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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
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