EPSL/model_shared_component.py at main · Xi-L/EPSL · GitHub

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import torch
import torch.nn as nn

device = 'cpu'

class ParetoSetModel(torch.nn.Module):
    def __init__(self, n_dim, n_obj):
        super(ParetoSetModel, self).__init__()
        self.n_dim = n_dim
        self.n_obj = n_obj
        self.n_node = 1024

        self.fc1 = nn.Linear(self.n_obj, self.n_node)
        self.fc2 = nn.Linear(self.n_node, self.n_node)
        self.fc3 = nn.Linear(self.n_node, self.n_dim)

        self.constant = nn.Parameter(data=torch.rand((1, n_dim), dtype=torch.float), requires_grad=True)


    def forward(self, pref):

        x = torch.relu(self.fc1(pref))
        x = torch.relu(self.fc2(x))
        x = self.fc3(x)

        alpha = torch.ones(self.n_dim).to(device)
        alpha[3] = 0

        x = self.constant + alpha * x

        x = torch.sigmoid(x)

        return x.to(torch.float64)