point-voxel transformer

Point-Voxel Transformer是一种3D Transformer，它可以同时处理点云和体素数据。它是基于点云和体素之间的相互转换来实现的。具体来说，它使用了一个Point-Voxel Feature Propagation模块，该模块可以将点云特征映射到体素空间中，然后使用一个Voxel-Point Feature Aggregation模块将体素特征映射回点云空间中。这样，Point-Voxel Transformer就可以同时处理点云和体素数据，从而提高了3D Transformer的灵活性和适用性。

下面是一个Point-Voxel Transformer的示例代码：

import torch
import torch.nn as nn

class PointVoxelTransformer(nn.Module):
    def __init__(self, num_points, num_voxels, num_channels):
        super(PointVoxelTransformer, self).__init__()
        self.num_points = num_points
        self.num_voxels = num_voxels
        self.num_channels = num_channels
        
        # Point-wise Transformer
        self.point_transformer = nn.MultiheadAttention(embed_dim=num_channels, num_heads=8)
        
        # Voxel-wise Transformer
        self.voxel_transformer = nn.MultiheadAttention(embed_dim=num_channels, num_heads=8)
        
        # Point-Voxel Feature Propagation
        self.point_voxel_propagation = nn.Linear(num_channels, num_channels)
        
        # Voxel-Point Feature Aggregation
        self.voxel_point_aggregation = nn.Linear(num_channels, num_channels)
        
    def forward(self, points, voxels):
        # Point-wise Transformer
        point_features = self.point_transformer(points, points, points)[0]
        
        # Voxel-wise Transformer
        voxel_features = self.voxel_transformer(voxels, voxels, voxels)[0]
        
        # Point-Voxel Feature Propagation
        voxel_features_propagated = self.point_voxel_propagation(point_features)
        
        # Voxel-Point Feature Aggregation
        point_features_aggregated = self.voxel_point_aggregation(voxel_features)
        
        return point_features_aggregated, voxel_features_propagated