Method eval

imaginaire/trainers/gancraft.py:45–66

r"""Produce output given segmentation and other conditioning inputs. random style will be used if neither z nor style_img is provided. Args: label (N x C x H x W tensor): One-hot segmentation mask of shape. z: Style vector. style_img: Style image.

(self, label, z=None, style_img=None)

        print('[GauGANLoader] GauGAN loading complete.')

    def eval(self, label, z=None, style_img=None):
        r"""Produce output given segmentation and other conditioning inputs.
        random style will be used if neither z nor style_img is provided.

        Args:
            label (N x C x H x W tensor): One-hot segmentation mask of shape.
            z: Style vector.
            style_img: Style image.
        """
        inputs = {'label': label[:, :-1].detach().half()}
        random_style = True

        if z is not None:
            random_style = False
            inputs['z'] = z.detach().half()
        elif style_img is not None:
            random_style = False
            inputs['images'] = style_img.detach().half()

        net_GG_output = self.net_GG(inputs, random_style=random_style)

        return net_GG_output['fake_images']


class Trainer(BaseTrainer):