[theano-users] Re: MILA and the future of Theano

[sunnysaxena . webtunix]

Dear Theano Team,

I would like to say thank you very much to your entire team for developing 
a awesome deep learning library.
I hoping that you guys will again get stared the halted campaign.




Regards,
Sunny Saxena

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Re: [theano-users] Re: Cannot update Theano to 1.0.0

[mcomin]

I don't need the GPU on the MAC computer. Still, *conda install -c 
mila-udem theano  *is installing theano 0.9.0-py35_0.
So how can I get the 1.0.0 version ?

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[theano-users] NameError: name '__file__' is not defined in SDA example

[tony]

HI

I'm getting this error after I run the SDA code , how this error can be 
fixed ?


NameError Traceback (most recent call 
last) in ()466 467 if __name__ == 
'__main__':--> 468 test_SdA()
 in test_SdA(finetune_lr, pretraining_epochs, 
pretrain_lr, training_epochs, dataset, batch_size)375 376 
print(('The pretraining code for file ' +--> 377
os.path.split(__file__)[1] +378' ran for %.2fm' % ((end_time - 
start_time) / 60.)), file=sys.stderr)379 # end-snippet-4
NameError: name '__file__' is not defined



SDA from deeplearning.net 

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[theano-users] Re: Problem with theano in gpu

[Ruben Dario Fonnegra Tarazona]

Hi Pascal.



I already solve the problem. Apparently, the seg fault was caused by some 
internal problem with the cudnn 6 library (it seemed to be a bug). After 
I verify it was a cudnn library problem, I realize that I could run 
code using the dnn.enable=False flag. However, I solve this bug by 
uninstalling the cudnn 6 and installing cudnn 7. It worked perfectly. Thank 
you very much for your response, in any case. (Y)





El miércoles, 22 de noviembre de 2017, 1:49:45 (UTC+1), Ruben Dario 
Fonnegra Tarazona escribió:
>
> Hi.
>
>
>
> I'm having ploblems executing code in theano. I installed the dev version 
> and it runs perfectly in CPU. However, when I try to run anything in the 
> gpu (even LeNet with MNIST) the model doesn't even run and it appears an 
> only message saying "Segmentation fault. Core dumped". Despite of that, I 
> tried to verify theano installation using the command THEANO_FLAGS='';python 
> -c "import theano; theano.test()" and it did not work (I attach the 
> output in log file). I tried several things but I couldn't solve the 
> problem. I attach a file with the output after executing the command, and 
> my theanorc file. I work with a Kubuntu 16.04, CUDA 8 and cuDNN 6.2 in the 
> Quadro M4000 series (8GB - the problem is not memory allocation). I hope 
> you could help me solve the problem. Thanks in advice, and I will be very 
> attentive for your answer.
>
>
>
> What I've tried?
> - Install stable, bleeding edge and dev theano version, using their 
> corresponding libgpuarray library (same issue) 
> - Manually compile OpenBLAS for installation
> - Use environment variable CUDA_LAUNCH_BLOCKING set to 1
> - Use several floatX types (float16, float32, float64)
> - Use device=cpu and device=cuda0 flags
>
> Note: It might be the CUDA drivers; however, I can use TensorFlow running 
> on GPU without any problem.
>
>
>
>
> output of theano.test() 
> -
>
> HP-Z840-Workstation:~/Data$ THEANO_FLAGS=''; python -c "import theano; 
> theano.test()"
>
> Theano version 1.0.0
>
> theano is installed in /home/bluegum1/Theano/theano
> NumPy version 1.13.3
>
> NumPy relaxed strides checking option: True
> NumPy is installed in 
> /home/bluegum1/.local/lib/python2.7/site-packages/numpy
>
> Python version 2.7.12 (default, Nov 19 2016, 06:48:10) [GCC 5.4.0 20160609]
>
> nose version 1.3.7
>
> Using cuDNN version 6021 on context None
>
> Mapped name None to device cuda: Quadro M4000 (:04:00.0)
>
> ..ERROR (theano.gof.opt): 
> Optimization failure due to: insert_bad_dtype
> ERROR (theano.gof.opt): node: 
> Elemwise{add,no_inplace}(, 
> )
>
> ERROR (theano.gof.opt): TRACEBACK:
> ERROR (theano.gof.opt): Traceback (most recent call last):
>   File "/home/bluegum1/Theano/theano/gof/opt.py", line 2059, in 
> process_node
> remove=remove)
>   File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 569, in 
> replace_all_validate_remove
> chk = fgraph.replace_all_validate(replacements, reason)
>   File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 518, in 
> replace_all_validate
> fgraph.replace(r, new_r, reason=reason, verbose=False)
>   File "/home/bluegum1/Theano/theano/gof/fg.py", line 486, in replace
> ". The type of the replacement must be the same.", old, new)
>
> BadOptimization: BadOptimization Error 
>   Variable: id 140331434464144 Elemwise{Cast{float32}}.0
>   Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
>   Value Type: 
>   Old Value:  None
>   New Value:  None
>   Reason:  insert_bad_dtype. The type of the replacement must be the same.
>   Old Graph:
>   Elemwise{add,no_inplace} [id A]  ''   
>| [id B] 
>| [id C] 
>
>  
> New Graph:
>   Elemwise{Cast{float32}} [id D]  ''   
>|Elemwise{add,no_inplace} [id A]  ''   
>
>
>
> Hint: relax the tolerance by setting tensor.cmp_sloppy=1
>   or even tensor.cmp_sloppy=2 for less-strict comparison
>
>
> ..S./home/bluegum1/Theano/theano/compile/nanguardmode.py:150:
>  
> RuntimeWarning: All-NaN slice encountered
>   return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
> /home/bluegum1/Theano/theano/compile/nanguardmode.py:150: RuntimeWarning: 
> All-NaN axis encountered
>   return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
>
> ../home/bluegum1/Theano/theano/gof/vm.py:886:
>  
> UserWarning: CVM does not support memory profile, using Stack VM.
>   'CVM does not support memory profile, using Stack VM.')
> /home/bluegum1/Theano/theano/compile/profiling.py:283: 
> UserWarning: You are running the Theano profiler with CUDA enabled. Theano 
> GPU ops execution is asynchronous by default. So by default, the profile is 
> useless. You must set the environment variable CUDA_LAUNCH_BLOCKING to 1 to 
> tell the CUDA driver to synchronize the execution to get a meaningful 
> pro

Re: [theano-users] Using NumPy C-API based implementation for BLAS functions.

[Pascal Lamblin]

Hi,

Usually, Theano tries to link directly with a BLAS library (MKL, 
OpenBlas...) if it is able to detect one, and use it for dot products on 
CPU.
If it does not, it uses the fallback of using the C API of numpy 
instead, which can be slower and result in more memory copies.


On 2017-11-23 05:00 AM, Mathias Müller wrote:


Hi,

With the newest Theano, I get the following warning:

|
WARNING (theano.tensor.blas):UsingNumPyC-API based implementation 
forBLAS functions.

|

What does this message mean? Does that mean there is an alternative to 
Numpy C-API based BLAS functions?


Thanks a lot for your help.
Mathias

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Re: [theano-users] Using Theano and cuDNN with clang-3.8 in a linux environment

[Pascal Lamblin]

Theano 0.8 is not supported any more. Can you use 1.0?

On 2017-11-22 05:44 AM, Antonio Abello wrote:

Hello!

I'm using Theano 0.8.0 on a machine that I have no control over and has 
an older version of Debian installed (Debian Squeeze - 6.3.0).
It does not have a low enough gcc version to run cuda-7.5 (<= 4.9) nor 
it has a high enough version to run cuda 8
Whenever I tried to import theano it said that clang-3.8 was available 
and it should be used instead. So I included this on my .theanorc and it 
worked:


[global]
device=gpu
floatX = float32
[nvcc]
flags = -ccbin=clang-3.8
[dnn]
include_path="/home/$USER/cuda/include"
library_path="/home/$USER/cuda/lib64"

But I noticed it didn't use cuDNN, so it was significantly slower. When 
I enforced cuDNN use with optimizer_including=cudnn I got:


AssertionError: cuDNN optimization was enabled, but Theano was not able 
to use it. We got this error:

Theano can not compile with cuDNN. We got this error:
ERROR: No supported gcc/g++ host compiler found, but clang-3.8 is 
available. Use 'nvcc -ccbin clang-3.8' to use that instead.\n"


Which is incidentaly the exact same error I got in the beggining.
I believe gcc/g++ is used as the default option whenever theano is on a 
Linux environment. Is there a way to force Theano to use clang-3.8 to 
compile cuDNN instead? Is there something else I'm missing here? 
Unfortunately upgrading Theano is not an option since the NN lib im 
using (Lasagne) has not updated to Theano 1.0


Thanks,
Antonio

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Re: [theano-users] Problem with theano in gpu

[Pascal Lamblin]

Hi,

Can you try running "nosetests -v" or "theano-nose -v" in command line, 
rather than from Python?

This should at least give the name of the test during which it crashes.

On 2017-11-21 07:49 PM, Ruben Dario Fonnegra Tarazona wrote:

Hi.



I'm having ploblems executing code in theano. I installed the dev 
version and it runs perfectly in CPU. However, when I try to run 
anything in the gpu (even LeNet with MNIST) the model doesn't even run 
and it appears an only message saying "Segmentation fault. Core dumped". 
Despite of that, I tried to verify theano installation using the command 
THEANO_FLAGS='';python -c "import theano; theano.test()" and it did not 
work (I attach the output in log file). I tried several things but I 
couldn't solve the problem. I attach a file with the output after 
executing the command, and my theanorc file. I work with a Kubuntu 
16.04, CUDA 8 and cuDNN 6.2 in the Quadro M4000 series (8GB - the 
problem is not memory allocation). I hope you could help me solve the 
problem. Thanks in advice, and I will be very attentive for your answer.




What I've tried?
- Install stable, bleeding edge and dev theano version, using their 
corresponding libgpuarray library (same issue)

- Manually compile OpenBLAS for installation
- Use environment variable CUDA_LAUNCH_BLOCKING set to 1
- Use several floatX types (float16, float32, float64)
- Use device=cpu and device=cuda0 flags

Note: It might be the CUDA drivers; however, I can use TensorFlow 
running on GPU without any problem.





output of theano.test() 
-


HP-Z840-Workstation:~/Data$ THEANO_FLAGS=''; python -c "import theano; 
theano.test()"


Theano version 1.0.0

theano is installed in /home/bluegum1/Theano/theano
NumPy version 1.13.3

NumPy relaxed strides checking option: True
NumPy is installed in 
/home/bluegum1/.local/lib/python2.7/site-packages/numpy


Python version 2.7.12 (default, Nov 19 2016, 06:48:10) [GCC 5.4.0 20160609]

nose version 1.3.7

Using cuDNN version 6021 on context None

Mapped name None to device cuda: Quadro M4000 (:04:00.0)

..ERROR (theano.gof.opt): 
Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: 
Elemwise{add,no_inplace}(, 
)


ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
   File "/home/bluegum1/Theano/theano/gof/opt.py", line 2059, in 
process_node

     remove=remove)
   File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 569, in 
replace_all_validate_remove

     chk = fgraph.replace_all_validate(replacements, reason)
   File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 518, in 
replace_all_validate

     fgraph.replace(r, new_r, reason=reason, verbose=False)
   File "/home/bluegum1/Theano/theano/gof/fg.py", line 486, in replace
     ". The type of the replacement must be the same.", old, new)

BadOptimization: BadOptimization Error
   Variable: id 140331434464144 Elemwise{Cast{float32}}.0
   Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
   Value Type: 
   Old Value:  None
   New Value:  None
   Reason:  insert_bad_dtype. The type of the replacement must be the same.
   Old Graph:
   Elemwise{add,no_inplace} [id A]  ''
    | [id B] 
    | [id C] 

New Graph:
   Elemwise{Cast{float32}} [id D]  ''
    |Elemwise{add,no_inplace} [id A]  ''



Hint: relax the tolerance by setting tensor.cmp_sloppy=1
   or even tensor.cmp_sloppy=2 for less-strict comparison


..S./home/bluegum1/Theano/theano/compile/nanguardmode.py:150: 
RuntimeWarning: All-NaN slice encountered

   return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/home/bluegum1/Theano/theano/compile/nanguardmode.py:150: 
RuntimeWarning: All-NaN axis encountered

   return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))

../home/bluegum1/Theano/theano/gof/vm.py:886: 
UserWarning: CVM does not support memory profile, using Stack VM.

   'CVM does not support memory profile, using Stack VM.')
/home/bluegum1/Theano/theano/compile/profiling.py:283: 
UserWarning: You are running the Theano profiler with CUDA enabled. 
Theano GPU ops execution is asynchronous by default. So by default, the 
profile is useless. You must set the environment variable 
CUDA_LAUNCH_BLOCKING to 1 to tell the CUDA driver to synchronize the 
execution to get a meaningful profile.

   warnings.warn(msg)

0.0581646137166

0.0581646137166

0.0581646137166

0.0581646137166

.../home/bluegum1/Theano/theano/gof/vm.py:889: 
UserWarning: LoopGC does not support partial evaluation, using Stack VM.

   'LoopGC does not support partial evaluation, '

Re: [theano-users] Re: Cannot update Theano to 1.0.0

[Frédéric Bastien]

We have problems supporting mac computers with GPUs as CUDA isn't well
supported there. Do you need the GPU? If not, just install Theano like this:

conda install -c mila-udem theano

>From memory, pygpu isn't build anymore for mac.

On Tue, Nov 28, 2017 at 10:32 AM mcomin  wrote:

> From Theano website :
>
>
>
> *Latest conda packages for theano (>= 0.9) and pygpu (>= 0.6*) currently
> don’t support Python 3.4 branch.*And :
>
> *Moved Python 3.* minimum supported version from 3.3 to 3.4*
>
> Does it mean that I can't update Theano from conda if I have python 3.5 ?
>
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[theano-users] Re: Cannot update Theano to 1.0.0

[mcomin]

>From Theano website :



*Latest conda packages for theano (>= 0.9) and pygpu (>= 0.6*) currently 
don’t support Python 3.4 branch.*And :

*Moved Python 3.* minimum supported version from 3.3 to 3.4*

Does it mean that I can't update Theano from conda if I have python 3.5 ?

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