it/s]
uriparser-0.9.3 | 49 KB | : 100% 1.0/1 [00:00<00:00, 23.09it/s]
cytoolz-0.10.1 | 431 KB | : 100% 1.0/1 [00:00<00:00, 6.53it/s]
pixman-0.38.0 | 594 KB | : 100% 1.0/1 [00:00<00:00, 6.14it/s]
snappy-1.1.8 | 39 KB | : 100% 1.0/1 [00:00<00:00, 22.74it/s]
markupsafe-1.1.1 | 26 KB | : 100% 1.0/1 [00:00<00:00, 26.04it/s]
cusignal-0.13.0 | 67 KB | : 100% 1.0/1 [00:00<00:00, 1.21it/s]
hdf5-1.10.5 | 3.1 MB | : 100% 1.0/1 [00:00<00:00, 1.42it/s]
libgdal-2.4.4 | 18.6 MB | : 100% 1.0/1 [00:04<00:00, 4.17s/it]
libcudf-0.13.0 | 136.5 MB | : 100% 1.0/1 [00:43<00:00, 43.20s/it]
libblas-3.8.0 | 10 KB | : 100% 1.0/1 [00:00<00:00, 24.98it/s]
json-c-0.13.1 | 76 KB | : 100% 1.0/1 [00:00<00:00, 16.50it/s]
geos-3.8.1 | 1.0 MB | : 100% 1.0/1 [00:00<00:00, 2.12it/s]
c-ares-1.15.0 | 100 KB | : 100% 1.0/1 [00:00<00:00, 15.47it/s]
liblapack-3.8.0 | 10 KB | : 100% 1.0/1 [00:00<00:00, 26.94it/s]
cudatoolkit-10.0.130 | 380.0 MB | : 100% 1.0/1 [01:09<00:00, 69.79s/it]
curl-7.69.1 | 137 KB | : 100% 1.0/1 [00:00<00:00, 17.88it/s]
google-auth-oauthlib | 18 KB | : 100% 1.0/1 [00:00<00:00, 24.75it/s]
numba-0.49.1 | 3.5 MB | : 100% 1.0/1 [00:01<00:00, 1.53s/it]
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Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Copying shared object files to /usr/lib
Copying RAPIDS compatible xgboost
************************************************
Your Google Colab instance has RAPIDS installed!
************************************************
***********************************************************************
Let us check on those pyarrow and cffi versions...
***********************************************************************
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
unloaded pyarrow 0.14.1
loaded pyarrow 0.15.0
You're now running pyarrow 0.15.0 and are good to go!
unloaded cffi 1.14.0
loaded cffi 1.11.5
drscotthawley
All 9 comments
According to minimum requirements describe at https://rapids.ai/start.html it should be
CUDA & NVIDIA Drivers: One of the following supported versions:
10.0 & v410.48+ 10.1.2 & v418.87+ 10.2 & v440.33+
But driver on Google Colab has version Driver Version: 418.67 CUDA Version: 10.1
Ahwar
on 3 Jun 2020
👍1
@Ahwar that is true, there is a minor mismatch of the driver version, but that shouldn't cause an issue with cuDF's Python code AFAIK, so it wouldn't be the cause of this issue.
@drscotthawley I would recommend cross posting this issue in the cuDF repository since more people might be able to help with this particular error over there https://github.com/rapidsai/cudf.
dantegd
on 3 Jun 2020
Found this too on an independent investigation and was checking for solutions. I'll reopen this on cudf and escalate. _lib is there, but not getting picked up in import
taureandyernv
on 3 Jun 2020
Sounds like this notebook is just outdated and needs to be updated based on the massive refactor that landed in cudf.
kkraus14
on 3 Jun 2020
@kkraus14 i was slacking you when i googled and found this issue. Its affecting 0.13 stable once you fix importing six for numba. This wasn't happening a week ago.
taureandyernv
on 3 Jun 2020
this is not a cudf error. Local install works fine. I'll make an issue in rapidsai/rapidsai-csp-utils
@drscotthawley I'm sorry for the inconvenience. I maintain the RAPIDS-Colab code. I found this while solving another bug. If your workload is just cudf and cuml, please try app.blazingsql.com. The current length of the RAPIDS installation is a colab issue due to ever worsening situation when needing to force their system to install conda and rapids from scratch on a system that didn't initially support it. If in the future you hit a colab snag, please make your issues here: https://github.com/rapidsai/rapidsai-csp-utils. :). thanks so much!
taureandyernv
on 3 Jun 2020
@taureandyernv Thanks for getting back to me.
Feel free to close.... And/yet I'd love to get a notice somehow of when it's ok to try on Colab again.
Regarding app.blazingsql.com: After I log in via Google, all I see is a JupyterHub logo and
"400 : Bad Request
OAuth state missing from cookies"
...that was with Brave browser and shields down. With Chrome it's:
"500 : Internal Server Error"
drscotthawley
on 3 Jun 2020
I tried that colab code with version 0.11, 0.12 and 0.13. Every version has same problem.
That is why I am also convinced that this issue is only on Google Colab. It perfectly works on app.blazingsql.com.
Thanks @taureandyernv! for telling about app.blazingsql.com.It really helped me a lot. I used cuML for the first time and it is amazingly fast.
@drscotthawley! I also faced the same OAuth state missing from cookies error. you will have to first sign up with google, load the page and then login.
Ahwar
on 4 Jun 2020
@Ahwar thanks, I thought I did that last night but... Well, today it's working (on blazingsqlcom)! So, I'm able to run the welcome notebook there and everything runs to completion. Great.
drscotthawley
on 4 Jun 2020
👍1
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