Initialize the RMSNorm normalization layer. Args: dim (int): The dimension of the input tensor.

[summary] Args: nsample (int): maximum number of features to gather in the ball use_xyz (bool, optional): concate xyz

:param radius: float, radius of ball :param nsample: int, maximum number of features to gather in the ball :param use_xyz:

:param npoint: int :param radii: list of float, list of radii to group with :param nsamples: list of int, number of samples i

:param mlp: list of int :param bn: whether to use batchnorm

Decay the learning rate with half-cycle cosine after warmup

Decay the learning rate with half-cycle cosine after warmup

:param ctx: :param grad_out: (B, C, N) tensor with gradients of outputs :return: grad_features: (B, C, M) tensor

:param ctx: :param grad_out: (B, C, npoint, nsample) tensor of the gradients of the output from forward :return:

Forward pass through the RMSNorm layer. Args: x (torch.Tensor): The input tensor. Returns:

Args: support ([tensor]): [B, N, C] query ([tensor]): [B, M, C] Returns: [int]: neighbor idx. [B,

:param ctx: :param features: (B, C, N) tensor of features to group :param idx: (B, npoint, nsample) tensor containing the ind

:param query_xyz: (B, N, 3) xyz coordinates of the features :param support_xyz: (B, npoint, 3) centroids :param features: (B,

Uses iterative furthest point sampling to select a set of npoint features that have the largest minimum distance :param ctx:

Uses iterative furthest point sampling to select a set of npoint features that have the largest minimum distance :param ctx:

:param ctx: :param features: (B, C, N) :param idx: (B, npoint) index tensor of the features to gather :return:

Find the three nearest neighbors of unknown in known :param ctx: :param unknown: (B, N, 3) :param known: (B, M, 3)

Performs weight linear interpolation on 3 features :param ctx: :param features: (B, C, M) Features descriptors to be interpol

:param ctx: :param features: (B, C, N) tensor of features to group :param idx: (B, npoint, nsample) tensor containing the ind

:param ctx: :param radius: float, radius of the balls :param nsample: int, maximum number of features in the balls :p

:param xyz: (B, N, 3) xyz coordinates of the features :param new_xyz: (B, npoint, 3) centroids :param features: (B, C, N) des

:param xyz: (B, N, 3) xyz coordinates of the features :param new_xyz: ignored :param features: (B, C, N) descriptors of the f