r""" Initializes the image-to-video generation model components. Args: config (EasyDict): Object containi

r""" Initializes the Wan text-to-video generation model components. Args: config (EasyDict): Object conta

r""" Initialize the diffusion model backbone. Args: model_type (`str`, *optional*, defaults to 't2v'): Mo

r""" Initialize the diffusion model backbone. Args: model_type (`str`, *optional*, defaults to 't2v'): Mo

Args: api_key: The API key for Dash Scope authentication and access to related services. model_name: Model name, 'qwe

Args: model_name: Use predefined model names such as 'QwenVL2.5_7B' and 'Qwen2.5_14B', which are specific version

Convert x0 prediction to flow matching's prediction. x0_pred: the x0 prediction with shape [B, C, H, W] xt: the input noisy d

Convert x0 prediction to flow matching's prediction. x0_pred: the x0 prediction with shape [B, C, H, W] xt: the input noisy d

read video using decord.VideoReader Args: ele (dict): a dict contains the configuration of video. support keys: - vid

read video using torchvision.io.read_video Args: ele (dict): a dict contains the configuration of video. support keys:

q: [b, s, n_h, d] k: [b, s, n_h, d]

Diffusion forward corruption process. Input: - clean_latent: the clean latent with shape [B, C, H, W] - noise

Diffusion forward corruption process. Input: - clean_latent: the clean latent with shape [B, C, H, W] - noi

Args: grad_dw0_dw2: [B, 2 * Hidden, D] grad_dw1: [B, D, Hidden] Outs: grad_W0: [B, Hidden, D]