5418fba726d1186b7fdf0bda31a0239568c7a64b,plugins/train/model/realface.py,Model,decoder_a,#Model#,151

Before Change

            var_x = self.blocks.upscale(var_x, decoder_a_complexity // 2**idx)
        var_x = self.blocks.upscale(var_x, decoder_a_complexity // 2**(idx + 1))

        var_x = Conv2D(3, kernel_size=5, padding="same", activation="sigmoid")(var_x)

        outputs = [var_x]

        if self.config.get("mask_type", None) is not None:

After Change

            var_x = self.blocks.upscale(var_x, decoder_a_complexity // 2**idx)
        var_x = self.blocks.upscale(var_x, decoder_a_complexity // 2**(idx + 1))

        var_x = self.blocks.conv2d(var_x, 3, kernel_size=5, padding="same", activation="sigmoid")

        outputs = [var_x]

        if self.config.get("mask_type", None) is not None:
            var_y = var_xy
            mask_a_complexity = 384
            for idx in range(self.upscalers_no-2):
                var_y = self.blocks.upscale(var_y, mask_a_complexity // 2**idx)
            var_y = self.blocks.upscale(var_y, mask_a_complexity // 2**(idx + 1))

            var_y = self.blocks.conv2d(var_y, 1,
                                       kernel_size=5,
                                       padding="same",
                                       activation="sigmoid")

            outputs += [var_y]

        return KerasModel(input_, outputs=outputs)

Instances