class GRU(nn.Module):
    def __init__(self, num_classes, input_size, hidden_size, num_layers, seq_length):
        super(GRU, self).__init__()
        self.num_classes = num_classes
        self.num_layers = num_layers
        self.input_size = input_size
        self.hidden_size = hidden_size
        self.seq_length = seq_length

        self.gru = nn.GRU(input_size=input_size, hidden_size=hidden_size, num_layers=num_layers, batch_first=True)
        self.fc_1 = nn.Linear(hidden_size, 128)
        self.fc = nn.Linear(128, num_classes)
        self.relu = nn.ReLU()

    def forward(self, x):
        h_0 = Variable(torch.zeros(self.num_layers, x.size(0), self.hidden_size)) ------ 은닉 상태에 대해 0으로 초기화하는 부분으로, LSTM 계층은 셀 상태가 있었지만 GRU는 셀 상태를 정의하지 않습니다.
        output, (hn) = self.gru(x, (h_0))
        hn = hn.view(-1, self.hidden_size)
        out = self.relu(hn)
        out = self.fc_1(out)
        out = self.relu(out)
        out = self.fc(out)
        return out