Issue 1:
Please make sure that this is a build/installation issue. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04 on gcloud

TensorFlow installed from (source or binary): not sure

TensorFlow version: 1.13.

Python version: 3.5

Installed using virtualenv? pip? conda?: pip

Bazel version (if compiling from source):

GCC/Compiler version (if compiling from source):

CUDA/cuDNN version: 10

GPU model and memory: Nvidia K-80 15 GB

Describe the problem

I created a gpu vm instance on google cloud and followed the steps to install tensorflow-gpu

Provide the exact sequence of commands / steps that you executed before running into the problem

update apt-get

sudo apt-get update

work as root

sudo su

#!/bin/bash

echo "Checking for CUDA and installing."

Check for CUDA and try to install.

if ! dpkg-query -W cuda; then

curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb

sudo dpkg -i cuda-repo-ubuntu1604_9.0.176-1_amd64.deb

sudo apt-get update

sudo apt-get install cuda-9-0

sudo nvidia-smi -pm 1

fi

Test that your GPU is sucessfully installed:

check that GPU is working

nvidia-smi

Install your Deep Neural Network (cuDNN) binaries that you uploaded earlier (check your version):

sudo dpkg -i libcudnn7_7.4.2.24-1+cuda10.0_amd64.deb

echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc

echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc

echo 'export LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc

source ~/.bashrc

Install tensorflow

sudo apt-get install python3-dev python3-pip libcupti-dev

install tensorflow-gpu

sudo pip3 install tensorflow-gpu

install ipython3

apt install ipython3

Any other info / logs

here is my error file when i do python3 import tensorflow as tf

Traceback (most recent call last):

File "", line 1, in

File "/usr/local/lib/python3.5/dist-packages/tensorflow/init.py", line 24, in

from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import

File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/init.py", line 49, in

from tensorflow.python import pywrap_tensorflow

File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in

raise ImportError(msg)

ImportError: Traceback (most recent call last):

File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in

from tensorflow.python.pywrap_tensorflow_internal import *

File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in

_pywrap_tensorflow_internal = swig_import_helper()

File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_i

mport_helper

_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)

File "/usr/lib/python3.5/imp.py", line 242, in load_module

return load_dynamic(name, filename, file)

File "/usr/lib/python3.5/imp.py", line 342, 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.

Issue 2:
System information

Linux 4.9.0-kali4-686-pae #1 SMP Debian 4.9.25-1kali1 (2017-05-04) i686 GNU/Linux

TensorFlow installed from source code

TensorFlow version : 1.0.1

Bazel version : 0.4.2

CUDA/cuDNN version: None

GPU model and memory: None

== cat /etc/issue ===============================================

Linux 4.9.0-kali4-686-pae #1 SMP Debian 4.9.25-1kali1 (2017-05-04) i686 GNU/Linux

VERSION="2017.1"

VERSION_ID="2017.1"

== are we in docker =============================================

No

== compiler =====================================================

c++ (Debian 6.3.0-16) 6.3.0 20170425

Copyright (C) 2016 Free Software Foundation, Inc.

This is free software; see the source for copying conditions. There is NO

warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

== uname -a =====================================================

Linux 4.9.0-kali4-686-pae #1 SMP Debian 4.9.25-1kali1 (2017-05-04) i686 GNU/Linux

== check pips ===================================================

numpy (1.12.1)

== check for virtualenv =========================================

False

== tensorflow import ============================================

Traceback (most recent call last):

File "", line 1, in

File "tensorflow/init.py", line 24, in

from tensorflow.python import *

File "tensorflow/python/init.py", line 72, in

raise ImportError(msg)

ImportError: Traceback (most recent call last):

File "tensorflow/python/init.py", line 61, in

from tensorflow.python import pywrap_tensorflow

ImportError: cannot import name pywrap_tensorflow

Failed to load the native TensorFlow runtime.

See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error

for some common reasons and solutions. Include the entire stack trace

above this error message when asking for help.

== env ==========================================================

LD_LIBRARY_PATH is unset

DYLD_LIBRARY_PATH is unset

== nvidia-smi ===================================================

== cuda libs ===================================================

Describe the problem

I compiled it from source, and got this fatal error when try to import tensorflow in python3.5.3:

Python 3.5.3 (default, Jan 19 2017, 14:11:04)
[GCC 6.3.0 20170118] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
F tensorflow/core/platform/cpu_feature_guard.cc:35] The TensorFlow library was compiled to use SSE instructions, but these aren't available on your machine.
Aborted

And here is the information of my CPU:

.......
processor : 3
vendor_id : GenuineIntel
cpu family : 6
model : 37
model name : Intel(R) Core(TM) i3 CPU M 370 @ 2.40GHz
stepping : 5
microcode : 0x4
cpu MHz : 933.000
cache size : 3072 KB
physical id : 0
siblings : 4
core id : 2
cpu cores : 2
apicid : 5
initial apicid : 5
fdiv_bug : no
f00f_bug : no
coma_bug : no
fpu : yes
fpu_exception : yes
cpuid level : 11
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe nx rdtscp lm constant_tsc arch_perfmon pebs bts xtopology nonstop_tsc aperfmperf eagerfpu pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 popcnt lahf_lm tpr_shadow vnmi flexpriority ept vpid dtherm arat
bugs :
bogomips : 4787.91
clflush size : 64
cache_alignment : 64
address sizes : 36 bits physical, 48 bits virtual
......

that's all.