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Asgat

Pytorch benchmarking source code for decimation model

Install / Use

/learn @seanli3/Asgat
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

ASGAT

Installation

You can install the dependencies by one of the following two methods.

Conda

The conda env file assumes you would use CUDA11.

conda env create -f environment.yml

pip

  1. Install PyTorch 1.9+
  2. Install PyTorch Geometrics
  3. pip install -r requirements.txt

Run

./run.sh

Note

The accuracy performance might differ a little depending on the GPU vs. CPU, CUDA driver, Pytorch version, etc. We try to make the results as deterministic as possible using torch.use_deterministic but this feature is experimental and not stable. For details, see https://github.com/rusty1s/pytorch_geometric/issues/2788 https://pytorch.org/docs/stable/notes/randomness.html

Attribution

Some of the benchmark implimentations are forked from https://github.com/rusty1s/pytorch_geometric/tree/master/benchmark

Related Skills

View on GitHub
GitHub Stars5
CategoryDevelopment
Updated1y ago
Forks0

Languages

Jupyter Notebook

Security Score

55/100

Audited on Apr 27, 2024

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