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在`def model_init(model, X, y, A_norm): """ load the pre-train model and calculate similarity and cluster centers Args: model: Dual Correlation Reduction Network X: input feature matrix y: input label A_norm: normalized adj Returns: embedding similarity matrix """ # load pre-train model model = load_pretrain_parameter(model)
# calculate embedding similarity with torch.no_grad(): _, _, _, sim, _, _, _, Z, _, _ = model(X, A_norm, X, A_norm) # calculate cluster centers acc, nmi, ari, f1, centers = clustering(Z, y) return sim, centers`中 _, _, _, sim, _, _, _, Z, _, _ = model(X, A_norm, X, A_norm)中X,A_norm出现了两次
在传入forward(self, X_tilde1, Am, X_tilde2, Ad)函数时是应该是x1一波和x2一波, 这样的话取平均好像好不取平均是一样的了 Z_ae = (Z_ae1 + Z_ae2) / 2 Z_igae = (Z_igae1 + Z_igae2) / 2
这个地方不太理解,可以解答一下吗?
The text was updated successfully, but these errors were encountered:
你好,感谢关注。在模型初始化的时候,还不需要做图数据增强,因此只有一个视图的数据,只需要传X和A_norm一次。这里写的应该只是为了适配那个函数的输入和输出,实际上只计算一次就可以,之后可以修改成只做一次encoding的。
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在`def model_init(model, X, y, A_norm):
"""
load the pre-train model and calculate similarity and cluster centers
Args:
model: Dual Correlation Reduction Network
X: input feature matrix
y: input label
A_norm: normalized adj
Returns: embedding similarity matrix
"""
# load pre-train model
model = load_pretrain_parameter(model)
在传入forward(self, X_tilde1, Am, X_tilde2, Ad)函数时是应该是x1一波和x2一波,
![image](https://private-user-images.githubusercontent.com/117249790/268834630-2a745eb0-152f-49d0-b088-d4c249c67eee.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjQyNjc3OTAsIm5iZiI6MTcyNDI2NzQ5MCwicGF0aCI6Ii8xMTcyNDk3OTAvMjY4ODM0NjMwLTJhNzQ1ZWIwLTE1MmYtNDlkMC1iMDg4LWQ0YzI0OWM2N2VlZS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwODIxJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDgyMVQxOTExMzBaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT00MGM4OTI5ZTdiMzNlMDkxN2U5OGQzMDg2YTg1MzI1YTQwM2QzNTM3NzcyMzcwZWU4OWM2MzM0OGJlNjFjYTYyJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.HgN31LJmFu1AHz8duBbBi9s1LmJOnPbWkgo5llJUrS8)
这样的话取平均好像好不取平均是一样的了 Z_ae = (Z_ae1 + Z_ae2) / 2
Z_igae = (Z_igae1 + Z_igae2) / 2
这个地方不太理解,可以解答一下吗?
The text was updated successfully, but these errors were encountered: