Code Monkey home page Code Monkey logo

Comments (3)

cuongth95 avatar cuongth95 commented on June 1, 2024

Hallo Sugandhrise,

The reason depends on network-by-network.
In designing INP, the designer (creation software) often adds auxiliary nodes/ edges. You need to clean the INP file or isolate "unused" nodes and edges in code before generating datasets or training models.
If the INP file is available, we are happy to help.

Cheers.

from gnn-pressure-estimation.

sugandhrise avatar sugandhrise commented on June 1, 2024

Hallo Sugandhrise,

The reason depends on network-by-network. In designing INP, the designer (creation software) often adds auxiliary nodes/ edges. You need to clean the INP file or isolate "unused" nodes and edges in code before generating datasets or training models. If the INP file is available, we are happy to help.

Cheers.

Hey Huy,

I have tried it on Net1.inp from https://github.com/KIOS-Research/epanet-function-test/blob/master/Net1.inp and C-Town.inp from https://www.batadal.net/data/CTOWN.INP.

Could you please elaborate more on what you mean by unused nodes and edges?

Thanks

from gnn-pressure-estimation.

sugandhrise avatar sugandhrise commented on June 1, 2024

Update: I used the same .zip file for dataset_paths and test_data_path and the same .inp file for input paths and test_input_path, so the command for executing train.py became this (notice it's only NET.zip and NET.inp):

python train.py --model gatres_small --epochs 500 --batch_size 8 --device 'cuda' --mask_rate 0.95 --dataset_paths /home/sugandh/gnn2/gnn-pressure-estimation/datasets/NET/datasets/NET.zip --input_paths /home/sugandh/gnn2/gnn-pressure-estimation/inputs/NET.inp --save_path /home/sugandh/Downloads/ --test_data_path /home/sugandh/gnn2/gnn-pressure-estimation/datasets/NET/datasets/NET.zip --test_input_path /home/sugandh/gnn2/gnn-pressure-estimation/inputs/NET.inp

and I got this error:

Traceback (most recent call last):
  File "/home/sugandh/gnn2/gnn-pressure-estimation/train.py", line 611, in <module>
    train(args, model=model, do_load=False)
  File "/home/sugandh/gnn2/gnn-pressure-estimation/train.py", line 520, in train
    train_ds, val_ds, test_ds = get_default_datasets(args)
  File "/home/sugandh/gnn2/gnn-pressure-estimation/train.py", line 86, in get_default_datasets
    test_ds = get_stacked_set(zip_file_path=args.test_data_path,  # fullnode
  File "/home/sugandh/gnn2/gnn-pressure-estimation/utils/DataLoader.py", line 440, in get_stacked_set
    test_train_ds = WDNDataset(zip_file_paths=[zip_file_path],
  File "/home/sugandh/gnn2/gnn-pressure-estimation/utils/DataLoader.py", line 127, in __init__
    graph_template, array, keep_list = self.collect(input_path, zip_file_path, feature, edge_attrs, removal,
  File "/home/sugandh/gnn2/gnn-pressure-estimation/utils/DataLoader.py", line 252, in collect
    array = np.take(array, taken_indices, axis=-1)
  File "/home/sugandh/anaconda3/envs/gnn/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 192, in take
    return _wrapfunc(a, 'take', indices, axis=axis, out=out, mode=mode)
  File "/home/sugandh/anaconda3/envs/gnn/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 59, in _wrapfunc
    return bound(*args, **kwds)
IndexError: index 10 is out of bounds for axis 1 with size 10

When I started digging into the code, I think the error is introduced in DataLoader.py due to the variables "taken_indices" and "array" having the wrong sizes (again difference of 1 in their lengths). Or the error is being introduced in the data generation phase itself.

from gnn-pressure-estimation.

Related Issues (3)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.