Run black for formatting, fix pylint errors, and change to warning.

modules/processing_diffusers.py

@@ -63,7 +63,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         pooled = None
         negative_embed = None
         negative_pooled = None
-        if shared.opts.data['prompt_attention'] != 'Fixed attention':
+        if shared.opts.data['prompt_attention'] in {'Compel parser', 'Full parser'}:
             prompt_embed, pooled, negative_embed, negative_pooled = prompt_parser_diffusers.compel_encode_prompt(model, prompt, negative_prompt, prompt_2, negative_prompt_2, is_refiner)
         if 'prompt' in possible:
             if hasattr(model, 'text_encoder') and 'prompt_embeds' in possible and prompt_embed is not None:

modules/prompt_parser_diffusers.py

@@ -9,10 +9,11 @@ import modules.prompt_parser as prompt_parser
 def convert_to_compel(prompt: str):
     if prompt is None:
         return None
-    # TODO: 100 should be steps, but doesn't actually matter because we can't schedule yet
     all_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(
         prompt, 100
-    )[0]
+    )[
+        0
+    ]
     output_list = prompt_parser.parse_prompt_attention(all_schedules[0][1])
     converted_prompt = []
     for subprompt, weight in output_list:
@@ -28,9 +29,10 @@ def convert_to_compel(prompt: str):
 def compel_encode_prompt(pipeline: typing.Any, *args, **kwargs):
     compel_encode_fn = COMPEL_ENCODE_FN_DICT.get(type(pipeline), None)
     if compel_encode_fn is None:
-        raise TypeError(
+        shared.log.warning(
             f"Compel encoding not yet supported for {type(pipeline).__name__}."
         )
+        return (None,) * 4
     return compel_encode_fn(pipeline, *args, **kwargs)