Python CONFIG.FeatureLen Examples

Example #1

 def __init__(self):
     super(Attacker, self).__init__()  # 调用父类初始化
     self.attack = False
     self.conv1 = GCNConv(CONFIG.FeatureLen(), 180)
     self.conv2 = GCNConv(180, 120)
     self.lin1 = torch.nn.Linear(120, CONFIG.ClassNum())
     # 这次反而需要调整的参数是输入
     self.X = torch.tensor([1], dtype=torch.float)
     self.edges = torch.tensor([[], []], dtype=torch.long)

Example #2

File: OpData.py Project: HELLORPG/Attack-Graph-Model

def GetFeatures() -> np.matrix:
    features_ndarray = OpFile.ReadFeatures()
    features_matrix = features_ndarray.reshape(
        (len(features_ndarray), CONFIG.FeatureLen()))
    return features_matrix

Example #3

File: RPGGCN.py Project: HELLORPG/Attack-Graph-Model

 def __init__(self, drop=0.5, conv1_hide=100, leaky=0.01):
     super(RPGGCN, self).__init__()  # 调用父类
     self.drop = drop    # 在dropout操作中，元素被置为0的概率
     self.leaky = leaky
     self.conv1 = GCNConv(CONFIG.FeatureLen(), conv1_hide)
     self.conv2 = GCNConv(conv1_hide, CONFIG.ClassNum())

Example #4

 def __init__(self):
     super(GCNClassifier, self).__init__()  # 调用父类初始化
     self.conv1 = GCNConv(CONFIG.FeatureLen(), 180)
     self.conv2 = GCNConv(180, 120)
     # self.conv3 = GCNConv(100, CONFIG.ClassNum())
     self.lin1 = torch.nn.Linear(120, CONFIG.ClassNum())