Naive Tensorflow/GPU1 question

[Dougal Sutherland]

It works for me too, not in IPython. Try this:

CUDA_VISIBLE_DEVICES=5 python -c 'import tensorflow as tf;
tf.InteractiveSession()'

On Fri, May 12, 2017 at 4:55 PM Kirthevasan Kandasamy <kandasamy at cmu.edu>
wrote:

> No, I don't use iPython.
>
> On Fri, May 12, 2017 at 11:22 AM, <chiragn at andrew.cmu.edu> wrote:
>
>> Have you tried running it from with iPython notebook as an interactive
>> session?
>>
>> I am doing that right now and it works.
>>
>> Chirag
>>
>>
>> > Kirthevasan Kandasamy <kandasamy at cmu.edu> wrote:
>> >
>> >> Hi Predrag,
>> >>
>> >> I am re-running a tensorflow project on GPU1 - I haven't touched it in
>> >> 4/5
>> >> months, and the last time I ran it it worked fine, but when I try now I
>> >> seem to be getting the following error.
>> >>
>> >
>> > This is the first time I hear about it. I was under impression that GPU
>> > nodes were usable.  I am redirecting your e-mail to users at autonlab.org
>> > in the hope that somebody who is using TensorFlow on the regular basis
>> > can be of more help.
>> >
>> > Predrag
>> >
>> >
>> >
>> >
>> >> Can you please tell me what the issue might be or direct me to someone
>> >> who
>> >> might know?
>> >>
>> >> This is for the NIPS deadline, so I would appreciate a quick response.
>> >>
>> >> thanks,
>>
>> >> Samy
>> >>
>> >>
>> >> I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0
>> >> with
>> >> properties:
>> >> name: Tesla K80
>> >> major: 3 minor: 7 memoryClockRate (GHz) 0.8235
>> >> pciBusID 0000:05:00.0
>> >> Total memory: 11.17GiB
>> >> Free memory: 11.11GiB
>> >> I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0
>> >> I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0:   Y
>> >> I tensorflow/core/common_runtime/gpu/gpu_device.cc:838] Creating
>> >> TensorFlow
>> >> device (/gpu:0) -> (device: 0, name: Tesla K80, pci bus id:
>> >> 0000:05:00.0)
>> >> E tensorflow/stream_executor/cuda/cuda_dnn.cc:347] Loaded runtime CuDNN
>> >> library: 4007 (compatibility version 4000) but source was compiled with
>> >> 5103 (compatibility version 5100).  If using a binary install, upgrade
>> >> your
>> >> CuDNN library to match.  If building from sources, make sure the
>> library
>> >> loaded at runtime matches a compatible version specified during compile
>> >> configuration.
>> >> F tensorflow/core/kernels/conv_ops.cc:457] Check failed:
>> >> stream->parent()->GetConvolveAlgorithms(&algorithms)
>> >> run_resnet.sh: line 49: 22665 Aborted                 (core dumped)
>> >> CUDA_VISIBLE_DEVICES=$GPU python ../resnettf/resnet_main.py --data_dir
>> >> $DATA_DIR --max_batch_iters $NUM_ITERS --report_results_every
>> >> $REPORT_RESULTS_EVERY --log_root $LOG_ROOT --dataset $DATASET
>> --num_gpus
>> >> 1
>> >> --save_model_dir $SAVE_MODEL_DIR --save_model_every $SAVE_MODEL_EVERY
>> >> --skip_add_method $SKIP_ADD_METHOD --architecture $ARCHITECTURE
>> >> --skip_size
>> >> $SKIP_SIZE
>> >
>>
>>
>>
>
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