- Add gradio dropdown list to select checkpoints

    return '', geninfo, info

def run_modelmerger(from_model_name, to_model_name, interp_method, interp_amount):

def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount):

    # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)

    def weighted_sum(theta0, theta1, alpha):

        return ((1 - alpha) * theta0) + (alpha * theta1)

        alpha = alpha * alpha * (3 - (2 * alpha))

        return theta0 + ((theta1 - theta0) * alpha)

    if os.path.exists(to_model_name):

        to_model_filename = to_model_name

        to_model_name = os.path.splitext(os.path.basename(to_model_name))[0]

    if os.path.exists(secondary_model_name):

        secondary_model_filename = secondary_model_name

        secondary_model_name = os.path.splitext(os.path.basename(secondary_model_name))[0]

    else:

        to_model_filename = 'models/' + to_model_name + '.ckpt'

        secondary_model_filename = 'models/' + secondary_model_name + '.ckpt'

    if os.path.exists(from_model_name):

        from_model_filename = from_model_name

        from_model_name = os.path.splitext(os.path.basename(from_model_name))[0]

    if os.path.exists(primary_model_name):

        primary_model_filename = primary_model_name

        primary_model_name = os.path.splitext(os.path.basename(primary_model_name))[0]

    else:

        from_model_filename = 'models/' + from_model_name + '.ckpt'

        primary_model_filename = 'models/' + primary_model_name + '.ckpt'

    print(f"Loading {to_model_filename}...")

    model_0 = torch.load(to_model_filename, map_location='cpu')

    print(f"Loading {secondary_model_filename}...")

    model_0 = torch.load(secondary_model_filename, map_location='cpu')

    print(f"Loading {from_model_filename}...")

    model_1 = torch.load(from_model_filename, map_location='cpu')

    print(f"Loading {primary_model_filename}...")

    model_1 = torch.load(primary_model_filename, map_location='cpu')

    theta_0 = model_0['state_dict']

    theta_1 = model_1['state_dict']

        if 'model' in key and key not in theta_0:

            theta_0[key] = theta_1[key]

    output_modelname = 'models/' + from_model_name + '_' + str(interp_amount) + '-' + to_model_name + '_' + str(float(1.0) - interp_amount) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'

    output_modelname = 'models/' + primary_model_name + '_' + str(interp_amount) + '-' + secondary_model_name + '_' + str(float(1.0) - interp_amount) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'

    print(f"Saving to {output_modelname}...")

    torch.save(model_0, output_modelname)

                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>/models</b> directory.</p>")

                with gr.Row():

                    from_model_name = gr.Textbox(elem_id="modelmerger_from_model_name", label="Model Name (from)")

                    to_model_name = gr.Textbox(elem_id="modelmerger_to_model_name", label="Model Name (to)")

                    ckpt_name_list = [x.model_name for x in modules.sd_models.checkpoints_list.values()]

                    primary_model_name   = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_primary_model_name", label="Primary Model Name")

                    secondary_model_name = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")

                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)

                interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid"], value="Weighted Sum", label="Interpolation Method")

                submit = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')

            submit.click(

                fn=run_modelmerger,

                inputs=[

                    from_model_name,

                    to_model_name,

                    primary_model_name,

                    secondary_model_name,

                    interp_method,

                    interp_amount

                ],