RuntimeError, when using ICL model

[943fansi]

RuntimeError: Trying to create tensor with negative dimension -1: [100, -1]

x_train shape [4320, 1]
x_test shape [4320, 1]

modelL = {0: DeepSVDD, 1: REPEN, 2: RDP, 3: RCA, 4: GOAD, 5: ICL}
model_name = ["SVDD", "REPEN", "RDP", "RCA", "GOAD", "ICL"]
for index in range(1, 6):
    model = modelL[index]()
    model.fit(x_train, y=None)
    score = model.decision_function(x_test)

        self.enc_f_net = MLPnet(
            n_features=n_features-kernel_size,
            n_hidden=hidden_dims,
            n_output=rep_dim,
            mid_channels=len(self.all_idx),
            batch_norm=True,
            activation=f_act,
            bias=bias,
        )

here, n_features=1 and kernel_size=2, and then it got -1

[xuhongzuo]

ICL is a self-supervised model that learns the mapping of sub-vectors and the remaining parts. If the input only contains one feature, ICL cannot handle this case.

Thanks for raising this issue, I will add a check_array function in this model.