找出这段代码错误import tensorflow as tf from tensorflow.keras import layers class GCNModel(tf.keras.Model): def __init__(self, hidden_dim, output_dim): super(GCNModel, self).__init__() self.gc1 = GraphConvolution(hidden_dim) self.gc2 = GraphConvolution(output_dim) self.relu = layers.ReLU() self.dropout = layers.Dropout(0.5) self.dense = layers.Dense(1) def call(self, inputs): x, adj = inputs x = self.gc1(x, adj) x = self.relu(x) x = self.dropout(x) x = self.gc2(x, adj) x = self.dense(tf.reduce_mean(x, axis=1)) return x loss_fn = tf.keras.losses.MeanSquaredError() metrics = [tf.keras.metrics.MeanAbsoluteError(), tf.keras.metrics.RootMeanSquaredError()] optimizer = tf.keras.optimizers.Adam(learning_rate=0.01) model = GCNModel(hidden_dim=64, output_dim=32) model.compile(optimizer=optimizer, loss=loss_fn, metrics=metrics) history=model.fit((train_features,train_adj),train_labels,epochs=50,validation_data=((val_features, val_adj), val_labels)) test_scores = model.evaluate((test_features, test_adj), test_labels, verbose=0)

这段代码的错误是缺少GraphConvolution类的定义和导入。需要在代码开头添加类的定义和导入。如果已经定义了GraphConvolution类，则可能是没有导入GraphConvolution类所在的模块。