I have a project that need to use tensorflow model and pytorch model at the same time. When tf model do inference, it caused
2019-01-13 13:48:27.819434: E tensorflow/stream_executor/cuda/cuda_dnn.cc:378] Loaded runtime CuDNN library: 7102 (compatibility version 7100) but source was compiled with 6021 (co mpatibility version 6000).  If using a binary install, upgrade your CuDNN library to match.  If building from sources, make sure the library loaded at runtime matches a compatibleversion specified during compile configuration.
2019-01-13 13:48:27.819986: F tensorflow/core/kernels/conv_ops.cc:667] Check failed: stream->parent()->GetConvolveAlgorithms(conv_parameters.ShouldIncludeWinogradNonfusedAlgo<T>() , &algorithms)

But the cudnn version on my local version is:
#define CUDNN_MAJOR      5
#define CUDNN_MINOR      1
#define CUDNN_PATCHLEVEL 10
···
#define CUDNN_VERSION    (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)

#include "driver_types.h"

my pytorch version is 0.4.1. tensorflow version is 1.4.0
It may caused by pytorch autoload cudnn in its version.
How to avoid this problem ?