How should I solve this error?
$ python tensorboard_viz.py
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
2018-10-24 19:49:39.925967: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-10-24 19:49:40.093637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:05:00.0
totalMemory: 10.92GiB freeMemory: 10.03GiB
2018-10-24 19:49:40.238084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 1 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:06:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2018-10-24 19:49:40.238960: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1490] Adding visible gpu devices: 0, 1
2018-10-24 19:49:41.287661: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-10-24 19:49:41.287712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] 0 1
2018-10-24 19:49:41.287733: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0: N Y
2018-10-24 19:49:41.287748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 1: Y N
2018-10-24 19:49:41.288287: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1103] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9694 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:05:00.0, compute capability: 6.1)
2018-10-24 19:49:41.434704: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1103] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 10405 MB memory) -> physical GPU (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:06:00.0, compute capability: 6.1)
2018-10-24 19:49:44.406950: E tensorflow/stream_executor/cuda/cuda_dnn.cc:343] Loaded runtime CuDNN library: 7.0.5 but source was compiled with: 7.2.1. CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
Segmentation fault
Can you please provide the correct commands for doing so?
I had this same problem, following approach works fine
Note: I am using 'pip3' because I was working with python-3.x, you can use 'pip' instead if you are working with python-2.x
I had the same problem and I solved it by installing the CuDNN library suggested in the traceback (Loaded runtime cuDNN library: 7.0.5 but source was compiled with: 7.2.1.)
I replaced the cuDNN version with cuDNN v7.2.1 (August 7, 2018), for CUDA 9.2 and it works for me. This way you can maintain your tensorflow-gpu version.
You can get the library from the cuDNN Archive: https://developer.nvidia.com/rdp/cudnn-archive
Ensure your whole configuration matches one of the tested built configurations: https://www.tensorflow.org/install/source_windows#tested_build_configurations https://www.tensorflow.org/install/source#tested_build_configurations
Please type this in terminal....problem is with Tensorflow version
sudo pip install --upgrade --force-reinstall tensorflow-gpu==1.9.0