fix CLIP doing the unneeded normalization

revert SD2.1 back to use the original repo
add SDXL's force_zero_embeddings to negative prompt

1 files changed, 10 insertions, 4 deletions

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 33810669..b29d079d 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -116,11 +116,17 @@ class SdConditioning(list):
     A list with prompts for stable diffusion's conditioner model.

     Can also specify width and height of created image - SDXL needs it.

     """

-    def __init__(self, prompts, width=None, height=None):

+    def __init__(self, prompts, is_negative_prompt=False, width=None, height=None, copy_from=None):

         super().__init__()

         self.extend(prompts)

-        self.width = width or getattr(prompts, 'width', None)

-        self.height = height or getattr(prompts, 'height', None)

+

+        if copy_from is None:

+            copy_from = prompts

+

+        self.is_negative_prompt = is_negative_prompt or getattr(copy_from, 'is_negative_prompt', False)

+        self.width = width or getattr(copy_from, 'width', None)

+        self.height = height or getattr(copy_from, 'height', None)

+

 

 

 def get_learned_conditioning(model, prompts: SdConditioning | list[str], steps):

@@ -153,7 +159,7 @@ def get_learned_conditioning(model, prompts: SdConditioning | list[str], steps):
             res.append(cached)

             continue

 

-        texts = [x[1] for x in prompt_schedule]

+        texts = SdConditioning([x[1] for x in prompt_schedule], copy_from=prompts)

         conds = model.get_learned_conditioning(texts)

 

         cond_schedule = []