Compatibility with Cuda 10.1? #26289

jiapei100 · 2019-03-03T03:52:33Z

Just wanna compile tensorflow 1.12 against Cuda 10.1 ?

➜  tensorflow git:(master) bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
Starting local Bazel server and connecting to it...
WARNING: The following configs were expanded more than once: [cuda]. For repeatable flags, repeats are counted twice and may lead to unexpected behavior.
DEBUG: Rule 'build_bazel_rules_swift' modified arguments {"commit": "001736d056d7eae20f1f4da41bc9e6f036857296", "shallow_since": "1547844730 -0800"} and dropped ["tag"]
DEBUG: ~/.cache/bazel/_bazel_user/15086820fc7a6f1383d8c38c62220208/external/build_bazel_rules_apple/apple/repositories.bzl:35:5: 
WARNING: `build_bazel_rules_apple` depends on `bazel_skylib` loaded from https://github.com/bazelbuild/bazel-skylib.git (tag 0.6.0), but we have detected it already loaded into your workspace from None (tag None). You may run into compatibility issues. To silence this warning, pass `ignore_version_differences = True` to `apple_rules_dependencies()`.

ERROR: Skipping '//tensorflow/tools/pip_package:build_pip_package': error loading package 'tensorflow/tools/pip_package': in ....../tensorflow/tensorflow.bzl: Encountered error while reading extension file 'cuda/build_defs.bzl': no such package '@local_config_cuda//cuda': Traceback (most recent call last):
        File "....../third_party/gpus/cuda_configure.bzl", line 1501
                _create_local_cuda_repository(repository_ctx)
        File "....../third_party/gpus/cuda_configure.bzl", line 1266, in _create_local_cuda_repository
                _find_libs(repository_ctx, cuda_config)
        File "....../third_party/gpus/cuda_configure.bzl", line 859, in _find_libs
                _find_cuda_lib("cublas", repository_ctx, cpu_value, c..., ...)
        File "....../third_party/gpus/cuda_configure.bzl", line 773, in _find_cuda_lib
                find_lib(repository_ctx, [("%s/%s%s" % (bas...], ...)))
        File "....../third_party/gpus/cuda_configure.bzl", line 750, in find_lib
                auto_configure_fail(("No library found under: " + ",...)))
        File "....../third_party/gpus/cuda_configure.bzl", line 341, in auto_configure_fail
                fail(("\n%sCuda Configuration Error:%...)))

Cuda Configuration Error: No library found under: /usr/local/cuda-10.1/lib64/libcublas.so.10.1, /usr/local/cuda-10.1/lib64/stubs/libcublas.so.10.1, /usr/local/cuda-10.1/lib/powerpc64le-linux-gnu/libcublas.so.10.1, /usr/local/cuda-10.1/lib/x86_64-linux-gnu/libcublas.so.10.1, /usr/local/cuda-10.1/lib/x64/libcublas.so.10.1, /usr/local/cuda-10.1/lib/libcublas.so.10.1, /usr/local/cuda-10.1/libcublas.so.10.1
WARNING: Target pattern parsing failed.
ERROR: error loading package 'tensorflow/tools/pip_package': in ....../tensorflow/tensorflow.bzl: Encountered error while reading extension file 'cuda/build_defs.bzl': no such package '@local_config_cuda//cuda': Traceback (most recent call last):
        File "....../third_party/gpus/cuda_configure.bzl", line 1501
                _create_local_cuda_repository(repository_ctx)
        File "....../third_party/gpus/cuda_configure.bzl", line 1266, in _create_local_cuda_repository
                _find_libs(repository_ctx, cuda_config)
        File "....../third_party/gpus/cuda_configure.bzl", line 859, in _find_libs
                _find_cuda_lib("cublas", repository_ctx, cpu_value, c..., ...)
        File "....../third_party/gpus/cuda_configure.bzl", line 773, in _find_cuda_lib
                find_lib(repository_ctx, [("%s/%s%s" % (bas...], ...)))
        File "....../third_party/gpus/cuda_configure.bzl", line 750, in find_lib
                auto_configure_fail(("No library found under: " + ",...)))
        File "....../third_party/gpus/cuda_configure.bzl", line 341, in auto_configure_fail
                fail(("\n%sCuda Configuration Error:%...)))

Cuda Configuration Error: No library found under: /usr/local/cuda-10.1/lib64/libcublas.so.10.1, /usr/local/cuda-10.1/lib64/stubs/libcublas.so.10.1, /usr/local/cuda-10.1/lib/powerpc64le-linux-gnu/libcublas.so.10.1, /usr/local/cuda-10.1/lib/x86_64-linux-gnu/libcublas.so.10.1, /usr/local/cuda-10.1/lib/x64/libcublas.so.10.1, /usr/local/cuda-10.1/lib/libcublas.so.10.1, /usr/local/cuda-10.1/libcublas.so.10.1
INFO: Elapsed time: 10.828s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (0 packages loaded)
    currently loading: tensorflow/tools/pip_package
    Fetching @local_config_cuda; fetching

Any suggestions?

The text was updated successfully, but these errors were encountered:

jvishnuvardhan · 2019-03-03T16:39:34Z

@jiapei100 For Faster resolutions, Please provide the details requested at issue template here.

Please check tested build configurations here. Tensorflow 1.12 was built with CUDA9.0. So when you install some of the paths in different modules are looking for CUDA9.0. If you want to use CUDA10 or CUDA 10.1, use latest version of TF and check whether CUDA and cuDNN are referencing correct paths. First, uninstall python and tensorflow and reinstall following the instructions here but use new version of CUDA and cuDNN. Please let me know how it progresses. Thanks!

wjcskqygj2015 · 2019-03-05T01:52:31Z

Since based on cublas issues and cublas new features. the cublas is in the seperate directory and therefore you may could use soft link to temporarily fix it.

devillove084 · 2019-03-05T04:01:10Z

I meet the same problem about cublas. Path /usr/local/cuda/lib64, does not include cublas library.

devillove084 · 2019-03-05T04:09:56Z

So, how to modify the code and complie the path for CUDA 10.1.

beew · 2019-03-17T00:09:55Z

@wjcskqygj2015

Symlinking doesn't work, try build tensorflow master

ERROR: Skipping '//tensorflow/tools/pip_package:build_pip_package': error loading package 'tensorflow/tools/pip_package': in /home/bernard/opt/cuda_test/tensorflow/tensorflow/tensorflow.bzl: Encountered error while reading extension file 'cuda/build_defs.bzl': no such package '@local_config_cuda//cuda': Traceback (most recent call last):
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 1502
		_create_local_cuda_repository(repository_ctx)
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 1266, in _create_local_cuda_repository
		_find_libs(repository_ctx, cuda_config)
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 859, in _find_libs
		_find_cuda_lib("cublas", repository_ctx, cpu_value, c..., ...)
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 773, in _find_cuda_lib
		find_lib(repository_ctx, [("%s/%s%s" % (bas...], ...)))
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 747, in find_lib
		auto_configure_fail(("None of the libraries match th...)))
	File "/home/bernard/opt/cuda_test/tensorflow/third_party/gpus/cuda_configure.bzl", line 341, in auto_configure_fail
		fail(("\n%sCuda Configuration Error:%...)))

Cuda Configuration Error: None of the libraries match their SONAME: /home/bernard/opt/cuda_test/cuda/lib64/libcublas.so.10.1

Besides, all libcu***.so.10.1 are missing, not just libcublas, it is a pain to have to create symlink for all these even if symlinking works.

madeye-matt · 2019-03-18T09:51:00Z

I have the same problem using tensorflow 1.13.1 and CUDA 10.1. Use of symlinks 'worked' for me in so far as there were no path errors - however attempting to run the tensorflow sanity check results in a core dump, presumably as there are genuine incompatabilities between those versions of tensorflow and CUDA

(venv) ➜  tensorflow python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
python: Relink `/lib64/libmount.so.1' with `/lib64/librt.so.1' for IFUNC symbol `clock_gettime'
python: Relink `/lib64/libsystemd.so.0' with `/lib64/librt.so.1' for IFUNC symbol `clock_gettime'
[1]    24472 segmentation fault (core dumped)  python -c

EDIT: the following link commands fixed the path errors

sudo ln -s /usr/local/cuda-10.1/targets/x86_64-linux/lib/libcublas.so.10.1.0.105 /usr/lib64/libcublas.so.10.0
sudo ln -s /usr/local/cuda-10.1/targets/x86_64-linux/lib/libcusolver.so.10.1.105 /usr/lib64/libcusolver.so.10.0 
sudo ln -s /usr/local/cuda-10.1/targets/x86_64-linux/lib/libcudart.so.10.1.105 /usr/lib64/libcudart.so.10.0

wjcskqygj2015 · 2019-03-29T03:04:14Z

@beew
It seems mainly because the SONAME is incompatible for some library in cuda
I just modify the third_party/gpus/cuda_configure.bzl at line 871, 878, 885, 892, 907
replace cuda_config.cuda_version, with "10",
then using symlinks it works, I hope it will help you

plopresti · 2019-04-09T23:06:28Z

If you are heading down this particular rabbit hole, you will find #26155 relevant.

prassanna-ravishankar · 2019-04-23T19:56:14Z

Interestingly, got it working on windows, with an unsupported compiler - #28086

kgizdov · 2019-04-23T23:12:47Z

This is due to conflicting behaviour at configure/build time and run time. Have a look at the patch in #28093 for a temporary workaround.

gunan · 2019-05-11T00:10:25Z

@chsigg @annarev has done a lot on this. I think we are compatible now.

lfaino · 2019-05-13T08:14:50Z

Dear
i`m trying to install tensorflow using an Nvidia 1070, CUDA 10.1, cudnn7.5.1.10 on Ubuntu 18.04.
the nvidia drivers are NVIDIA-SMI 418.40.04 Driver Version: 418.40.04 CUDA Version: 10.1 (this comes from nvidia-smi).

I install tensorflow-gpu using pip3.

the error that i get when i run:
python3 -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
is the following

File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/usr/lib/python3.6/imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.6/imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: libcublas.so.10.0: cannot open shared object file: No such file or directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.6/dist-packages/tensorflow/init.py", line 24, in
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/usr/lib/python3.6/imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.6/imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: libcublas.so.10.0: cannot open shared object file: No such file or directory

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.

can you please help me?

Cheers
Luigi

chsigg · 2019-05-13T10:33:05Z

If you want to use TensorFlow with CUDA 10.1, you currently need to build it from source. The binaries we ship are built for CUDA 10.0.

ymodak · 2019-05-15T20:41:28Z

If you want to use TensorFlow with CUDA 10.1, you currently need to build it from source. The binaries we ship are built for CUDA 10.0.

Closing this issue since chsigg's explanation addresses the issue. Feel free to reopen if have any further questions. Thanks!

leimao · 2019-06-11T22:57:53Z

chsigg's suggestion is not helpful. Most of us are building from source.

leimao · 2019-06-11T22:59:27Z

Please re-open this issue.

leimao · 2019-06-12T01:07:43Z

tensorflow/lite/delegates/nnapi/nnapi_delegate.cc: In static member function 'static void tflite::StatefulNnApiDelegate::DoFreeBufferHandle(TfLiteContext*, TfLiteDelegate*, TfLiteBufferHandle*)':
tensorflow/lite/delegates/nnapi/nnapi_delegate.cc:2136:31: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   if (*handle >= 0 && *handle < delegate_data->tensor_memory_map.size()) {
                       ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ERROR: /home/leimao/.cache/bazel/_bazel_leimao/b5222491e5f5e6954d481a492cdf3412/external/nccl_archive/BUILD.bazel:54:1: undeclared inclusion(s) in rule '@nccl_archive//:device_lib':
this rule is missing dependency declarations for the following files included by 'external/nccl_archive/src/collectives/device/functions.cu.cc':
  'external/nccl_archive/src/collectives/device/common.h'
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 101.561s, Critical Path: 19.52s
INFO: 513 processes: 513 local.
FAILED: Build did NOT complete successfully

chsigg · 2019-06-12T15:12:16Z

The error you are seeing is an unrelated bug that will be fixed shortly. Or you can use a commit from 2 days ago for now.

…

On Wed, Jun 12, 2019, 03:16 Lei Mao ***@***.***> wrote: ` tensorflow/lite/delegates/nnapi/nnapi_delegate.cc: In static member function 'static void tflite::StatefulNnApiDelegate::DoFreeBufferHandle(TfLiteContext*, TfLiteDelegate*, TfLiteBufferHandle*)': tensorflow/lite/delegates/nnapi/nnapi_delegate.cc:2136:31: warning: comparison between signed and unsigned integer expressions [-Wsign-compare] if (*handle >= 0 && *handle < delegate_data->tensor_memory_map.size()) { ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ERROR: /home/leimao/.cache/bazel/_bazel_leimao/b5222491e5f5e6954d481a492cdf3412/external/nccl_archive/BUILD.bazel:54:1: undeclared inclusion(s) in rule ***@***.***_archive//:device_lib': this rule is missing dependency declarations for the following files included by 'external/nccl_archive/src/collectives/device/functions.cu.cc ': 'external/nccl_archive/src/collectives/device/common.h' Target //tensorflow/tools/pip_package:build_pip_package failed to build Use --verbose_failures to see the command lines of failed build steps. INFO: Elapsed time: 101.561s, Critical Path: 19.52s INFO: 513 processes: 513 local. FAILED: Build did NOT complete successfully ` — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#26289?email_source=notifications&email_token=ABZM5DXBBSGF4XNOXVQGXADP2BE5HA5CNFSM4G3LCTW2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXO6EKI#issuecomment-501080617>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABZM5DSNAHFSDXGKHERD5ADP2BE5HANCNFSM4G3LCTWQ> .

AngledLuffa · 2019-10-28T03:01:13Z

I agree that it sucks for interfaces to change in a point release, and it's too bad nvidia hasn't released a working 10.0 on rhel/centos 8. At the same time, it's been 8 months since 10.1 came out. Some timeline for a TF update would be nice.

…

On Sun, Oct 27, 2019, 12:17 PM Roger Weihrauch ***@***.***> wrote: Hi all Since my own experiences on trying and failing installations with many different combinations of PythonX.x.x, PipX, Debian 9.x/10.x and CUDA 10.0.x/10.1.x, I think this is NVIDIA's part on solution. Since the actual errors with latest AND legacy releases of TF (as described from many users above) can only be solved by hands-on doing symlinking, the actual quality level NVIDIA shows on its heroical CUDA env is a very high crappy/shitty one. So, last but not least, me (and maybe some of you also) are damned to stay on Kernel version maximum 4.19 (best 4.9, does also not run with kernel 5.2.x), CUDA10.0.x incl. patch, cuDNN7.4.2 (i think is the latest for CUDA10.0.x) and system based pip version. Also, focusing on those versions, I get cuda up and running using the GPU on TF; nevertheless, also this version/installation shows missing some libraries after setting up CUDA, all necessary device files, shown be CUDA10.0.x version, are missing in CUDA10.1.x, which are NOT included. Also the NVIDIA_Samples will not be compiled completely since missing depending libs and programs. So, in my eyes NVIDIA is doing a very bad and unuseful job here. They are going to scare away their users from CUDA this way. That is only my opinion on this. Regards, Roger — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#26289?email_source=notifications&email_token=AA2AYWMSERUHFXTQU7EFMBLQQXLKLA5CNFSM4G3LCTW2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOECLFSJI#issuecomment-546724133>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AA2AYWOJ5PTHCE7MFODA3NTQQXLKLANCNFSM4G3LCTWQ> .

sytelus · 2019-10-28T11:42:03Z

I would also like to point out (in addition to everything that is already said) that PyTorch officially only displays CUDA 10.1 support. For someone like me who often end up having TF and PyTorch in same environment, this makes it very difficult to have them install side by side. Fortunately PyTorch builds have been superbly flexible with CUDA and I eventually figured out that merely including cudatoolkit=10.0 in conda install makes it work with CUDA 10.0 as well! I hope something like this might be possible for TF.

JeffreyWardman · 2019-11-07T04:48:32Z

In addition to what @sytelus said, the exact statement is:
conda install pytorch torchvision cudatoolkit=10.0 python==X -c pytorch
where X is your current python version if you don't want to upgrade it.

AngledLuffa · 2019-11-07T06:56:59Z

Unfortunately, the issue I'm currently running into is that cuda 10.0 doesn't even exist for centos 8. Perhaps centos / redhat was not the most convenient linux distro to choose, but switching to a different distro would be even more inconvenient at this point.

…

On Wed, Nov 6, 2019 at 8:57 PM Jeffrey Wardman ***@***.***> wrote: In addition to what @sytelus <https://github.com/sytelus> said, the exact statement is: conda install pytorch torchvision cudatoolkit=10.0 python==X -c pytorch where X is your current python version if you don't want to upgrade it. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#26289?email_source=notifications&email_token=AA2AYWKPRR3MWPUEVBDVP4LQSON4RA5CNFSM4G3LCTW2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEDJ3EOA#issuecomment-550744632>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AA2AYWKWEN336LADF5HCCD3QSON4RANCNFSM4G3LCTWQ> .

chsigg · 2019-11-07T08:27:17Z

We are working on updating TF builds to CUDA 10.1.

dexception · 2019-11-12T17:50:22Z

Release a timeline. So that we can adjust accordingly. Simply staying mum for 6 months is unacceptable. We also have jobs.

AndreMaz · 2019-11-17T10:00:50Z

Looking at #34327 seems like TF team already solved the compatibility issue. Hopefully the 2.1 release happens soon

phoerious · 2019-11-17T10:31:24Z

As an intermediary workaround, I had no issues symlinking the affected libraries to *.so.10.0.

dexception · 2019-11-21T10:01:41Z

Very unprofessional attitude towards managing a software.

chsigg · 2019-11-21T13:39:34Z

Nightly release builds and r2.1 release are built against CUDA 10.1. I'm going to close this issue.

@dexception, I agree I could have handled this better. Sorry.

tensorflow-bot · 2019-11-21T13:39:36Z

Are you satisfied with the resolution of your issue?
Yes
No

rjurney · 2019-11-21T19:03:53Z

2.1? Try 2.0.1. 2.1 will be forever, right?

chsigg · 2019-11-21T20:23:05Z

TF 2.0 release will probably stay on CUDA 10.0. You can build TF with CUDA 10.1 from any branch, or use nightly releases before TF 2.1 is released.

megazone87 · 2019-12-06T08:47:19Z

You can build TF with CUDA 10.1 from any branch

Are you sure about that? But I build from source on branch: r1.13 with the cuda 10.1, and obviously it does not work.
Errors:

library cannot find: libcublas.so.10.1 etc. Solved through syslink.
cannot find cublas_v2.h. Solved through syslink.
tensorflow/tensorflow/compiler/xla/service/gpu/BUILD:661:1: C++ compilatio n of rule '//tensorflow/compiler/xla/service/gpu:gpu_compiler' failed I have no clue for this...

Could you help me, to verify tf-1.* work with cuda10.1?

To be precise, I compiled with XLA=on (tensorRT=off). If turn it off, everything just fine. Thus i thought the above XLA related problem is not big and solvable. Please check it.

chsigg · 2019-12-06T10:05:44Z

TF r1.13 does not build with CUDA 10.1. Please use r1.15 or r2.x.

deimsdeutsch · 2020-01-01T10:00:55Z

9 months and Tensorflow is still catching up. Oh boy ! Is this library too complicated to work with ?

dishkakrauch · 2020-01-09T18:07:21Z

Version 2.1 uploaded yesterday.
It supports cuda 10.1, enjoy)

SalahAdDin · 2020-01-16T12:49:49Z

@dishkakrauch What's about CUDA 10,2?

mihaimaruseac · 2020-01-16T15:58:48Z

You can always compile from source to get compatibility with other CUDA versions.

We only provide a subset of the infinite amount of combinations that you can build with (python version, operating system version, cuda version, compiler version, libraries/dependencies versions, etc.) For all other cases all that we can do is provide instructions on how to build from source and let community do the builds.

SalahAdDin · 2020-01-17T13:53:49Z

Just downgraded to Cuda 10,1, thanks.

uranusx86 · 2020-04-18T04:01:27Z

I have made a script for install tf 1.12 with CUDA 10.1 in Ubuntu.
check my repo https://github.com/uranusx86/Tensorflow1.12-CUDA10.1-Build

youweiliang · 2020-09-03T06:57:47Z

For folks who want to use tensorflow 1.xx with CUDA 10.1, I find conda has the correct compilation of tensorflow against CUDA 10.1. Just install tensorflow 1.xx with conda within your conda environment. E.g., I install with the following command
conda install tensorflow=1.14

woodcockjosh · 2020-11-24T03:13:31Z

I "fixed" by changing this line to always return false

def _should_check_soname(version, static):
      return False

tensorflow/third_party/gpus/cuda_configure.bzl

Lines 478 to 479 in 5bc7265

    
           def _should_check_soname(version, static): 
        
               return version and not static

jiapei100 mentioned this issue Mar 3, 2019

Failed to pip install tensorflow-gpu #26290

Closed

jvishnuvardhan self-assigned this Mar 3, 2019

jvishnuvardhan added type:build/install Build and install issues stat:awaiting response Status - Awaiting response from author labels Mar 3, 2019

jvishnuvardhan assigned gunan and unassigned jvishnuvardhan Mar 20, 2019

jvishnuvardhan added stat:awaiting tensorflower Status - Awaiting response from tensorflower subtype: ubuntu/linux Ubuntu/Linux Build/Installation Issues and removed stat:awaiting response Status - Awaiting response from author labels Mar 20, 2019

tensorflowbutler removed the stat:awaiting tensorflower Status - Awaiting response from tensorflower label May 11, 2019

ymodak closed this as completed May 15, 2019

ymodak reopened this Jun 12, 2019

chsigg closed this as completed Nov 21, 2019

seanpmorgan mentioned this issue Nov 25, 2019

Build Addons with CUDA 10.1 tensorflow/addons#719

Closed

HaFred mentioned this issue Feb 10, 2020

ImportError: /lib64/libm.so.6: version `GLIBC_2.23' not found (required by /home/xsx/.conda/envs/tensorflow/lib/python3.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so) #28660

Closed

Saduf2019 mentioned this issue Jul 28, 2020

RuntimeError: tensorflow/lite/kernels/detection_postprocess.cc:158 NumOutputs(node) != 4 (3 != 4)Node number 180 (TFLite_Detection_PostProcess) failed to prepare. #41787

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beew mentioned this issue Aug 17, 2020

mxnet python gpu not work apache/mxnet#18879

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bertsky mentioned this issue Sep 18, 2020

CUDA version woes OCR-D/core#595

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jaentrouble mentioned this issue Sep 27, 2020

Failed to build on Cuda-11.1 #43588

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Compatibility with Cuda 10.1? #26289

Compatibility with Cuda 10.1? #26289

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