cleanup logging

Signed-off-by: Vladimir Mandic <mandic00@live.com>

modules/loader.py

@@ -93,13 +93,13 @@
 
 class _tqdm_cls():
     def __call__(self, *args, **kwargs):
-        bar_format = 'Diffusers {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + '{desc}' + '\x1b[0m'
+        bar_format = 'Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + '{desc}' + '\x1b[0m'
         return tqdm_lib.tqdm(*args, bar_format=bar_format, ncols=80, colour='#327fba', **kwargs)
 
 class _tqdm_old(tqdm_lib.tqdm):
     def __init__(self, *args, **kwargs):
         kwargs.pop("name", None)
-        kwargs['bar_format'] = 'Diffusers {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + '{desc}' + '\x1b[0m'
+        kwargs['bar_format'] = 'Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + '{desc}' + '\x1b[0m'
         kwargs['ncols'] = 80
         super().__init__(*args, **kwargs)
 

modules/processing_args.py

@@ -99,7 +99,7 @@ def task_specific_kwargs(p, model):
             'output_type': 'pil',
         }
     if debug_enabled:
-        debug_log(f'Diffusers task specific args: {task_args}')
+        debug_log(f'Process task specific args: {task_args}')
     return task_args
 
 
@@ -121,7 +121,7 @@ def set_pipeline_args(p, model, prompts:list, negative_prompts:list, prompts_2:t
     possible = list(signature.parameters)
 
     if debug_enabled:
-        debug_log(f'Diffusers pipeline possible: {possible}')
+        debug_log(f'Process pipeline possible: {possible}')
     prompts, negative_prompts, prompts_2, negative_prompts_2 = fix_prompts(p, prompts, negative_prompts, prompts_2, negative_prompts_2)
     steps = kwargs.get("num_inference_steps", None) or len(getattr(p, 'timesteps', ['1']))
     clip_skip = kwargs.pop("clip_skip", 1)
@@ -300,15 +300,15 @@ def set_pipeline_args(p, model, prompts:list, negative_prompts:list, prompts_2:t
             args[arg] = task_kwargs[arg]
     task_args = getattr(p, 'task_args', {})
     if debug_enabled:
-        debug_log(f'Diffusers task args: {task_args}')
+        debug_log(f'Process task args: {task_args}')
     for k, v in task_args.items():
         if k in possible:
             args[k] = v
         else:
-            debug_log(f'Diffusers unknown task args: {k}={v}')
+            debug_log(f'Process unknown task args: {k}={v}')
     cross_attention_args = getattr(p, 'cross_attention_kwargs', {})
     if debug_enabled:
-        debug_log(f'Diffusers cross-attention args: {cross_attention_args}')
+        debug_log(f'Process cross-attention args: {cross_attention_args}')
     for k, v in cross_attention_args.items():
         if args.get('cross_attention_kwargs', None) is None:
             args['cross_attention_kwargs'] = {}
@@ -329,7 +329,7 @@ def set_pipeline_args(p, model, prompts:list, negative_prompts:list, prompts_2:t
 
     # handle implicit controlnet
     if 'control_image' in possible and 'control_image' not in args and 'image' in args:
-        debug_log('Diffusers: set control image')
+        debug_log('Process: set control image')
         args['control_image'] = args['image']
 
     sd_hijack_hypertile.hypertile_set(p, hr=len(getattr(p, 'init_images', [])) > 0)
@@ -365,7 +365,7 @@ def set_pipeline_args(p, model, prompts:list, negative_prompts:list, prompts_2:t
         t1 = time.time()
         shared.log.debug(f'Profile: pipeline args: {t1-t0:.2f}')
     if debug_enabled:
-        debug_log(f'Diffusers pipeline args: {args}')
+        debug_log(f'Process pipeline args: {args}')
 
     _args = {}
     for k, v in args.items(): # pipeline may modify underlying args

modules/sd_models.py

@@ -406,7 +406,7 @@ def load_diffuser_file(model_type, pipeline, checkpoint_info, diffusers_load_con
                 from diffusers.utils import import_utils
                 import_utils._accelerate_available = False # pylint: disable=protected-access
             if shared.opts.diffusers_to_gpu and model_type.startswith('Stable Diffusion'):
-                shared.log.debug(f'Diffusers accelerate: direct={shared.opts.diffusers_to_gpu}')
+                shared.log.debug(f'Setting {op}: component=accelerate: direct={shared.opts.diffusers_to_gpu}')
                 sd_hijack_accelerate.hijack_accelerate()
             else:
                 sd_hijack_accelerate.restore_accelerate()

modules/sd_samplers_diffusers.py

@@ -37,7 +37,7 @@
         KDPM2AncestralDiscreteScheduler,
     )
 except Exception as e:
-    shared.log.error(f'Diffusers import error: version={diffusers.__version__} error: {e}')
+    shared.log.error(f'Sampler import: version={diffusers.__version__} error: {e}')
     if os.environ.get('SD_SAMPLER_DEBUG', None) is not None:
         errors.display(e, 'Samplers')
 try:
@@ -50,7 +50,7 @@
     from modules.schedulers.scheduler_ufogen import UFOGenScheduler # pylint: disable=ungrouped-imports
     from modules.perflow import PeRFlowScheduler # pylint: disable=ungrouped-imports
 except Exception as e:
-    shared.log.error(f'Diffusers import error: version={diffusers.__version__} error: {e}')
+    shared.log.error(f'Sampler import: version={diffusers.__version__} error: {e}')
     if os.environ.get('SD_SAMPLER_DEBUG', None) is not None:
         errors.display(e, 'Samplers')
 

modules/sd_vae.py

@@ -222,7 +222,7 @@ def load_vae_diffusers(model_file, vae_file=None, vae_source="unknown-source"):
                 vae = diffusers.AutoencoderKL.from_single_file(vae_file, **diffusers_load_config)
                 if getattr(vae.config, 'scaling_factor', 0) == 0.18125 and shared.sd_model_type == 'sdxl':
                     vae.config.scaling_factor = 0.13025
-                    shared.log.debug('Diffusers VAE: fix scaling factor')
+                    shared.log.debug('Setting model: component=VAE fix scaling factor')
             vae = vae.to(devices.dtype_vae)
         else:
             if 'consistency-decoder' in vae_file: