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import torch
import torch.nn as nn
class MeanVFE(nn.Module):
def __init__(self):
super().__init__()
def forward(self, batch_dict, **kwargs):
"""
Args:
batch_dict:
voxels: (num_voxels, max_points_per_voxel, C)
voxel_num_points: optional (num_voxels)
**kwargs:
Returns:
vfe_features: (num_voxels, C)
"""
voxel_features, voxel_num_points = batch_dict['voxels'], batch_dict['voxel_num_points']
points_mean = voxel_features[:, :, :].sum(dim=1, keepdim=False)
normalizer = torch.clamp_min(voxel_num_points.view(-1, 1), min=1.0).type_as(voxel_features)
points_mean = points_mean / normalizer
batch_dict['voxel_features'] = points_mean.contiguous()
return batch_dict
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