| import numpy as np | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| from functools import partial | |
| from config import Config | |
| config = Config() | |
| class BasicLatBlk(nn.Module): | |
| def __init__(self, in_channels=64, out_channels=64, inter_channels=64): | |
| super(BasicLatBlk, self).__init__() | |
| inter_channels = in_channels // 4 if config.dec_channels_inter == 'adap' else 64 | |
| self.conv = nn.Conv2d(in_channels, out_channels, 1, 1, 0) | |
| def forward(self, x): | |
| x = self.conv(x) | |
| return x | |