On Friday, June 30, 2017 at 9:50:58 PM UTC-4, Daniel Seita wrote: > > your plan worked! >
Nice to hear that :) > Pascal and nouiz, just one last thing, this GPU backend is the first time > that Theano can run float64 with the GPU, right? I'm hoping to take > existing code which uses float64 only and running it on the GPU. (That's > why I've been using the CPU recently, to use float64.) > Yes, indeed. Note that float64 performance can be much slower than float32, depending on the GPU. For instance, on a Titan X (Pascal), it would be 32x slower than float32, K40 and K80 should be only 3x slower, and P100 / GP100 2x slower. > > > > On Friday, June 30, 2017 at 6:48:08 PM UTC-7, Daniel Seita wrote: >> >> Hi nouiz and Pascal, thanks for the responses. I've been busy using the >> CPU version of Theano in the meantime, so sorry for the delay in responding. >> >> nouiz: >> >> I actually had my `cudnn.h` file in both a `lib64` directory and an >> `include` directory: >> >> ~$ ls -lh /usr/local/cuda-8.0/include/cudnn.h >> -r--r--r-- 1 root root 98K Oct 17 2016 /usr/local/cuda-8.0/include/cudnn >> .h >> ~$ ls -lh /usr/local/cuda-8.0/lib64/cudnn.h >> -r--r--r-- 1 root root 98K Oct 17 2016 /usr/local/cuda-8.0/lib64/cudnn.h >> >> I must have copied them to both when I was installing it. Also, here is >> my error message in full, assuming that my `~/.theanorc` file is >> >> ~$ cat ~/.theanorc >> [global] >> device = cuda >> floatX = float64 >> >> [cuda] >> root = /usr/local/cuda-8.0 >> ~$ ipython >> Python 2.7.13 |Anaconda custom (64-bit)| (default, Dec 20 2016, 23:09:15) >> Type "copyright", "credits" or "license" for more information. >> >> IPython 5.3.0 -- An enhanced Interactive Python. >> ? -> Introduction and overview of IPython's features. >> %quickref -> Quick reference. >> help -> Python's own help system. >> object? -> Details about 'object', use 'object??' for extra details. >> >> In [1]: import theano >> ERROR (theano.gpuarray): Could not initialize pygpu, support disabled >> Traceback (most recent call last): >> File >> "/home/daniel/anaconda2/lib/python2.7/site-packages/theano/gpuarray/__init__.py" >> , line 164, in <module> >> use(config.device) >> File >> "/home/daniel/anaconda2/lib/python2.7/site-packages/theano/gpuarray/__init__.py" >> , line 151, in use >> init_dev(device) >> File >> "/home/daniel/anaconda2/lib/python2.7/site-packages/theano/gpuarray/__init__.py" >> , line 68, in init_dev >> context.cudnn_handle = dnn._make_handle(context) >> File >> "/home/daniel/anaconda2/lib/python2.7/site-packages/theano/gpuarray/dnn.py" >> , line 80, in _make_handle >> cudnn = _dnn_lib() >> File >> "/home/daniel/anaconda2/lib/python2.7/site-packages/theano/gpuarray/dnn.py" >> , line 67, in _dnn_lib >> raise RuntimeError('Could not find cudnn library (looked for v5[.1])' >> ) >> RuntimeError: Could not find cudnn library (looked for v5[.1]) >> >> This happens if I also set the device to be `cuda0` instead of `cuda`, >> and trying with `float32` instead of `float64`. >> >> >> >> >> On Friday, June 30, 2017 at 5:43:35 PM UTC-7, Pascal Lamblin wrote: >>> >>> Something weird seems to be happening: >>> - theano detects that cuDNN is available, in fact it called >>> _dnn_check_compile() and _dnn_check_version() successfully >>> - however, calling _dnn_lib() failed, which means ctypes did not manage >>> to find the cudnn library. >>> >>> Is /usr/local/cuda-8.0/lib64 in your LIBRARY_PATH (in addition to >>> LD_LIBRARY_PATH)? >>> >>> On Monday, June 19, 2017 at 6:16:37 PM UTC-4, nouiz wrote: >>>> >>>> Your cudnn.h file should not be in the lib64 directory, but in an >>>> include directory. Tensorflow does none standard stuff related to import >>>> and cause problem in other setup, but it seem to tolerate your non >>>> standard >>>> setup. Theano does the standard setup. >>>> >>>> You can use the Theano flag dnn.include_path and dnn.library_path to >>>> tell Theano where your cudnn.h and cudnn.so* files are. >>>> >>>> I did not see your last error in full. >>>> >>>> Le ven. 16 juin 2017 19:35, Daniel Seita <takesh...@gmail.com> a >>>> écrit : >>>> >>>>> Ack, sorry, half of my post got deleted! Hopefully you can still see >>>>> it (i can find it by looking at the original post but it's in a really >>>>> ugly >>>>> format, sorry). >>>>> >>>>> >>>>> >>>>> On Friday, June 16, 2017 at 4:33:20 PM UTC-7, Daniel Seita wrote: >>>>> >>>>>> I was running into some more difficulties, so I gave up on getting >>>>>> this to work and tried to uninstall and then reinstall Theano. Just to >>>>>> be >>>>>> extra clear, here is my setup: >>>>>> >>>>>> - Ubuntu 16.04 >>>>>> - Cuda 8.0, stored in `usr/local/cuda-8.0` >>>>>> - Titan X GPU with Pascal >>>>>> >>>>>> cuDNN is here: >>>>>> >>>>>> $ ls /usr/local/cuda-8.0/lib64/cudnn.h >>>>>> /usr/local/cuda-8.0/lib64/cudnn.h >>>>>> >>>>>> To verify that I can use my GPU I started this quick TensorFlow >>>>>> computation: >>>>>> >>>>>> In [1]: import tensorflow as tf >>>>>> >>>>>> In [2]: tf.__version__ >>>>>> Out[2]: '1.1.0' >>>>>> >>>>>> In [3]: tf.GPUOptions >>>>>> Out[3]: tensorflow.core.protobuf.config_pb2.GPUOptions >>>>>> >>>>>> In [4]: with tf.device('/gpu:0'): >>>>>> ...: a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, >>>>>> 3], name='a') >>>>>> ...: b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, >>>>>> 2], name='b') >>>>>> ...: c = tf.matmul(a,b) >>>>>> ...: >>>>>> >>>>>> In [5]: with tf.Session() as sess: >>>>>> ...: print(sess.run(c)) >>>>>> ...: >>>>>> 2017-06-16 16:10:54.402311: W tensorflow/core/platform/ >>>>>> cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to >>>>>> use SSE4.1 instructions, but these are available on your machine and >>>>>> could >>>>>> speed up CPU computations. >>>>>> 2017-06-16 16:10:54.402328: W >>>>>> tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library >>>>>> wasn't compiled to use SSE4.2 instructions, but these are available >>>>>> on your machine and could speed up CPU computations. >>>>>> 2017-06-16 16:10:54.402346: W tensorflow/core/platform/ >>>>>> cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to >>>>>> use AVX instructions, but these are available on your machine and could >>>>>> speed up CPU computations. >>>>>> 2017-06-16 16:10:54.402350: W >>>>>> tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library >>>>>> wasn't compiled to use AVX2 instructions, but these are available on >>>>>> your machine and could speed up CPU computations. >>>>>> 2017-06-16 16:10:54.402356: W tensorflow/core/platform/ >>>>>> cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to >>>>>> use FMA instructions, but these are available on your machine and could >>>>>> speed up CPU computations. >>>>>> 2017-06-16 16:10:54.527167: I >>>>>> tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful >>>>>> NUMA >>>>>> node read from SysFS had negative value (-1), but there must be at least >>>>>> one NUMA node, so returning NUMA node zero >>>>>> 2017-06-16 16:10:54.527553: I >>>>>> tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 >>>>>> with >>>>>> properties: >>>>>> name: TITAN X (Pascal) >>>>>> major: 6 minor: 1 memoryClockRate (GHz) 1.531 >>>>>> pciBusID 0000:01:00.0 >>>>>> Total memory: 11.90GiB >>>>>> Free memory: 11.38GiB >>>>>> 2017-06-16 16:10:54.527565: I >>>>>> tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 >>>>>> 2017-06-16 16:10:54.527568: I >>>>>> tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y >>>>>> 2017-06-16 16:10:54.527590: I >>>>>> tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating >>>>>> TensorFlow >>>>>> device (/gpu:0) -> (device: 0, name: TITAN X (Pascal), pci bus id: >>>>>> 0000:01:00.0) >>>>>> [[ 22. 28.] >>>>>> [ 49. 64.]] >>>>>> >>>>>> >>>>>> This looks like it indicates a successful GPU and/or cuDNN >>>>>> installation. >>>>>> >>>>>> Great, now let's install the *development version* of Theano. The >>>>>> instructions I'm following step-by-step: >>>>>> http://deeplearning.net/software/theano_versions/dev/install_ubuntu.html >>>>>> >>>>>> The first step seems t >>>>>> >>>>> -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.