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from collections import OrderedDict
import numpy as np
import torch
import torch.nn as nn
import torchvision
from .normalizer import Normalizer
class RGBResNext50(nn.Sequential):
def __init__(self):
super(RGBResNext50, self).__init__()
self.resnext = torch.hub.load('pytorch/vision:v0.6.0', 'resnext50_32x4d', pretrained=True)
self.normalizer = Normalizer()
super(RGBResNext50, self).__init__(self.normalizer, self.resnext)
class RGBResNext101(nn.Sequential):
def __init__(self):
super(RGBResNext101, self).__init__()
self.resnext = torch.hub.load('pytorch/vision:v0.6.0', 'resnext101_32x8d', pretrained=True)
self.normalizer = Normalizer()
super(RGBResNext101, self).__init__(self.normalizer, self.resnext)
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