def decode()

in sparse_autoencoder/model.py [0:0]

• 6 lines of code
• 2 McCabe index (conditional complexity)

    def decode(self, latents: torch.Tensor, info: dict[str, Any] | None = None) -> torch.Tensor:
        """
        :param latents: autoencoder latents (shape: [batch, n_latents])
        :return: reconstructed data (shape: [batch, n_inputs])
        """
        ret = self.decoder(latents) + self.pre_bias
        if self.normalize:
            assert info is not None
            ret = ret * info["std"] + info["mu"]
        return ret