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import torch | |
import torch.nn as nn | |
import torch.nn.functional as F | |
from torch.autograd import Variable | |
from layers import * | |
import os | |
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1): | |
"""3x3 convolution with padding""" | |
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, |
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from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
import argparse | |
import os | |
import pprint | |
import torch | |
import torch.nn.parallel | |
import torch.backends.cudnn as cudnn |