Closed wangzeyu135798 closed 3 years ago
Hi, @wangzeyu135798,
The code should automatically download the dataset at the first run if you download the correct dependencies. Please feel free to drop questions if it still not works.
你好: 感谢你的回复! 在运行你的github代码的时候,在semisupervised_TU/pre-training/tu_dataset.py line 50 报错,错误为不存在.pt文件。 我想问下代码在自动下载数据的时候包括相关的.pt文件吗?我看到你的这个项目在github网页上提到了gfn-master,对于gfn-master这套代码,我也遇到了相关的问题。
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年10月30日(星期五) 晚上9:36 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Hi, @wangzeyu135798,
The code should automatically download the dataset at the first run if you download the correct dependencies. Please feel free to drop questions if it still not work.
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包括的。他会自动下载数据,然后预处理成.pt文件。需要torch-geometric版本之类的正确才行。
I make an update to provide the conda environment file that might help you collect the required dependencies. Please see https://github.com/Shen-Lab/GraphCL/tree/master/semisupervised_TU#option-2.
Any other questions feel free to drop here. Thanks.
Hi: After reading you data, I have two questions. First, is one positive pair is the same graph data instance augmented in two aspects? Second, when calculating the loss, line res_gcn.py line 233, loss = pos_sim / (sim_matrix.sum(dim=1)) - pos_sim - self_sim, while in paper equation(3) the last two components(pos_sim and self_dim) are lost, why? I hope your reply. Thanks.
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年11月5日(星期四) 晚上10:59 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Hi @wangzeyu135798,
I make an update to provide the conda environment file that might help you collect the required dependencies. Please see https://github.com/Shen-Lab/GraphCL/tree/master/semisupervised_TU#option-2.
Any other questions feel free to drop here. Thanks.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
Hi: When I run the finetuning step, there is a code error. In semisupervised_TU/finetuning/traineval.py line 181, for , idx in skf_semi.split(torch.zeros(idx_train.size()[0]), dataset[idx_trian].data.y) ValueError: Found input variables with inconsistent numbers of samples: [3699, 4110] How to solve it? Thanks.
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年11月5日(星期四) 晚上10:59 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Hi @wangzeyu135798,
I make an update to provide the conda environment file that might help you collect the required dependencies. Please see https://github.com/Shen-Lab/GraphCL/tree/master/semisupervised_TU#option-2.
Any other questions feel free to drop here. Thanks.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
你好: 还有一个问题。在semisupervised-TU/fine-tuning/train_eval.py 里面,调用train函数的时候是在进行有监督训练,那么此时的model不也应该被保存吗?在代码中没有看到调用train函数时模型被save。
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年11月5日(星期四) 晚上10:59 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Hi @wangzeyu135798,
I make an update to provide the conda environment file that might help you collect the required dependencies. Please see https://github.com/Shen-Lab/GraphCL/tree/master/semisupervised_TU#option-2.
Any other questions feel free to drop here. Thanks.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
First, is one positive pair is the same graph data instance augmented in two aspects?: Yes.
_Second, when calculating the loss, line res_gcn.py line 233, loss = pos_sim / (sim_matrix.sum(dim=1)) - pos_sim - self_sim, while in paper equation(3) the last two components(pos_sim and selfdim) are lost, why? Thanks for pointing it out. The denominator in formulation should be corrected as sum_{k=1, k!=i}^N xxx.
ValueError: Found input variables with inconsistent numbers of samples: [3699, 4110] Would you mind sharing your environment.yml file that I can double-check? Thanks.
_还有一个问题。在semisupervised-TU/fine-tuning/traineval.py 里面,调用train函数的时候是在进行有监督训练,那么此时的model不也应该被保存吗?在代码中没有看到调用train函数时模型被save。 In finetuning I only saved the results before since the overall results are 10- or 100-fold evaluation with 5 runs. Of course, you can make small modification in code to save the models.
Hope my answers can help you.
你好: 我现在在看你的这篇文章When Does Self-Supervision Help Graph Convolutional Networks? 在看到Graph partition的时候,对应代码里用到了metis的一个分割图的函数metis.part_graph, 对于metis这个包,我直接pip install metis,安装0.2a4这个版本,运行后报错RuntimeError: Could not locate METIS dll. Please set the METIS_DLL environment variable to its full path.我一直没有找到解决方案。我现在的环境是windows,请问你当时是怎么安装的这个包?
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年11月10日(星期二) 凌晨5:38 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Thanks @wangzeyu135798,
First, is one positive pair is the same graph data instance augmented in two aspects?: Yes.
Second, when calculating the loss, line res_gcn.py line 233, loss = pos_sim / (sim_matrix.sum(dim=1)) - pos_sim - self_sim, while in paper equation(3) the last two components(pos_sim and selfdim) are lost, why? Thanks for pointing it out. The denominator in formulation should be corrected as sum{k=1, k!=i}^N xxx.
ValueError: Found input variables with inconsistent numbers of samples: [3699, 4110] Would you mind sharing your environment.yml file that I can double-check? Thanks.
还有一个问题。在semisupervised-TU/fine-tuning/train_eval.py 里面,调用train函数的时候是在进行有监督训练,那么此时的model不也应该被保存吗?在代码中没有看到调用train函数时模型被save。 In finetuning I only saved the results before since the overall results are 10- or 100-fold evaluation with 5 runs. Of course, you can make small modification in code to save the models.
Hope my answers can help you.
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Please follow the dependencies part https://github.com/Shen-Lab/SS-GCNs#dependencies that pip install
only provide your the API between python and METIS, but you also need to install METIS such that python can call METIS.
In https://github.com/Shen-Lab/SS-GCNs#dependencies for Linux thus we need to run sudo apt-get install libmetis-dev
.
Hi: Under SS-GCN/cluster_labels, there are three .npy files. I want to learn how to make these npy files?
------------------ 原始邮件 ------------------ 发件人: "Shen-Lab/GraphCL" <notifications@github.com>; 发送时间: 2020年11月12日(星期四) 晚上11:22 收件人: "Shen-Lab/GraphCL"<GraphCL@noreply.github.com>; 抄送: "天津工业大学王泽宇"<1051533398@qq.com>;"Mention"<mention@noreply.github.com>; 主题: Re: [Shen-Lab/GraphCL] Code (#1)
Hi @wangzeyu135798,
Please follow the dependencies part https://github.com/Shen-Lab/SS-GCNs#dependencies that pip install only provide your the API between python and METIS, but you also need to install METIS such that python can call METIS.
In https://github.com/Shen-Lab/SS-GCNs#dependencies for Linux thus we need to run sudo apt-get install libmetis-dev.
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Please see the bottom of this README.md https://github.com/Shen-Lab/SS-GCNs/tree/master/SS-GCNs#training--evaluation.
Hi: In GraphCL/semisupervised_TU/pre-training/ I take NCI1 as an example as you stated, run CUDA_VISIBLE_DEVICES=$GPU_ID python main.py --dataset NCI1 --aug1 random2 --aug2 random2 --lr 0.001 --suffix 0. There is an error that "No such file or directory: data/NCI1/NCI1/processed/data_deg+odeg100.pt". How could I get the file data_deg+odeg100.pt? Should I run another code before getting .pt file?