lint changes

modules/extra_networks.py

@@ -67,7 +67,7 @@ def is_stepwise(en_obj):
     for en in en_obj:
         all_args.extend(en.positional[1:])
         all_args.extend(en.named.values())
-    return any([len(str(x).split("@")) > 1 for x in all_args]) # noqa C419
+    return any([len(str(x).split("@")) > 1 for x in all_args]) # noqa C419 # pylint: disable=use-a-generator
 
 
 def activate(p, extra_network_data, step=0):

modules/images.py

@@ -701,7 +701,7 @@ def save_video_atomic(images, filename, video_type: str = 'none', duration: floa
 
 def save_video(p, images, filename = None, video_type: str = 'none', duration: float = 2.0, loop: bool = False, interpolate: int = 0, scale: float = 1.0, pad: int = 1, change: float = 0.3, sync: bool = False):
     if images is None or len(images) < 2 or video_type is None or video_type.lower() == 'none':
-        return
+        return None
     image = images[0]
     if p is not None:
         namegen = FilenameGenerator(p, seed=p.all_seeds[0], prompt=p.all_prompts[0], image=image)

modules/interrogate.py

@@ -83,7 +83,7 @@ class InterrogateModels:
         from repositories.blip.models import blip
         import modules.modelloader as modelloader
         model_path = os.path.join(paths.models_path, "BLIP")
-        download_name='model_base_caption_capfilt_large.pth',
+        download_name='model_base_caption_capfilt_large.pth'
         shared.log.debug(f'Model interrogate load: type=BLiP model={download_name} path={model_path}')
         files = modelloader.load_models(
             model_path=model_path,

modules/ipadapter.py

@@ -48,7 +48,7 @@ def get_images(input_images):
     for image in input_images:
         if image is None:
             continue
-        elif isinstance(image, list):
+        if isinstance(image, list):
             output_images.append(get_images(image)) # recursive
         elif isinstance(image, Image.Image):
             output_images.append(image)
@@ -185,7 +185,7 @@ def apply(pipe, p: processing.StableDiffusionProcessing, adapter_names=[], adapt
                 clip_loaded = f'{clip_repo}/{clip_subfolder}'
             except Exception as e:
                 shared.log.error(f'IP adapter: failed to load image encoder: {e}')
-                return
+                return False
         sd_models.move_model(pipe.image_encoder, devices.device)
 
     # main code

modules/masking.py

@@ -500,8 +500,7 @@ def run_mask_live(input_image: gr.Image):
             res = run_mask(input_image)
             busy = False
             return res
-    else:
-        return None
+    return None
 
 
 def create_segment_ui():

modules/modelloader.py

@@ -237,7 +237,7 @@ def load_diffusers_models(clear=True):
     try:
         for folder in os.listdir(place):
             try:
-                if any([x in folder for x in excluded_models]): # noqa:C419
+                if any([x in folder for x in excluded_models]): # noqa:C419 # pylint: disable=use-a-generator
                     continue
                 if "--" not in folder:
                     continue

modules/pag/__init__.py

@@ -32,6 +32,8 @@ def apply(p: processing.StableDiffusionProcessing): # pylint: disable=arguments-
     pag_applied_layers_index = pag_applied_layers.split() if len(pag_applied_layers) > 0 else []
     pag_applied_layers_index = [p.strip() for p in pag_applied_layers_index]
     p.task_args['pag_applied_layers_index'] = pag_applied_layers_index if len(pag_applied_layers_index) > 0 else ['m0'] # Available layers: d[0-5], m[0], u[0-8]
+    p.extra_generation_params["PAG scale"] = p.pag_scale
+    p.extra_generation_params["PAG adaptive"] = p.pag_adaptive
     shared.log.debug(f'{c}: args={p.task_args}')
 
 

modules/patches.py

@@ -40,7 +40,7 @@ def undo(key, obj, field):
     patch_key = (obj, field)
     if patch_key not in originals[key]:
         log.error(f"Patch no patch to undo: field={field}")
-        return
+        return None
     original_func = originals[key].pop(patch_key)
     if original_func is None:
         delattr(obj, field)

modules/processing_diffusers.py

@@ -7,7 +7,6 @@ import typing
 import numpy as np
 import torch
 import torchvision.transforms.functional as TF
-import diffusers
 from modules import shared, devices, processing, sd_samplers, sd_models, images, errors, prompt_parser_diffusers, sd_hijack_hypertile, processing_correction, processing_vae, sd_models_compile, extra_networks, hidiffusion
 from modules.processing_helpers import resize_init_images, resize_hires, fix_prompts, calculate_base_steps, calculate_hires_steps, calculate_refiner_steps
 from modules.onnx_impl import preprocess_pipeline as preprocess_onnx_pipeline, check_parameters_changed as olive_check_parameters_changed
@@ -366,6 +365,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
 
     def update_pipeline(sd_model, p: processing.StableDiffusionProcessing):
         """
+        import diffusers
         if p.sag_scale > 0 and is_txt2img():
             update_sampler(shared.sd_model)
             supported = ['DDIMScheduler', 'PNDMScheduler', 'DDPMScheduler', 'DEISMultistepScheduler', 'UniPCMultistepScheduler', 'DPMSolverMultistepScheduler', 'DPMSolverSinlgestepScheduler']

modules/prompt_parser_diffusers.py

@@ -98,9 +98,9 @@ def get_prompt_schedule(prompt, steps):
 
 
 def encode_prompts(pipe, p, prompts: list, negative_prompts: list, steps: int, clip_skip: typing.Optional[int] = None):
-    if 'StableDiffusion' not in pipe.__class__.__name__ and 'DemoFusion':
+    if 'StableDiffusion' not in pipe.__class__.__name__ and 'DemoFusion' not in pipe.__class__.__name__:
         shared.log.warning(f"Prompt parser not supported: {pipe.__class__.__name__}")
-        return None, None, None, None
+        return
     else:
         t0 = time.time()
         positive_schedule, scheduled = get_prompt_schedule(prompts[0], steps)

modules/sd_models_compile.py

@@ -78,9 +78,9 @@ def ipex_optimize(sd_model):
                 sd_model.prior_text_encoder = ipex_optimize_model(sd_model.prior_text_encoder)
         t1 = time.time()
         shared.log.info(f"IPEX Optimize: time={t1-t0:.2f}")
-        return sd_model
     except Exception as e:
         shared.log.warning(f"IPEX Optimize: error: {e}")
+    return sd_model
 
 
 def nncf_compress_weights(sd_model):
@@ -132,9 +132,9 @@ def nncf_compress_weights(sd_model):
                 sd_model.prior_text_encoder = nncf_compress_model(sd_model.prior_text_encoder)
         t1 = time.time()
         shared.log.info(f"Compress Weights: time={t1-t0:.2f}")
-        return sd_model
     except Exception as e:
         shared.log.warning(f"Compress Weights: error: {e}")
+    return sd_model
 
 
 def optimize_openvino(sd_model):
@@ -258,7 +258,7 @@ def compile_torch(sd_model):
                 shared.compiled_model_state = CompiledModelState()
             return sd_model
         elif shared.opts.cuda_compile_backend ==  "migraphx":
-            import torch_migraphx
+            import torch_migraphx # pylint: disable=unused-import
         log_level = logging.WARNING if shared.opts.cuda_compile_verbose else logging.CRITICAL # pylint: disable=protected-access
         if hasattr(torch, '_logging'):
             torch._logging.set_logs(dynamo=log_level, aot=log_level, inductor=log_level) # pylint: disable=protected-access

modules/ui_control.py

@@ -59,7 +59,7 @@ def generate_click(job_id: str, active_tab: str, *args):
         except Exception as e:
             shared.log.error(f"Control exception: {e}")
             errors.display(e, 'Control')
-            return None, None, None, None, f'Control: Exception: {e}'
+            yield [None, None, None, None, f'Control: Exception: {e}']
         progress.finish_task(job_id)
     shared.state.end()
 
@@ -114,7 +114,7 @@ def create_ui(_blocks: gr.Blocks=None):
                 mask_controls = masking.create_segment_ui()
 
                 cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_advanced_inputs('control')
-                hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio, = ui_sections.create_correction_inputs('control')
+                hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('control')
 
                 with gr.Accordion(open=False, label="Video", elem_id="control_video", elem_classes=["small-accordion"]):
                     with gr.Row():
@@ -579,6 +579,9 @@ def create_ui(_blocks: gr.Blocks=None):
                 (refiner_steps, "Refiner steps"),
                 (refiner_prompt, "Prompt2"),
                 (refiner_negative, "Negative2"),
+                # pag
+                (pag_scale, "PAG scale"),
+                (pag_adaptive, "PAG adaptive"),
                 # hidden
                 (seed_resize_from_w, "Seed resize from-1"),
                 (seed_resize_from_h, "Seed resize from-2"),

modules/ui_img2img.py

@@ -134,7 +134,7 @@ def create_ui():
 
                     cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_advanced_inputs('img2img')
                     full_quality, restore_faces, tiling, hidiffusion = ui_sections.create_options('img2img')
-                    hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio, = ui_sections.create_correction_inputs('img2img')
+                    hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('img2img')
 
                     # with gr.Group(elem_id="inpaint_controls", visible=False) as inpaint_controls:
                     with gr.Accordion(open=False, label="Mask", elem_classes=["small-accordion"], elem_id="img2img_mask_group") as inpaint_controls:

modules/ui_sections.py

@@ -196,7 +196,7 @@ def create_correction_inputs(tab):
             with gr.Row(elem_id=f"{tab}_hdr_color_row"):
                 hdr_color_picker = gr.ColorPicker(label="Color", show_label=True, container=False, value=None, elem_id=f"{tab}_hdr_color_picker")
                 hdr_tint_ratio = gr.Slider(label='Color grading', minimum=-1.0, maximum=1.0, step=0.05, value=0.0, elem_id=f"{tab}_hdr_tint_ratio")
-        return hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio,
+        return hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio
 
 
 def create_sampler_and_steps_selection(choices, tabname):

modules/ui_txt2img.py

@@ -47,7 +47,7 @@ def create_ui():
                         ui_sections.create_sampler_options('txt2img')
                     seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = ui_sections.create_seed_inputs('txt2img')
                     _cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, _cfg_end = ui_sections.create_advanced_inputs('txt2img', base=False)
-                    hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio, = ui_sections.create_correction_inputs('txt2img')
+                    hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundry, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('txt2img')
                     enable_hr, hr_sampler_index, denoising_strength, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative = ui_sections.create_hires_inputs('txt2img')
                     override_settings = ui_common.create_override_inputs('txt2img')
 
@@ -131,6 +131,9 @@ def create_ui():
                 (refiner_steps, "Refiner steps"),
                 (refiner_prompt, "Prompt2"),
                 (refiner_negative, "Negative2"),
+                # pag
+                (pag_scale, "PAG scale"),
+                (pag_adaptive, "PAG adaptive"),
                 # hidden
                 (seed_resize_from_w, "Seed resize from-1"),
                 (seed_resize_from_h, "Seed resize from-2"),