Method sample_mixed

training/triplane.py:148–152

(self, coordinates, directions, ws, truncation_psi=1, truncation_cutoff=None, update_emas=False, **synthesis_kwargs)

        return self.renderer.run_model(planes, self.decoder, coordinates, directions, self.rendering_kwargs)

    def sample_mixed(self, coordinates, directions, ws, truncation_psi=1, truncation_cutoff=None, update_emas=False, **synthesis_kwargs):
        # Same as sample, but expects latent vectors 'ws' instead of Gaussian noise 'z'
        planes = self.backbone.synthesis(ws, update_emas = update_emas, **synthesis_kwargs)
        planes = planes.view(len(planes), 3, 32 * self.rendering_kwargs['triplane_depth'], planes.shape[-2], planes.shape[-1])
        return self.renderer.run_model(planes, self.decoder, coordinates, directions, self.rendering_kwargs)

    def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, neural_rendering_resolution=None, update_emas=False, cache_backbone=False, use_cached_backbone=False, **synthesis_kwargs):
        # Render a batch of generated images.