hanjun-dai / graphnn Goto Github PK

I followed your guidelines in README.md, but I encounter the following errors. I have no idea how to fix it. Can you help me?

I have tried v4.0.0 and v3.0.0, and both of them cant run properly on example/mnist.

when compiling graphnn with libfmt v3.0.0 got warning:

include/fmt/format.h(2591): warning: statement is unreachable

and while running mnist example later got error:

➜  mnist ✗ make -j
g++ -Wall -O3 -std=c++11 -DUSE_GPU -I/usr/local/cuda/include -I/opt/intel/mkl/include -I../../include -Iinclude -o build/mnist mnist.cpp ../../build/lib/libgnn.a -L../../build/lib -lgnn -lm -L/usr/local/cuda/lib64 -lcudart -lcublas -lcurand -lcusparse -lmkl_rt -lfmt
/usr/bin/ld: cannot find -lfmt
collect2: error: ld returned 1 exit status
Makefile:21: recipe for target 'build/mnist' failed
make: *** [build/mnist] Error 1

I am getting the following errors when running make -j8

/usr/include/tbb/concurrent_vector.h(667): error: ambiguous "?" operation: second operand of type "tbb::internal::concurrent_vector_base_v3::size_type" can be converted to third operand type "tbb::atomic", and vice versa

/usr/include/tbb/concurrent_vector.h(680): error: ambiguous "?" operation: second operand of type "tbb::internal::concurrent_vector_base_v3::size_type" can be converted to third operand type "tbb::atomic", and vice versa

2 errors detected in the compilation of "/tmp/tmpxft_00000897_00000000-4_gpu_handle.cpp4.ii".
make: *** [build/objs/cuda/tensor/gpu_handle.o] Error 2

Is there some potential compatability issues of cuda or centos ?

Hello, I ran the following code in s2v_mvc and got the error. Is it because the version of python? i am using python 3.5 How to fix it? Thanks.

graph_comb/code/s2v_mvc$ ./run_nstep_dqn.sh
Traceback (most recent call last):
File "main.py", line 78, in
api = MvcLib(sys.argv)
File "/graph_comb/code/s2v_mvc/mvc_lib/mvc_lib.py", line 18, in init
arr[:] = args
TypeError: bytes or integer address expected instead of str instance

I tried to build this project but error occurs:

find: -printf: unknown primary or operator
find: -printf: unknown primary or operator
find: -printf: unknown primary or operator
find: -printf: unknown primary or operator
find: -printf: unknown primary or operator
ar rcs build_cpuonly/lib/libgnn.a
ar: no archive members specified

I tried to delete all -printf in Makefile but another error occurs:

make: *** No rule to make target build_cpuonly/objs/cxx/src//nn/hit_at_k.o', needed by build_cpuonly/lib/libgnn.a'. Stop.

I tried to install findutils as suggested by this but it wouldn't work.

I think this is a trivial error that can be easily solved. However it seems that nobody has occurred the same issue.

Can anybody provide some instructions? Thanks!

error in open: /usr/local/cuda/bin/../nvvm/libdevice/libdevice.compute_50.10.bc
No such file or directory
Makefile:47: recipe for target 'build/objs/cuda/nn/cross_entropy.o' failed
make: *** [build/objs/cuda/nn/cross_entropy.o] Error 1

I have problems in Build Static Library section,
modify configurations in make_common file
make -j8
these two commands do not work: do not find the modify command, what's the problem?

I am trying to build this package on my virtual machine:

• Ubuntu 16.04
• No GPU (hence no CUDA)
  I have already installed Intel Parallel Studio XE 2018.

Here is the details of the error message I get:

g++ -Wall -O3 -std=c++11 -I/include -I/data/util/intel/mkl/include -I/data/util/intel/tbb/include -Iinclude -fPIC -MMD -c -o build_cpuonly/objs/cxx/nn/one_hot.o src/nn/one_hot.cpp
g++ -Wall -O3 -std=c++11 -I/include -I/data/util/intel/mkl/include -I/data/util/intel/tbb/include -Iinclude -fPIC -MMD -c -o build_cpuonly/objs/cxx/nn/variable.o src/nn/variable.cpp
g++ -Wall -O3 -std=c++11 -I/include -I/data/util/intel/mkl/include -I/data/util/intel/tbb/include -Iinclude -fPIC -MMD -c -o build_cpuonly/objs/cxx/nn/square_error.o src/nn/square_error.cpp
g++ -Wall -O3 -std=c++11 -I/include -I/data/util/intel/mkl/include -I/data/util/intel/tbb/include -Iinclude -fPIC -MMD -c -o build_cpuonly/objs/cxx/nn/is_equal.o src/nn/is_equal.cpp
src/nn/one_hot.cpp: In instantiation of ‘void gnn::OneHot<mode, Dtype>::Forward(std::vector<std::shared_ptrgnn::Variable >&, std::vector<std::shared_ptrgnn::Variable >&, gnn::Phase) [with mode = gnn::CPU; Dtype = float]’:
src/nn/one_hot.cpp:54:1: required from here
src/nn/one_hot.cpp:43:9: error: ‘memcpy’ was not declared in this scope
memcpy(output.data->row_ptr, idxes.data(), sizeof(int) * idxes.size());
^
src/nn/one_hot.cpp:44:9: error: ‘memcpy’ was not declared in this scope, and no declarations were found by argument-dependent lookup at the point of instantiation [-fpermissive]
memcpy(output.data->col_idx, input.data->ptr, sizeof(int) * input.rows());
^
src/nn/one_hot.cpp:43:9: note: ‘memcpy’ declared here, later in the translation unit
memcpy(output.data->row_ptr, idxes.data(), sizeof(int) * idxes.size());
^
src/nn/one_hot.cpp: In instantiation of ‘void gnn::OneHot<mode, Dtype>::Forward(std::vector<std::shared_ptrgnn::Variable >&, std::vector<std::shared_ptrgnn::Variable >&, gnn::Phase) [with mode = gnn::CPU; Dtype = double]’:
src/nn/one_hot.cpp:54:1: required from here
src/nn/one_hot.cpp:43:9: error: ‘memcpy’ was not declared in this scope
src/nn/one_hot.cpp:44:9: error: ‘memcpy’ was not declared in this scope, and no declarations were found by argument-dependent lookup at the point of instantiation [-fpermissive]
memcpy(output.data->col_idx, input.data->ptr, sizeof(int) * input.rows());
^
src/nn/one_hot.cpp:43:9: note: ‘memcpy’ declared here, later in the translation unit
memcpy(output.data->row_ptr, idxes.data(), sizeof(int) * idxes.size());
^
Makefile:53: recipe for target 'build_cpuonly/objs/cxx/nn/one_hot.o' failed

I tried to run the mnist example but there was an error:

./run.sh
60000 images for training
10000 images for test
testing
Assertion `isReady[VarIdx(p)]` failed in src/nn/factor_graph.cpp line 170: required variable ReduceMean_7:out_0 is not ready

I also found the similar error with graph classification example

Assertion `isReady[VarIdx(p)]` failed in src/nn/factor_graph.cpp line 170: required variable ReduceMean_21:out_0 is not ready

Any idea what the problem is?

I run the graph_classification example program and can get the results 

on accuracy and loss. Is it possible to directly get the predicted result?
The probabilities or the labels of the results. I tried to push
the output into targets by adding
targets.push_back(output);
at https://github.com/Hanjun-Dai/graphnn/blob/master/examples/graph_classification/src/kernel_mean_field.cpp#L61.

When retrieve the results, use
dynamic_cast<TensorTemplate<mode, DENSE, Dtype>*>(t.get())->Serialize(outfile);
at line https://github.com/Hanjun-Dai/graphnn/blob/master/examples/graph_classification/include/nn_common.h#L167.

Also I did some other little changes to make sure the first two elements are scalars and the newly-added element is tensor.

But this does not work well. It can create the outfile. But it is empty inside the file. Is there any suggestions on this? I plan to get the outputs and compute the AUC scores for the classification task.

I have already install fmt in the directory /usr/local/include. But when I $make, it reported error:‘sprintf’ is not a member of ‘fmt’. What happens and how can I fix it?Thanks a lot if you could share some advice!

Hello,
I can run mnist successfully, but met error when i run graph_classificationas follow:

Can anybody help me ? Thanks!

In your paper, there are two schemes:

• mean field
• loopy belief propagation

in example of graph_classification, there is only implementation of mean field.

loopy belief propagation contains two phases:

• v_i_j, message from i to j, gather all i's neighbor messages, except from j
• v_i, message from all i's neighbor, plus its own message

I am curious about how to efficiently calculate v_i_j. Unlike mean field, it simply do matrix multiplication. But loopy belief propagation is some what complicated and it is not easy because we need to remove neighbor j when we calculate v_i_j. Of course, we can implement it by just set i's neighbor j to zero, when calculate v_i_j, but it is not efficient.

So any hint on that?

hi, when i make your latest version code, i meet an error

Makefile:21: recipe for target 'build/mnist' failed
make: *** [build/mnist] Error 1

can you tell tell me how to fix this? Thanks.

line 46 in graphnn/src/nn/l2_col_norm.cpp

should it be ElewiseMul?

I just followed the docker instructions and built, ran it; however, I coundn't found the /opt/intel or MKL installed in my server, mybe it installed in my docker, but how could I find the path to change the makefile. Could you please give me some suggestions,thx!

As volume of data is increasing. I am curious is there any plan for a distributed version of graphnn?

i followed the instruction and come to this error

Hi, I am trying to implement it. However, in the step of "building static library". I encounter a problem. When I type "make", the computer cannot find the file thrust/device_vector.h.

Also you wrote "modify configurations in make_common", you mean we go into the file to change the configurations right? You do not mean I literally type in "modify configurations in make_common" right? (I tried to do that, the shell gives me a message "modify: command not found")

What is the format of the graph datasets used in the examples?
Is the txt file the adjacency list of the graph?

Thanks

src/nn/row_selection.cpp:3:21: fatal error: tbb/tbb.h: 没有那个文件或目录
#include "tbb/tbb.h"
^
compilation terminated.
Makefile:53: recipe for target 'build/objs/cxx/nn/row_selection.o' failed

hi, when i make your latest version code, i meet an error like:"src/nn/row_selection.cpp:3:21: fatal error: tbb/tbb.h: No such file or directory". So i want to ask you, which version of tbb do you used? could you give me the installation tutorial?

I tried to run the make, but it gives the error of cannot found mkl.h
Is it missing? Or should we create it?

Here is the error I got

g++ -Wall -O3 -std=c++11 -I/usr/local/cuda/include -I/home/abcde/anaconda2/lib/include -Iinclude -fPIC -DUSE_GPU -MMD -c -o build/objs/cxx/tensor/cpu_dense_tensor.o src/tensor/cpu_dense_tensor.cpp In file included from src/tensor/cpu_dense_tensor.cpp:5:0: include/tensor/mkl_helper.h:4:17: fatal error: mkl.h: No such file or directory compilation terminated. Makefile:53: recipe for target 'build/objs/cxx/tensor/cpu_dense_tensor.o' failed make: *** [build/objs/cxx/tensor/cpu_dense_tensor.o] Error 1

I have downloaded MKL and modified the make_common file to point to the directory however I am still getting a fatal error

-o build/objs/cxx/nn/tanh.o src/nn/tanh.cpp
g++ -Wall -O3 -std=c++11 -I/usr/local/cuda/include -I/usr/parallel_studio_xe_2020/compilers_and_libraries_2020/linux/mkl/include -I/usr/parallel_studio_xe_2020/compilers_and_libraries_2020/linux/tbb/include -Iinclude -fPIC -DUSE_GPU -MMD -c -o build/objs/cxx/nn/matmul.o src/nn/matmul.cpp
In file included from src/tensor/cpu_row_sparse_tensor.cpp:5:0:
include/tensor/mkl_helper.h:4:17: fatal error: mkl.h: No such file or directory
#include <mkl.h>
^
compilation terminated.
In file included from src/tensor/cpu_dense_tensor.cpp:6:0:
include/tensor/mkl_helper.h:4:17: fatal error: mkl.h: No such file or directory
#include <mkl.h>
^
compilation terminated.
In file included from src/nn/jagged_softmax.cpp:2:0:
include/tensor/mkl_helper.h:4:17: fatal error: mkl.h: No such file or directory
#include <mkl.h>

My make_common file is

INTEL_ROOT := /usr/parallel_studio_xe_2020/compilers_and_libraries_2020/linux
MKL_ROOT = $(INTEL_ROOT)/mkl
TBB_ROOT = $(INTEL_ROOT)/tbb
USE_GPU = 1

Thanks for your reply. I follow your guide, when I build static library.
I meet fatal error: tbb/tbb.h :No such file or directory

I don't know why and how to solve it.
I hope that you could help me.
Thank you!

^

Hi there,
I'm using Ubuntu 18.04 and planning to install an upper version of CUDA, therefore I have gone in the way to replicate the experiments of this study in a Docker image. After I have built all the workspace and executed ./run.sh in examples/mnist I get thrust:system_error unknown error.

Have you ever received this error in a host machine or in a Docker image?

/usr/bin/ld: 找不到 -lmkl_rt
/usr/bin/ld: 找不到 -ltbb
collect2: error: ld returned 1 exit status

Hello,

Thank you very much for your very interesting paper and code!
I have been trying to apply your method and in particular, I was hoping to study the output of the Embedded Mean Field algorithm (algorithm 1) of your paper. I admit to being a little lost with all of the classes and types: I was wondering if there was any way of saving each of the node embeddings to a txt file (before they are collapsed for graph embedding)?
Thank you very much for your time and help!
Best regards,

Claire

Hi. I tried to run the graph classification example but I experienced the following error:

Assertion isReady[VarIdx(p)] failed in src/nn/factor_graph.cpp line 173: required variable ReduceMean_21:out_0 is not ready

I'm trying to run the code on Ubuntu 16.04 and I read from another closed issue that it maybe could be the problem.

I follow your build guide, to do make -j, but it has the below error.

I do not know how to solve it.