You may need use gcc4.8 or gcc4.9 to reinstall protobuf.

BTW, there is a compatibility problem between gcc5.x and cuda 7,
http://stackoverflow.com/questions/34996295/trying-to-get-cuda-7-5-to-work-with-gcc-5-x



On Thu, Sep 22, 2016 at 4:31 PM, Arash Shafiei <arash.shaf...@gmail.com>
wrote:

> Yes, we are using the same link.
>
> gcc version is 5.4.0
>
> On Thu, Sep 22, 2016 at 4:24 PM, Wang Wei <wang...@comp.nus.edu.sg> wrote:
>
>> Are you using the singa wheel for protobuf 2.6 (i.e. the following link)?
>>
>> http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl
>>
>> May I know your gcc version for compiling protobuf?
>>
>> On Thu, Sep 22, 2016 at 4:10 PM, Arash Shafiei <arash.shaf...@gmail.com>
>> wrote:
>>
>>> Hi Wang Wei,
>>>
>>> Here is the output of ldd /usr/local/lib/python2.7/dist-
>>> packages/singa/_singa_wrap.so
>>>
>>> linux-vdso.so.1 =>  (0x00007ffc5abba000)
>>>     libprotobuf.so.9 => /usr/local/lib/libprotobuf.so.9
>>> (0x00007f20dd5c3000)
>>>     libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0
>>> (0x00007f20dd3a5000)
>>>     libcudnn.so.5 => /usr/lib/x86_64-linux-gnu/libcudnn.so.5
>>> (0x00007f20d985a000)
>>>     libcudart.so.7.5 => /usr/local/cuda/lib64/libcudart.so.7.5
>>> (0x00007f20d95fc000)
>>>     libcurand.so.7.5 => /usr/local/cuda/lib64/libcurand.so.7.5
>>> (0x00007f20d5d93000)
>>>     libcublas.so.7.5 => /usr/local/cuda/lib64/libcublas.so.7.5
>>> (0x00007f20d44b4000)
>>>     libopenblas.so.0 => /usr/lib/libopenblas.so.0 (0x00007f20d2420000)
>>>     libpython2.7.so.1.0 => /usr/local/lib/libpython2.7.so.1.0
>>> (0x00007f20d2022000)
>>>     libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6
>>> (0x00007f20d1ca0000)
>>>     libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007f20d1997000)
>>>     libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1
>>> (0x00007f20d1780000)
>>>     libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f20d13b7000)
>>>     libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007f20d119d000)
>>>     /lib64/ld-linux-x86-64.so.2 (0x000055d5047c5000)
>>>     librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007f20d0f94000)
>>>     libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007f20d0d90000)
>>>     libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3
>>> (0x00007f20d0a64000)
>>>     libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1
>>> (0x00007f20d0861000)
>>>     libquadmath.so.0 => /usr/lib/x86_64-linux-gnu/libquadmath.so.0
>>> (0x00007f20d0621000)
>>>
>>>
>>> Although we installed libprotobuf2.6, but it shows that the
>>> libprotobuf.so.9 is installed.
>>>
>>> We can verify the version of protobuf using:
>>> protoc --version
>>> libprotoc 2.6.0
>>>
>>> We are installing the protobuf from the source:
>>> https://github.com/google/protobuf/releases/tag/v2.6.0
>>>
>>> Would you know where we could be doing wrong?
>>>
>>> Thanks.
>>>
>>>
>>> On Thu, Sep 22, 2016 at 3:34 PM, Wang Wei <wang...@comp.nus.edu.sg>
>>> wrote:
>>>
>>>> Hi Arash,
>>>>
>>>> Have you installed google protobuf, which is a dependent library of
>>>> SINGA?
>>>> Can you send me the output from running
>>>>
>>>> ldd /usr/local/lib/python2.7/dist-packages/singa/_singa_wrap.so
>>>>
>>>> It would display the version of the protobuf wheel is using.
>>>>
>>>> Please make sure the version of the protobuf matches the wheel version.
>>>> Use the singa wheel for 2.5-protobuf if you installed protobuf 2.5 on
>>>> your machine.
>>>> Use the singa wheel for 2.6-protobuf if you installed protobuf 2.6 on
>>>> your machine.
>>>>
>>>> You don't need to reset the path if If you use virtualenv.
>>>>
>>>>
>>>> On Thu, Sep 22, 2016 at 3:24 PM, Arash Shafiei <arash.shaf...@gmail.com
>>>> > wrote:
>>>>
>>>>> Hi Wang Wei, Thanks.
>>>>>
>>>>> We installed it from the wheel and that problem was solved.
>>>>>
>>>>> Now we are facing a new error message:
>>>>> No module name _singa_wrap
>>>>>
>>>>> Then we set the path to the singa folder located at:
>>>>> /usr/local/lib/python2.7/dist-packages/singa
>>>>>
>>>>> And we are getting this error message:
>>>>> mportError: /usr/local/lib/python2.7/dist-packages/singa/_singa_wrap.so:
>>>>> undefined symbol: _ZNK6google8protobuf7Message11GetTypeNameEv
>>>>>
>>>>> It seems there is a link problem. Would you know where the problem
>>>>> could be?
>>>>>
>>>>> Thanks.
>>>>>
>>>>>
>>>>>
>>>>> On Thu, Sep 22, 2016 at 2:23 PM, Wang Wei <wang...@comp.nus.edu.sg>
>>>>> wrote:
>>>>>
>>>>>> Hi Arash,
>>>>>>
>>>>>> Have you installed PySINGA via the following approaches (
>>>>>> http://singa.apache.org/en/docs/installation.html#install-pysinga)?
>>>>>>
>>>>>> # in build/ folder
>>>>>> cmake -DUSE_CUDA=ON -DUSE_PYTHON=ON ..
>>>>>> make
>>>>>> cd python
>>>>>> pip install .
>>>>>>
>>>>>> or using the python wheel
>>>>>>
>>>>>> On Thu, Sep 22, 2016 at 2:02 PM, Arash Shafiei <
>>>>>> arash.shaf...@gmail.com> wrote:
>>>>>>
>>>>>>> Dear Wang Wei,
>>>>>>>
>>>>>>> We are still working on the activity recognition project and have
>>>>>>> some difficulties installing SINGA.
>>>>>>>
>>>>>>> The python2.7 is installed. Trying to do RNN training using
>>>>>>> "python2.7 train.py linux_input.txt", we get the following error:
>>>>>>>
>>>>>>> ImportError: No module name singa.
>>>>>>>
>>>>>>> It seems that python cannot find the singa module. We tried to set
>>>>>>> the path of singa in PYTHONPATH but it didn't help.
>>>>>>>
>>>>>>> Python is installed in:
>>>>>>>
>>>>>>> /usr/include/python2.7
>>>>>>> /usr/lib/python2.7
>>>>>>> /usr/bin/python2.7
>>>>>>>
>>>>>>> Singa is installed in:
>>>>>>> /usr/local/include/singa
>>>>>>> /usr/local/bin/singa
>>>>>>>
>>>>>>> Thanks.
>>>>>>> Arash
>>>>>>>
>>>>>>>
>>>>>>> On Fri, Sep 16, 2016 at 3:24 PM, Wang Wei <wang...@comp.nus.edu.sg>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Sure.
>>>>>>>> You can use the API of RNN (http://singa.apache.org/en/do
>>>>>>>> cs/layer.html#singa.layer.RNN) to construct a supervised model and
>>>>>>>> train it with labels.
>>>>>>>> E.g., a simple model would be input->rnn->dense->softmax->cross-entropy
>>>>>>>> loss.
>>>>>>>> The loss is computed to reduce the prediction error against the
>>>>>>>> ground truth labels.
>>>>>>>>
>>>>>>>> You may need to read some papers on activity recognition and find
>>>>>>>> proper datasets, e.g. http://archive.ics.uci.edu/ml/
>>>>>>>> datasets/Heterogeneity+Activity+Recognition.
>>>>>>>> I think one problem is that you need to do some feature engineering
>>>>>>>> for the raw data, whose feature has few dimensions.
>>>>>>>> We have tried to use the original 3-dimendional feature with a MLP
>>>>>>>> model, the performance is not good (about 50% accuracy). But the
>>>>>>>> 500-dimensional feature in the above dataset has about 90% accuracy.
>>>>>>>>
>>>>>>>> Best,
>>>>>>>> Wei
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>

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