Standard multivariate normal prior Assume z is batched

Slide along the long edge, with the short edge as crop size

Sample from top-k logits. Arguments: logits: Tensor of shape (batch_size, vocab_size)

returns a sampling function for calculating likelihood with given ODE settings Args: - sampling_method: type of sampler used in solvin

returns a sampling function with given SDE settings Args: - sampling_method: type of sampler used in solving the SDE; default to be Eu

u: r(B D L) delta: r(B D L) A: c(D N) or r(D N) B: c(D N) or r(B N L) or r(B N 2L) or r(B G N L) or (B G N L) C: c(D N) or r(B N

Argument: state: (batch, dim, dstate) x: (batch, dim) dt: (batch, dim) A: (dim, dstate) B: (batch, dstate

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These ma

Convert tensor data type from uint8 to float, divide value by 255.0 and permute the dimensions of clip tensor Args: clip (torch.t

Drops labels to enable classifier-free guidance.

Drops labels to enable classifier-free guidance.

Force network to always be in evaluation mode.

Loss for training the score model Args: - model: backbone model; could be score, noise, or velocity - x1: datapoint -

x: (N, T, patch_size**2 * C) imgs: (N, H, W, C)

x: (N, T, patch_size**2 * C) imgs: (N, H, W, C)

Constructor

Args: clip (torch.tensor): Video clip to be cropped. Size is (T, C, H, W) Returns: torch.tensor: randomly cro

Args: clip (torch.tensor): Video clip to be cropped. Size is (T, C, H, W) Returns: torch.tensor: scale resize

Args: clip (torch.tensor): Video clip to be cropped. Size is (T, C, H, W) Returns: torch.tensor: scale resize

Args: clip (torch.tensor): Video clip to be cropped. Size is (T, C, H, W) Returns: torch.tensor: center cropp

Args: clip (torch.tensor): video clip must be normalized. Size is (C, T, H, W)

Args: clip (torch.tensor, dtype=torch.uint8): Size is (T, C, H, W) Return: clip (torch.tensor, dtype=torch.fl

Args: clip (torch.tensor): Size is (T, C, H, W) Return: clip (torch.tensor): Size is (T, C, H, W)

Constructor for a general sampler; supporting different sampling methods Args: - transport: an tranport object specify model predictio

Simple block wrapping a mixer class with LayerNorm/RMSNorm and residual connection" This Block has a slightly different structure co

Initializes I3D model instance. Args: num_classes: The number of outputs in the logit layer (default 400, which matche