Expects a two dimensional flow image of shape [H,W,2] According to the C++ source code of Daniel Scharstein According to the Matlab sourc

Forward pass. Args: x (tensor): input Returns: tensor: output

Forward pass. Returns: tensor: output

Apply the module to `x` given `emb` timestep embeddings.

Apply the block to a Tensor, conditioned on a timestep embedding. :param x: an [N x C x ...] Tensor of features. :param emb:

Apply QKV attention. :param qkv: an [N x (H * 3 * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor afte

Apply QKV attention. :param qkv: an [N x (3 * H * C) x T] tensor of Qs, Ks, and Vs. :return: an [N x (H * C) x T] tensor afte

Apply the model to an input batch. :param x: an [N x C x ...] Tensor of inputs. :param timesteps: a 1-D batch of timesteps.

Create a linear module.

Take the mean over all non-batch dimensions.

Normalize coordinates of image scale to [-1, 1] Args: grid: [B, 2, H, W]

Scale the parameters of a module and return it.

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

Write optical flow to file. If v is None, uv is assumed to contain both u and v channels, stacked in depth. Original code by Deqing