Open ghost opened 4 years ago
@Byron309 I can run the code with Tensorflow-gpu 1.14. Before running the train script, I set export GPU=0
and export CUDA_VISIBLE_DEVICES=0
.
Hi, @Damcy Thank you for your reply.
I try tf-gpu==1.14 and I have run setup_all.sh. but I get the error "tensorflow.python.framework.errors_impl.NotFoundError: ./coref_kernels.so: undefined symbol: _ZTIN10tensorflow8OpKernelE"
Did you meet this problem?
I'm trying the E2E method and not the high-order method.
The cmd in setup_all.sh may be out-of-date.
You can change
g++ -std=c++11 -shared coref_kernels.cc -o coref_kernels.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2 -D_GLIBCXX_USE_CXX11_ABI=0
into
g++ -std=c++11 -shared coref_kernels.cc -o coref_kernels.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2
if your gcc version is higher than 4.8.3 (I guess).
Then it can generate a correct .so file.
Hi, @Damcy
Thanks for your help. But I didn't find the command g++ -std=c++11 -shared coref_kernels.cc -o coref_kernels.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2 -D_GLIBCXX_USE_CXX11_ABI=0
in the setup_all.sh.
Also I try the command g++ -std=c++11 -shared coref_kernels.cc -o coref_kernels.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2
, but get another error:
coref_kernels.cc:4:10: fatal error: tensorflow/core/framework/op.h: No such file or directory
#include "tensorflow/core/framework/op.h"
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
Have you met this error before?
g++ -std=c++11 -shared coref_kernels.cc -o coref_kernels.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2 -D_GLIBCXX_USE_CXX11_ABI=0
is line 13 in the setup_all.sh
I didn't meet this error before. I think you can make some modifications from setup_all.sh in the high-order repo.
It works! thank you!
Somehow the setup_all.sh file we are talking about is different. I try the file you share and it works.
Hi, I'm trying to run E2E method on GPU. While I noticed that code requires TensorFlow 1.0.0. How can I run it on GPU? I have already set the environment GPU=0 while it seems there is no tensorflow-GPU to allocate it.