def build_one_hid_model(self, input_dim):
        model = AutoEncoder(input_dim=input_dim, rand_seed=self.state.model.rand_seed)

        h1_noise = None if self.state.hidden1.layer_noise.type is None else \
              getattr(layer_noise, self.state.hidden1.layer_noise.type)()

        if ['BlackOut', 'MaskOut', 'BatchOut'] in self.state.hidden1.layer_noise.type:
            h1_noise.ratio = self.state.hidden1.layer_noise.ratio


        elif self.state.hidden1.layer_noise.type == 'Gaussian':
            h1_noise.std = self.state.hidden1.layer_noise.std
            h1_noise.mean = self.state.hidden1.layer_noise.mean

        hidden1 = getattr(layer, self.state.hidden1.type)(dim=self.state.hidden1.dim,
                                                        name=self.state.hidden1.name,
                                                        dropout_below=self.state.hidden1.dropout_below,
                                                        noise=h1_noise)
                                                        # blackout_below=self.state.hidden1.blackout_below)
        model.add_encode_layer(hidden1)
        h1_mirror = getattr(layer, self.state.h1_mirror.type)(dim=input_dim,
                                                            name=self.state.h1_mirror.name,
                                                            W=hidden1.W.T,
                                                            dropout_below=self.state.h1_mirror.dropout_below)
                                                            # blackout_below=self.state.h1_mirror.blackout_below)
        model.add_decode_layer(h1_mirror)
        return model
dataset/ETHPy150Open hycis/Pynet/hps/deprecated/AE.py/AE.build_one_hid_model/swapped operands of `in`