Hi Arnold, I have some problems similar to yours and I'm trying to run train.py on a Windows 10 machine. Did you find some solutions to your problems and incompatiblity with pycuda as I could understand in this post? Thanks in advance for expert help and your time. Greetings, Goffredo
------ C:\deep_learning\alexnet>python train.py WARNING (theano.sandbox.cuda): The cuda backend is deprecated and will be removed in the next release (v0.10). Please switch to the gpuarray backend. You can get more information about how to switch at this URL: https://github.com/Theano/Theano/wiki/Converting-to-the-new-gpu-back-end%28gpuarray%29 Using gpu device 0: GeForce GT 740M (CNMeM is enabled with initial size: 80.0% of memory, cuDNN 5105) WARNING (theano.sandbox.cuda): The cuda backend is deprecated and will be removed in the next release (v0.10). Please switch to the gpuarray backend. You can get more information about how to switch at this URL: https://github.com/Theano/Theano/wiki/Converting-to-the-new-gpu-back-end%28gpuarray%29 ... building the model conv (cudnn) layer with shape_in: (3, 227, 227, 256) Process Process-1: Traceback (most recent call last): File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\multiprocessing\process.py", line 254, in _bootstrap self.run() File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\multiprocessing\process.py", line 93, in run self._target(*self._args, **self._kwargs) File "C:\deep_learning\alexnet\train.py", line 52, in train_net model = AlexNet(config) File "C:\deep_learning\alexnet\alex_net.py", line 62, in __init__ lib_conv=lib_conv, File "./lib\layers.py", line 168, in __init__ dnn.dnn_conv(img=input_shuffled[:, :self.channel / 2, File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\tensor\var.py", line 540, in __getitem__ return theano.tensor.subtensor.advanced_subtensor(self, *args) File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\gof\op.py", line 604, in __call__ node = self.make_node(*inputs, **kwargs) File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\tensor\subtensor.py", line 2140, in make_node index = tuple(map(as_index_variable, index)) File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\tensor\subtensor.py", line 2081, in as_index_variable return make_slice(idx) File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\gof\op.py", line 604, in __call__ node = self.make_node(*inputs, **kwargs) File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\tensor\type_other.py", line 39, in make_node list(map(as_int_none_variable, inp)), File "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\theano\tensor\type_other.py", line 20, in as_int_none_variable raise TypeError('index must be integers') TypeError: index must be integers ------------------------------------------------------------------- PyCUDA ERROR: The context stack was not empty upon module cleanup. ------------------------------------------------------------------- A context was still active when the context stack was being cleaned up. At this point in our execution, CUDA may already have been deinitialized, so there is no way we can finish cleanly. The program will be aborted now. Use Context.pop() to avoid this problem. ------------------------------------------------------------------- Il giorno mercoledì 6 aprile 2016 00:10:06 UTC+2, Arnold Tunick ha scritto: > > Hello Petar, > > > 1. I received help from you on or about 15-17 March 2016 thru Google > groups theano-users (topic: theano_alexnet "train.py"). > 2. I have made great progress to install and test the prerequisite > software to implement Theano-AlexNet on a Windows 10 notebook computer. > 3. I have re-installed and tested the newer version of Theano (v0.8.0) > with CUDA 7.5, MS Visual Studio 12.0, python 2.7.9.4, pycuda 2015.1.3 , > boost 1.5.9, TDM-GCC (64-bit), numpy, zeromq, hickle and pylearn2. > 4. I have successfully pre-processed a subset of the ImageNet data using > the script generate_toy_data.sh, which generated all of the expected > folders and files. > 5. After fixing some problems related to TypeErrors, per your > instruction, I then went ahead and ran theano-alexnet train.py as > C:\SciSoft\Git\theano_alexnet>python train.py THEANO_FLAGS=mode=FAST_RUN, > floatX=float32. > 6. Now the program initializes fine, but when it starts the training, it > crashes with an error message that indicated something about the > operating system (OS). [see messages below]. > 7. I have contacted Weiguang Ding, who co-authored a 06 April 2015 arXiv > paper on theano-alexnet entitled, "Theano-based large-scale visual > recognition with multiple GPUs. > 8. Yet, he recommended that I continue to explore the Google groups > theano-users for help. > 9. Interestingly, both Fred Bastien and Pascal Lamblin advised running > the code on Linux because they think that the theano-alexnet code may use > features from CUDA that are only available on Linux. > 10. Nevertheless, I would like to continue to work towards viable > solution using the setup that I have already established, so that I can use > Theano-AlexNet to explore feature recognition from various new images. > 11. Any suggestions or recommendations that you may offer would be greatly > appreciated. > . > Thanks in advance for time and expert help. > . > Best, > Arnold Tunick > > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > ++++++++++++++++ > > C:\SciSoft\Git\theano_alexnet>python train.py > THEANO_FLAGS=mode=FAST_RUN, floatX=float32 > > > > Using gpu device 0: Quadro K4000M (CNMeM is disabled, CuDNN 3007) > . > > ... building the model > . > > conv (cudnn) layer with shape_in: (3, 227, 227, 256) > > conv (cudnn) layer with shape_in: (96, 27, 27, 256) > > conv (cudnn) layer with shape_in: (256, 13, 13, 256) > > conv (cudnn) layer with shape_in: (384, 13, 13, 256) > > conv (cudnn) layer with shape_in: (384, 13, 13, 256) > > fc layer with num_in: 9216 num_out: 4096 > > dropout layer with P_drop: 0.5 > > fc layer with num_in: 4096 num_out: 4096 > > dropout layer with P_drop: 0.5 > > softmax layer with num_in: 4096 num_out: 1000 > . > > ... training > . > > Process Process-1: > > Traceback (most recent call last): > > File > > "C:\SciSoft\WinPython-64bit-2.7.9.4\python-2.7.9.amd64\lib\ > multiprocessing\process.py", > > line 266, in _bootstrap > > self.run() > > File > > "C:\SciSoft\WinPython-64bit-2.7.9.4\python-2.7.9.amd64\lib\ > multiprocessing\process.py", > > line 120, in run > > self._target(*self._args, **self._kwargs) > > File "C:\SciSoft\Git\theano_alexnet\train.py", line 69, in train_net > > h = drv.mem_get_ipc_handle(gpuarray_batch.ptr) > . > > LogicError: cuIpcGetMemHandle failed: OS call failed or operation not > > supported > on this OS > +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. 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