【DGLError】dgl._ffi.base.DGLError:Check failed: fs: Filename is invalid

[ChloeWongxt]

Run pre-training example fails.

When i run wit this code

There are some troubles with it.

I don`t have any idea with what happens. Could you help me? thanks a lot.

paper`s name:GCC: Graph Contrastive Coding for Graph Neural NetworkPre-Training
paper:https://arxiv.org/abs/2006.09963
code:https://github.com/THUDM/GCC

Error

(GCC01) chloe@chloe-MS-7A74:~/Documents/00 Work/02 Xovee/01 Code/GCC$ bash scripts/pretrain.sh 0 --batch-size 256
Using backend: pytorch
Namespace(alpha=0.999, aug='1st', batch_size=256, beta1=0.9, beta2=0.999, clip_norm=1.0, cv=False, dataset='dgl', degree_embedding_size=16, epochs=100, exp='Pretrain', finetune=False, fold_idx=0, freq_embedding_size=16, gpu=0, hidden_size=64, learning_rate=0.005, load_path=None, lr_decay_epochs=[120, 160, 200], lr_decay_rate=0.0, max_degree=512, max_edge_freq=16, max_node_freq=16, moco=False, model='gin', model_folder='saved/Pretrain_moco_False_dgl_gin_layer_5_lr_0.005_decay_1e-05_bsz_256_hid_64_samples_2000_nce_t_0.07_nce_k_32_rw_hops_256_restart_prob_0.8_aug_1st_ft_False_deg_16_pos_32_momentum_0.999', model_name='Pretrain_moco_False_dgl_gin_layer_5_lr_0.005_decay_1e-05_bsz_256_hid_64_samples_2000_nce_t_0.07_nce_k_32_rw_hops_256_restart_prob_0.8_aug_1st_ft_False_deg_16_pos_32_momentum_0.999', model_path='saved', momentum=0.9, nce_k=32, nce_t=0.07, norm=True, num_copies=6, num_layer=5, num_samples=2000, num_workers=12, optimizer='adam', positional_embedding_size=32, print_freq=10, readout='avg', restart_prob=0.8, resume='', rw_hops=256, save_freq=1, seed=0, set2set_iter=6, set2set_lstm_layer=3, subgraph_size=128, tb_folder='tensorboard/Pretrain_moco_False_dgl_gin_layer_5_lr_0.005_decay_1e-05_bsz_256_hid_64_samples_2000_nce_t_0.07_nce_k_32_rw_hops_256_restart_prob_0.8_aug_1st_ft_False_deg_16_pos_32_momentum_0.999', tb_freq=250, tb_path='tensorboard', weight_decay=1e-05)
Use GPU: 0 for training
setting random seeds
before construct dataset 6.249996185302734
Traceback (most recent call last):
File "train.py", line 818, in
main(args)
File "train.py", line 555, in main
num_copies=args.num_copies
File "/home/chloe/Documents/00 Work/02 Xovee/01 Code/GCC/gcc/datasets/graph_dataset.py", line 58, in init
graph_sizes = dgl.data.utils.load_labels(dgl_graphs_file)[
File "/home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/data/graph_serialize.py", line 172, in load_labels
metadata = _CAPI_DGLLoadGraphs(filename, [], True)
File "dgl/_ffi/_cython/./function.pxi", line 287, in dgl._ffi._cy3.core.FunctionBase.call
File "dgl/_ffi/_cython/./function.pxi", line 222, in dgl._ffi._cy3.core.FuncCall
File "dgl/_ffi/_cython/./function.pxi", line 211, in dgl._ffi._cy3.core.FuncCall3
File "dgl/_ffi/_cython/./base.pxi", line 155, in dgl._ffi._cy3.core.CALL
dgl._ffi.base.DGLError: [21:41:01] /opt/dgl/src/graph/graph_serialize.cc:193: Check failed: fs: Filename is invalid
Stack trace:
[bt] (0) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/libdgl.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x22) [0x7fbe9e1ec782]
[bt] (1) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/libdgl.so(dgl::serialize::LoadDGLGraphs(std::string const&, std::vector<unsigned long, std::allocator >, bool)+0xe7c) [0x7fbe9e859a5c]
[bt] (2) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/libdgl.so(+0xd1f0eb) [0x7fbe9e85a0eb]
[bt] (3) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/libdgl.so(DGLFuncCall+0x52) [0x7fbe9e7f46e2]
[bt] (4) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/_ffi/_cy3/core.cpython-37m-x86_64-linux-gnu.so(+0x19cdb) [0x7fbef63a5cdb]
[bt] (5) /home/chloe/anaconda3/envs/GCC01/lib/python3.7/site-packages/dgl/_ffi/_cy3/core.cpython-37m-x86_64-linux-gnu.so(+0x1a25b) [0x7fbef63a625b]
[bt] (6) python(_PyObject_FastCallKeywords+0x48b) [0x55db603c900b]
[bt] (7) python(_PyEval_EvalFrameDefault+0x49b6) [0x55db6042d186]
[bt] (8) python(_PyFunction_FastCallKeywords+0xfb) [0x55db603c120b]

##Environment

scikit-learn==0.20.3
scipy==1.4.1
coverage==4.5.4
coveralls==1.9.2
black==19.3b0
pytest==5.3.2
networkx==2.3
numpy==1.18.2
matplotlib==3.1.0
seaborn==0.9.0
tqdm==4.43.0
tensorboard_logger==0.1.0

torch~=1.5.1
dgl~=0.4.3.post2
pandas~=1.0.5
requests~=2.24.0
psutil~=5.7.2
joblib~=0.16.0

Python:3.7
PyTorch 1.5.1
DGL 0.4.1
rdkit=2019.09.2.

[qibinc]

Hi @ChloeWongxt ,

Looks like the error happened when loading the pretraining dataset file. Did you successfully download it by following this step?

[ChloeWongxt]

Hi @ChloeWongxt ,

Looks like the error happened when loading the pretraining dataset file. Did you successfully download it by following this step?

My connection to cloud.tsinghua.edu.cn is ok.
But when i use the following code i can`t download the pre-training datasets, at the same time Google is not accessible.
How can i download the pre-training datasets? I am looking forward to your reply.

python scripts/download.py --url https://cloud.tsinghua.edu.cn/f/b37eed70207c468ba367/?dl=1 --path data --fname small.bin

[ChloeWongxt]

Hi @ChloeWongxt ,

Looks like the error happened when loading the pretraining dataset file. Did you successfully download it by following this step?

I can`t download the pretraining dataset file, at the same time Google is not accessible.

(GCC-double) chloe@chloe-MS-7A74:~/Documents/00 Work/02 Xovee/01 Code/GCC$ python scripts/download.py --url https://cloud.tsinghua.edu.cn/f/b37eed70207c468ba367/?dl=1 --path data --fname small.bin
[ downloading: https://cloud.tsinghua.edu.cn/f/b37eed70207c468ba367/?dl=1 to data/small.bin ]
Downloading small.bin: 0.00B [00:00, ?B/s]

[ChloeWongxt]

I finally deal with this question.Yea~~~

line 554 of file train.py
the datasets` path is

dgl_graphs_file="./data_bin/dgl/small.bin",

but when we download the pretraining dataset as the following step

python scripts/download.py --url https://drive.google.com/open?id=1JCHm39rf7HAJSp-1755wa32ToHCn2Twz --path data --fname small.bin
# For regions where Google is not accessible, use
# python scripts/download.py --url https://cloud.tsinghua.edu.cn/f/b37eed70207c468ba367/?dl=1 --path data --fname small.bin

the pretraing file will be ./data/small.bin

so the solution of this question is that you should new folder as this path ./data_bin/dgl/ and remove the file small.bin in this new folder, Or you can change the line 554 of file train.py as following

dgl_graphs_file="./data/small.bin"

I have spent 4 days to deal with it, even though this is a small question.
But i am so happy to deal with this question. Because at the process of dealing with it, i improved a lot.