Method _build_decoder

numpy_ml/neural_nets/models/vae.py:191–208

MLP decoder FC1 -> ReLU -> FC2 -> Sigmoid

(self)

        )

    def _build_decoder(self):
        """
        MLP decoder

        FC1 -> ReLU -> FC2 -> Sigmoid
        """
        self.decoder = OrderedDict()
        self.decoder["FC1"] = FullyConnected(
            act_fn=ReLU(),
            init=self.init,
            n_out=self.latent_dim,
            optimizer=self.optimizer,
        )
        # NB. `n_out` is dependent on the dimensionality of X. we use a
        # placeholder for now, and update it within the `forward` method
        self.decoder["FC2"] = FullyConnected(
            n_out=None, act_fn=Sigmoid(), optimizer=self.optimizer, init=self.init
        )

    @property
    def parameters(self):