def __init__(self, in_channels, out_channels, stride=1):
super(ResBlock, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.conv1 = Conv2d(in_channels,
out_channels[0],
kernel_size=1,
bias=False)
self.bn1 = BatchNorm2d(out_channels[0])
self.relu = ReLU(True)
self.conv2 = Conv2d(out_channels[0],
out_channels[0],
kernel_size=3,
padding=1,
stride=stride,
bias=False)
self.bn2 = self.bn1
self.conv3 = Conv2d(out_channels[0],
out_channels[1],
kernel_size=1,
bias=False)
self.bn3 = BatchNorm2d(out_channels[1])
if in_channels != out_channels:
self.downsample = _make_downsample(in_channels, out_channels[1],
stride)
initialize_weights(self)
def __init__(self, cfg, init_weights=True):
super(CNN_2_Layer, self).__init__()
self.cfg = cfg
self.CNN = self._make_cnn()
self.FCN = self._make_fcn()
if init_weights:
initialize_weights(self)
def __init__(self, cfg):
super(ResNet, self).__init__()
self.cfg = cfg
self.ResNet = _make_resnet(self)
avg_in = int(cfg.MODEL.BACKBONE.INPUT_RESOLUTION *
cfg.MODEL.RESNET.POOLER_SCALE[-1])
self.avgpool = AvgPool2d(avg_in, stride=1)
initialize_weights(self)
def __init__(self, config, init_weights=True):
super(ImageClassifier, self).__init__()
self.cfg = config
self.back_bone = _make_back_bone(self.cfg)
self.classifier = _make_classifier(self.cfg)
if init_weights:
initialize_weights(self)
# 其他参数
self.epoch = 0
def __init__(self, cfg):
super(BackBone, self).__init__()
self.cfg = cfg
# 搭建主干网
if 'VGG' in self.cfg.MODEL.BACKBONE.NAME:
self.features = _make_CNN(cfg)
elif 'ResNet' in self.cfg.MODEL.BACKBONE.NAME:
self.features = _make_resnet(cfg)
initialize_weights(self)
def __init__(self, cfg, init_weights=True):
super(SingleLayer, self).__init__()
self.cfg = cfg
self.layer1 = Linear(784, 200)
self.dropout = Dropout(0.5)
self.layer2 = Linear(200, 10)
self.ReLU = ReLU(inplace=True)
if init_weights:
initialize_weights(self)
def __init__(self, cfg):
super(FangClassification, self).__init__()
self.cfg = cfg
self.backbone = _make_back_bone(cfg)
self.classifier = _make_classifier(cfg)
initialize_weights(self)
def __init__(self, cfg):
super(Classifier, self).__init__()
self.cfg = cfg
self.drop = Dropout(0.5)
self.FCN = _make_FCN(cfg)
initialize_weights(self)