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enhance_vae_properties if vae is provided only

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davidb
2025-10-09 16:17:40 +00:00
committed by DavidBert
parent 6a66fbd2c4
commit d71ddd0079
1 changed files with 7 additions and 6 deletions
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13
src/diffusers/pipelines/photon/pipeline_photon.py
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@@ -234,8 +234,8 @@ class PhotonPipeline(
The Photon transformer model to denoise the encoded image latents.
scheduler ([`FlowMatchEulerDiscreteScheduler`]):
A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
text_encoder ([`T5EncoderModel`] or [`T5GemmaEncoder`]):
Text encoder model for encoding prompts. Supports T5EncoderModel or T5GemmaEncoder.
text_encoder ([`T5GemmaEncoder`]):
Text encoder model for encoding prompts.
tokenizer ([`T5TokenizerFast` or `GemmaTokenizerFast`]):
Tokenizer for the text encoder.
vae ([`AutoencoderKL`] or [`AutoencoderDC`]):
@@ -251,9 +251,9 @@ class PhotonPipeline(
self,
transformer: PhotonTransformer2DModel,
scheduler: FlowMatchEulerDiscreteScheduler,
text_encoder: Union[T5EncoderModel, T5GemmaEncoder],
text_encoder: Union[T5GemmaEncoder],
tokenizer: Union[T5TokenizerFast, GemmaTokenizerFast, AutoTokenizer],
vae: Union[AutoencoderKL, AutoencoderDC],
vae: Optional[Union[AutoencoderKL, AutoencoderDC]] = None,
default_sample_size: Optional[int] = DEFAULT_RESOLUTION,
):
super().__init__()
@@ -277,8 +277,9 @@ class PhotonPipeline(
self.register_to_config(default_sample_size=default_sample_size)
# Enhance VAE with universal properties for both AutoencoderKL and AutoencoderDC
self._enhance_vae_properties()
if vae is not None:
# Enhance VAE with universal properties for both AutoencoderKL and AutoencoderDC
self._enhance_vae_properties()
self.image_processor = PixArtImageProcessor(vae_scale_factor=self.vae_scale_factor)