There is not much I could say for I am running theano and numpy etc on
windows 7 with an older version such as theano 0.9 cuDNN ~5005. Everything
works though.
Also, your configuration file looks quite different from mine. As a
reference, here is my configuration
[global]
floatX = float32
device =cuda
mode=FAST_RUN
allow_gc=False
warn_float64=warn
[cuda]
root = C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
[gpuarray]
preallocate = 0.85
[dnn]
library_path = C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v8.0\lib\x64
include_path = C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v8.0\include
[nvcc]
flags=-LC:\Users.....
compiler_bindir=C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin
fastmath = True
optimizer_including=dnn
[blas]
ldflags = -lf77blas -latlas -lgfortran -lblas
On Wednesday, 22 November 2017 13:49:45 UTC+13, 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 (0000:04:00.0)
>
> ..........................................ERROR (theano.gof.opt):
> Optimization failure due to: insert_bad_dtype
> ERROR (theano.gof.opt): node:
> Elemwise{add,no_inplace}(<TensorType(float64, vector)>,
> <TensorType(float64, vector)>)
>
> 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: <type 'NoneType'>
> 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] <TensorType(float64, vector)> ''
> |<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
> |<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
>
>
> New Graph:
> Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
> |Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
>
>
>
> 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, '
> ..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................Violación
>
> de segmento (`core' generado)
>
> ---------------------------------------------------------------------
>
> theanorc file
> ---------------------------------------------------------------------
>
>
>
> [global]
> floatX = float32
> #device = cuda0
> #device = cpu
> #optimizer=fast_run
> #optimizer=fast_compile #Desabilita la GPU
> #optimizer=None
>
> [cuda]
> root = /usr/local/cuda-8.0
>
> [nvcc]
> fastmath = True
>
> [lib]
> cnmem = 1.0
>
>
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