r""" The function to the pipeline for image inversion as described by the [LEDITS++ Paper](https://arxiv.org/abs/2301.12247). If the s

Convert a numpy image or a batch of images to a PIL image.

Applies the FreeU mechanism as introduced in https: //arxiv.org/abs/2309.11497. Adapted from the official code repository: https://github.com/Chen

Activates gradient checkpointing for the current model (may be referred to as *activation checkpointing* or *checkpoint activations*

r""" Encodes the prompt into text encoder hidden states. Args: prompt (`str` or `List[str]`, *optional*):

Convert a NumPy image to a PyTorch tensor.

r""" Removes all hooks that were added when using `enable_sequential_cpu_offload` or `enable_model_cpu_offload`.

This function return the height and width that are downscaled to the next integer multiple of `vae_scale_factor`. Args:

Reads a checkpoint file, returning properly formatted errors if they arise.

Upload model, scheduler, or pipeline files to the 🤗 Hugging Face Hub. Parameters: repo_id (`str`): The n

To run a test in a subprocess. In particular, this can avoid (GPU) memory issue. Args: test_case (`unittest.TestCase`):

Predict the sample from the previous timestep by reversing the SDE. This function propagates the diffusion process from the learned m

r"""Move internal buffers of the ExponentialMovingAverage to `device`. Args: device: like `device` argument to `torch.Tensor.to`

Construct a layernorm module in the T5 style. No bias and no subtraction of mean.