class_docstr: Pipeline for text-guided video-to-video generation.
  
  This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
  implemented for all pipelines (downloading, saving, running on a particular device, etc.).
  
  Args:
      vae ([`AutoencoderKL`]):
          Variational Auto-Encoder (VAE) Model to encode and decode videos to and from latent representations.
      text_encoder ([`CLIPTextModel`]):
          Frozen text-encoder ([clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)).
      tokenizer (`CLIPTokenizer`):
          A [`~transformers.CLIPTokenizer`] to tokenize text.
      unet ([`UNet3DConditionModel`]):
          A [`UNet3DConditionModel`] to denoise the encoded video latents.
      scheduler ([`SchedulerMixin`]):
          A scheduler to be used in combination with `unet` to denoise the encoded image latents. Can be one of
          [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
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docstr: Enables the FreeU mechanism as in https://arxiv.org/abs/2309.11497.
  
  The suffixes after the scaling factors represent the stages where they are being applied.
  
  Please refer to the [official repository](https://github.com/ChenyangSi/FreeU) for combinations of the values
  that are known to work well for different pipelines such as Stable Diffusion v1, v2, and Stable Diffusion XL.
  
  Args:
      s1 (`float`):
          Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to
          mitigate "oversmoothing effect" in the enhanced denoising process.
      s2 (`float`):
          Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to
          mitigate "oversmoothing effect" in the enhanced denoising process.
      b1 (`float`): Scaling factor for stage 1 to amplify the contributions of backbone features.
      b2 (`float`): Scaling factor for stage 2 to amplify the contributions of backbone features.
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code: def enable_freeu(self, s1: float, s2: float, b1: float, b2: float):
      r"""Enables the FreeU mechanism as in https://arxiv.org/abs/2309.11497.
  
      The suffixes after the scaling factors represent the stages where they are being applied.
  
      Please refer to the [official repository](https://github.com/ChenyangSi/FreeU) for combinations of the values
      that are known to work well for different pipelines such as Stable Diffusion v1, v2, and Stable Diffusion XL.
  
      Args:
          s1 (`float`):
              Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to
              mitigate "oversmoothing effect" in the enhanced denoising process.
          s2 (`float`):
              Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to
              mitigate "oversmoothing effect" in the enhanced denoising process.
          b1 (`float`): Scaling factor for stage 1 to amplify the contributions of backbone features.
          b2 (`float`): Scaling factor for stage 2 to amplify the contributions of backbone features.
      """
      if not hasattr(self, "unet"):
          raise ValueError(
              "The pipeline must have `unet` for using FreeU."
          )
      self.unet.enable_freeu(s1=s1, s2=s2, b1=b1, b2=b2)
  
imports: import inspect
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import PIL.Image
  import torch
  from transformers import CLIPTextModel, CLIPTokenizer
  from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
  from ...models import AutoencoderKL, UNet3DConditionModel
  from ...models.lora import adjust_lora_scale_text_encoder
  from ...schedulers import KarrasDiffusionSchedulers
  from ...utils import USE_PEFT_BACKEND, deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
  from ...utils.torch_utils import randn_tensor
  from ..pipeline_utils import DiffusionPipeline
  from .None import TextToVideoSDPipelineOutput
label_desc: Use image node_id 13 for calling the VideoToVideoSDPipeline obj's underlying member method code with example usage: obj.enable_freeu(s1, s2, b1, b2) without return types