Update implementation so that it actually uses the custom classes

#3
by sayakpaul HF staff - opened
Files changed (1) hide show
  1. my_pipeline.py +5 -4
my_pipeline.py CHANGED
@@ -24,7 +24,9 @@ from diffusers.loaders import (
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  StableDiffusionXLLoraLoaderMixin,
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  TextualInversionLoaderMixin,
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  )
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- from diffusers.models import AutoencoderKL, UNet2DConditionModel
 
 
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  from diffusers.models.attention_processor import (
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  AttnProcessor2_0,
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  LoRAAttnProcessor2_0,
@@ -32,7 +34,6 @@ from diffusers.models.attention_processor import (
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  XFormersAttnProcessor,
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  )
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  from diffusers.models.lora import adjust_lora_scale_text_encoder
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- from diffusers.schedulers import KarrasDiffusionSchedulers
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  from diffusers.utils import (
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  USE_PEFT_BACKEND,
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  is_invisible_watermark_available,
@@ -145,8 +146,8 @@ class MyPipeline(
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  text_encoder_2: CLIPTextModelWithProjection,
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  tokenizer: CLIPTokenizer,
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  tokenizer_2: CLIPTokenizer,
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- unet: UNet2DConditionModel,
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- scheduler: KarrasDiffusionSchedulers,
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  force_zeros_for_empty_prompt: bool = True,
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  add_watermarker: Optional[bool] = None,
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  ):
 
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  StableDiffusionXLLoraLoaderMixin,
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  TextualInversionLoaderMixin,
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  )
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+ from diffusers.models import AutoencoderKL
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+ from .scheduler.my_scheduler import MyScheduler
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+ from .unet.my_unet_model import MyUNetModel
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  from diffusers.models.attention_processor import (
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  AttnProcessor2_0,
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  LoRAAttnProcessor2_0,
 
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  XFormersAttnProcessor,
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  )
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  from diffusers.models.lora import adjust_lora_scale_text_encoder
 
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  from diffusers.utils import (
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  USE_PEFT_BACKEND,
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  is_invisible_watermark_available,
 
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  text_encoder_2: CLIPTextModelWithProjection,
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  tokenizer: CLIPTokenizer,
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  tokenizer_2: CLIPTokenizer,
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+ unet: MyUNetModel,
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+ scheduler: MyScheduler,
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  force_zeros_for_empty_prompt: bool = True,
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  add_watermarker: Optional[bool] = None,
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  ):