Convert rotations given as Euler angles in radians to rotation matrices. Args: euler_angles: Euler angles in radians as tensor of sh

Convert Euler angles to quaternions.

Evaluate the results. Args: runner (:obj:`mmcv.Runner`): The underlined training runner. results (list): Output result

Convert axis-angle rotations (aka exponential maps) to quaternions. Stable formula from "Practical Parameterization of Rotations Usin

Forward function. Args: inputs (tuple): Input data. kwargs (dict): Args for ``mmcv.parallel.scatter_g

h: B, T, D emb: B, D

motion: B, T, D timesteps: [batch_size] (int)

motion: B, T, D

motion: B, T, D

x: B, T, D

x: B, T, D xf: B, N, L

x: B, T, D xf: B, N, L

x: B, T, D xf: B, N, P

x: B, T, D xf: B, N, L

x: B, T, D xf: B, N, L

x: B, T, D xf: B, N, L

x: B, T, D

x: B, T, D xf: B, N, L

Args: input (Tensor): The input for the loss module, i.e., the network prediction. target_is_real (bo

Forward function of loss. Args: pred (torch.Tensor): The prediction. target (torch.Tensor): The learning target of the

Convert rotations given as rotation matrices to axis/angle. Args: matrix: Rotation matrices as tensor of shape (..., 3, 3). Ret

Convert rotations given as rotation matrices to Euler angles in radians. Args: matrix: Rotation matrices as tensor of shape (..., 3,

Converts rotation matrices to 6D rotation representation by Zhou et al. [1] by dropping the last row. Note that 6D representation is not uniq

Extended MSE Loss with GMOF.

Prepare raw data for the f'{idx'}-th data.

Check output folder or file. Args: output_path (str): could be folder or file. allowed_suffix (List[str], optional):

Enforce quaternion continuity across the time dimension by selecting the representation (q or -q) with minimal distance (or, equivalently,

q0: starting quaternion q1: ending quaternion t: array of points along the way Returns: Tensor of Slerps: t.shape + q0.shape

Apply the rotation given by a quaternion to a 3D point. Usual torch rules for broadcasting apply. Args: quaternion: Tensor of qu

Multiply two quaternions representing rotations, returning the quaternion representing their composition, i.e. the versor with nonnegative re

Generate a single random 3x3 rotation matrix. Args: dtype: Type to return device: Device of returned tensor. Default: if Non

Converts 6D rotation representation by Zhou et al. [1] to rotation matrix using Gram--Schmidt orthogonalisation per Section B of [1]. Arg

Importance-sample timesteps for a batch. :param batch_size: the number of timesteps. :param device: the torch device to save

Set requies_grad for all the networks. Args: nets (nn.Module | list[nn.Module]): A list of networks or a single network.