In this section, I implement the model of Graph Attention Networks in the file GAT_Seq.ipynb in a sequencial order to help readers understand the working principle of the Networks and better understand how to process the raw data and eventually load the dataset into the model and train it, since when I first jumped into the area of AI I was so confused by the code shown by most of the coders and couldn't find one that suited my need for a thorough guidance. Through the steps we can better understand how models nowadays process data. And note that the structure I prefer is pytorch and I've exported the env in conda format, just feel free to build the same env as mine and have fun enjoying this intresting trip!