r""" Generates video frames from input first-last frame and text prompt using diffusion process. Args: input_prompt (`str

r""" Generates video frames from input image and text prompt using diffusion process. Args: input_prompt (`str`):

r""" Generates video frames from text prompt using diffusion process. Args: input_prompt (`str`): Text pr

Generate audio from either raw phonemes or pre-processed tokens. Args: tokens: Either a phoneme string or list of pre-pro

Ensures interchangeability with schedulers that need to scale the denoising model input depending on the current timestep. Ar

Ensures interchangeability with schedulers that need to scale the denoising model input depending on the current timestep. A

Sets the begin index for the scheduler. This function should be run from pipeline before the inference. Args: begin_index

Sets the begin index for the scheduler. This function should be run from pipeline before the inference. Args: begin_inde

Sets the discrete timesteps used for the diffusion chain (to be run before inference). Args: num_inference_steps (`int`):

The index counter for current timestep. It will increase 1 after each scheduler step.

The index counter for current timestep. It will increase 1 after each scheduler step.

Convert a string to a boolean. Supported true values: 'yes', 'true', 't', 'y', '1' Supported false values: 'no', 'false', 'f', 'n', '0'

x: A list of videos each with shape [C, T, H, W]. t: [B]. context: A list of text embeddings each with s

x: A list of videos each with shape [C, T, H, W]. t: [B]. context: A list of text embeddings each with s

XLMRobertaLarge adapted from Huggingface.