o GÆÏiîã@sŠddlmZddlmZddlmZddlmZmZm Z ddl m Z ddl m Z dd lmZe e¡ZGd d „d eƒZGd d „d eƒZdS)é)Úloggingé)ÚSequentialPipelineBlocks)Ú OutputParamé)ÚWanPrepareLatentsStepÚWanSetTimestepsStepÚWanTextInputStep)ÚWanVaeDecoderStep)ÚWan22DenoiseStep)ÚWanTextEncoderStepc@s@eZdZdZdZeeeegZ gd¢Z e dd„ƒZ e dd„ƒZ dS) ÚWan22CoreDenoiseStepa‘ denoise block that takes encoded conditions and runs the denoising process. Components: transformer (`WanTransformer3DModel`) scheduler (`UniPCMultistepScheduler`) guider (`ClassifierFreeGuidance`) guider_2 (`ClassifierFreeGuidance`) transformer_2 (`WanTransformer3DModel`) Configs: boundary_ratio (default: 0.875): The boundary ratio to divide the denoising loop into high noise and low noise stages. Inputs: num_videos_per_prompt (`None`, *optional*, defaults to 1): TODO: Add description. prompt_embeds (`Tensor`): Pre-generated text embeddings. Can be generated from text_encoder step. negative_prompt_embeds (`Tensor`, *optional*): Pre-generated negative text embeddings. Can be generated from text_encoder step. num_inference_steps (`None`, *optional*, defaults to 50): TODO: Add description. timesteps (`None`, *optional*): TODO: Add description. sigmas (`None`, *optional*): TODO: Add description. height (`int`, *optional*): TODO: Add description. width (`int`, *optional*): TODO: Add description. num_frames (`int`, *optional*): TODO: Add description. latents (`Tensor | NoneType`, *optional*): TODO: Add description. generator (`None`, *optional*): TODO: Add description. attention_kwargs (`None`, *optional*): TODO: Add description. Outputs: latents (`Tensor`): Denoised latents. Úwan)ÚinputÚ set_timestepsÚprepare_latentsÚdenoisecCódS)NzKdenoise block that takes encoded conditions and runs the denoising process.©©Úselfrrúh/home/ubuntu/.local/lib/python3.10/site-packages/diffusers/modular_pipelines/wan/modular_blocks_wan22.pyÚ description_óz Wan22CoreDenoiseStep.descriptioncCó t d¡gS)NÚlatents©rÚtemplaterrrrÚoutputscó zWan22CoreDenoiseStep.outputsN)Ú__name__Ú __module__Ú __qualname__Ú__doc__Ú model_namer rrr Ú block_classesÚ block_namesÚpropertyrrrrrrr +s*ü r c@s>eZdZdZdZeeegZgd¢Z e dd„ƒZ e dd„ƒZ dS) Ú Wan22Blocksac Modular pipeline for text-to-video using Wan2.2. Components: text_encoder (`UMT5EncoderModel`) tokenizer (`AutoTokenizer`) guider (`ClassifierFreeGuidance`) transformer (`WanTransformer3DModel`) scheduler (`UniPCMultistepScheduler`) guider_2 (`ClassifierFreeGuidance`) transformer_2 (`WanTransformer3DModel`) vae (`AutoencoderKLWan`) video_processor (`VideoProcessor`) Configs: boundary_ratio (default: 0.875): The boundary ratio to divide the denoising loop into high noise and low noise stages. Inputs: prompt (`None`, *optional*): TODO: Add description. negative_prompt (`None`, *optional*): TODO: Add description. max_sequence_length (`None`, *optional*, defaults to 512): TODO: Add description. num_videos_per_prompt (`None`, *optional*, defaults to 1): TODO: Add description. num_inference_steps (`None`, *optional*, defaults to 50): TODO: Add description. timesteps (`None`, *optional*): TODO: Add description. sigmas (`None`, *optional*): TODO: Add description. height (`int`, *optional*): TODO: Add description. width (`int`, *optional*): TODO: Add description. num_frames (`int`, *optional*): TODO: Add description. latents (`Tensor | NoneType`, *optional*): TODO: Add description. generator (`None`, *optional*): TODO: Add description. attention_kwargs (`None`, *optional*): TODO: Add description. output_type (`str`, *optional*, defaults to np): The output type of the decoded videos Outputs: videos (`list`): The generated videos. r)Ú text_encoderrÚdecodecCr)Nz0Modular pipeline for text-to-video using Wan2.2.rrrrrrªrzWan22Blocks.descriptioncCr)NÚvideosrrrrrr®rzWan22Blocks.outputsN) r r!r"r#r$r r r r%r&r'rrrrrrr(ns/ý r(N)ÚutilsrÚmodular_pipelinerÚmodular_pipeline_utilsrÚbefore_denoiserrr Údecodersr rr Úencodersr Ú get_loggerr Úloggerr r(rrrrÚs        C