jump patch

modules/processing.py

@@ -2,19 +2,25 @@ import json
 import math
 import os
 import sys
+import random
+import logging
+from typing import Any, Dict, List
 
 import torch
 import numpy as np
 from PIL import Image, ImageFilter, ImageOps
-import random
 import cv2
 from skimage import exposure
-from typing import Any, Dict, List
+
+from ldm.data.util import AddMiDaS
+from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion
+from einops import repeat, rearrange
+from blendmodes.blend import blendLayers, BlendType
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts # pylint: disable=unused-import
 from modules.sd_hijack import model_hijack
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, cmd_opts, state # pylint: disable=unused-import
 import modules.shared as shared
 import modules.paths as paths
 import modules.face_restoration
@@ -22,12 +28,6 @@ import modules.images as images
 import modules.styles
 import modules.sd_models as sd_models
 import modules.sd_vae as sd_vae
-import logging
-from ldm.data.util import AddMiDaS
-from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion
-
-from einops import repeat, rearrange
-from blendmodes.blend import blendLayers, BlendType
 
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
 opt_C = 4
@@ -198,7 +198,7 @@ class StableDiffusionProcessing:
     def unclip_image_conditioning(self, source_image):
         c_adm = self.sd_model.embedder(source_image)
         if self.sd_model.noise_augmentor is not None:
-            noise_level = 0 # TODO: Allow other noise levels?
+            noise_level = 0
             c_adm, noise_level_emb = self.sd_model.noise_augmentor(c_adm, noise_level=repeat(torch.tensor([noise_level]).to(c_adm.device), '1 -> b', b=c_adm.shape[0]))
             c_adm = torch.cat((c_adm, noise_level_emb), 1)
         return c_adm
@@ -267,7 +267,7 @@ class StableDiffusionProcessing:
         raise NotImplementedError()
 
     def close(self):
-        self.sampler = None
+        self.sampler = None # pylint: disable=attribute-defined-outside-init
 
 
 class Processed:
@@ -453,7 +453,7 @@ def fix_seed(p):
     p.subseed = get_fixed_seed(p.subseed)
 
 
-def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0):
+def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0): # pylint: disable=unused-argument
     index = position_in_batch + iteration * p.batch_size
 
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
@@ -527,7 +527,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
 
     if type(p.prompt) == list:
-        assert(len(p.prompt) > 0)
+        assert len(p.prompt) > 0
     else:
         assert p.prompt is not None
 
@@ -725,7 +725,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 
                     if opts.return_mask:
                         output_images.append(image_mask)
-                    
+
                     if opts.return_mask_composite:
                         output_images.append(image_mask_composite)