GAT源代码分析 GAT源代码分析
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首先展示核心公式以及训练过程中生成的aij注意力系数
layer.py
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphAttentionLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(GraphAttentionLayer, self).__init__()
self.dropout = dropout #dropout 参数
self.in_features =全部评论 (0)
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