def __init__(self, args):
super(cnn_TR2, self).__init__()
self.cnn_1 = cnn()
self.cnn_2 = cnn()
self.tr_1 = TR(args, (24, 8, 8), 64)
self.tr_2 = TR(args, (24, 8, 8), 64)
self.final = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 32), nn.ReLU(),
nn.Linear(32, 2))
def __init__(self, args):
super(cnn_test2, self).__init__()
self.cnn_1 = cnn()
self.cnn_2 = cnn()
self.tr_1 = TR(args, (24, 8, 8), 64)
self.sf_1 = SF(args, (24, 8, 8), 64)
self.tr_2 = TR(args, (24, 8, 8), 64)
self.sf_2 = SF(args, (24, 8, 8), 64)
self.af_1 = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 64), nn.ReLU())
self.af_2 = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 64), nn.ReLU())
self.final = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 32), nn.ReLU(),
nn.Dropout(p=0.1), nn.Linear(32, 2))
def __init__(self, args, fourier):
super(res_TR, self).__init__()
self.conv = transfer_img(fourier)
self.resnet = resnet50_F()
self.cnn_c = cnn_C()
self.tr = TR(args, (24, 8, 8), 2)
def __init__(self, args):
super(cnn_test, self).__init__()
self.cnn = cnn()
self.tr = TR(args, (24, 8, 8), 64)
self.sf = SF(args, (24, 8, 8), 64)
self.final = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 32), nn.ReLU(),
nn.Linear(32, 2))
def __init__(self, args, fourier):
super(res_test, self).__init__()
self.conv = transfer_img(fourier)
self.resnet = resnet50_F()
self.tr = TR(args, (24, 8, 8), 64)
self.sf = SF(args, (24, 8, 8), 64)
self.cnn_c = cnn_C()
self.final = nn.Sequential(nn.Linear(128, 64), nn.ReLU(),
nn.Linear(64, 32), nn.ReLU(),
nn.Linear(32, 2))
def __init__(self, args):
super(res_TR, self).__init__()
self.resnet = resnet50()
self.tr = TR(args, (24, 8, 8), 2)