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models.py
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models.py
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import torch
import torch.nn as nn
import torch.nn.functional as F
# ------ TO DO ------
class cls_model(nn.Module):
def __init__(self, num_classes=3):
super(cls_model, self).__init__()
pass
def forward(self, points):
'''
points: tensor of size (B, N, 3)
, where B is batch size and N is the number of points per object (N=10000 by default)
output: tensor of size (B, num_classes)
'''
pass
# ------ TO DO ------
class seg_model(nn.Module):
def __init__(self, num_seg_classes = 6):
super(seg_model, self).__init__()
pass
def forward(self, points):
'''
points: tensor of size (B, N, 3)
, where B is batch size and N is the number of points per object (N=10000 by default)
output: tensor of size (B, N, num_seg_classes)
'''
pass