Class ExtrasMiddleMultNode

adv_control/nodes_weight.py:305–329

                                                    uncond_multiplier=uncond_multiplier, cn_extras=cn_extras)

class CustomT2IAdapterWeights(io.ComfyNode):
    @classmethod
    def define_schema(cls) -> io.Schema:
        return io.Schema(
            node_id='ACN_CustomT2IAdapterWeights',
            display_name='T2IAdapter Custom Weights 🛂🅐🅒🅝',
            category='Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter',
            inputs=[
                io.Float.Input('input_0', default=1.0, max=10.0, min=0.0, step=0.001),
                io.Float.Input('input_1', default=1.0, max=10.0, min=0.0, step=0.001),
                io.Float.Input('input_2', default=1.0, max=10.0, min=0.0, step=0.001),
                io.Float.Input('input_3', default=1.0, max=10.0, min=0.0, step=0.001),
                io.Float.Input('uncond_multiplier', optional=True, default=1.0, max=1.0, min=0.0, step=0.01),
                io.Custom('CN_WEIGHTS_EXTRAS').Input('cn_extras', optional=True)
            ],
            outputs=[
                io.Custom('CONTROL_NET_WEIGHTS').Output('CN_WEIGHTS', is_output_list=False),
                io.Custom('TIMESTEP_KEYFRAME').Output('TK_SHORTCUT', is_output_list=False)
            ]
        )
    

    @classmethod
    def execute(cls, input_0, input_1, input_2, input_3,
                     uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
        weights = [input_0, input_1, input_2, input_3]
        weights = get_properly_arranged_t2i_weights(weights)
        weights = ControlWeights.t2iadapter(weights_input=weights, uncond_multiplier=uncond_multiplier, extras=cn_extras, disable_applied_to=True)