小编pro*_*pro的帖子

我正在尝试在 Cifar 10 数据集上训练我的自定义模型。我的模型代码如下： -

class cifar10Model(keras.Model):
  def __init__(self):
    super(cifar10Model, self).__init__()
    self.conv1 = keras.layers.Conv2D(32, 3, activation='relu', input_shape=(32, 32, 3))
    self.pool1 = keras.layers.MaxPool2D((3, 3))
    self.batch_norm1 = keras.layers.BatchNormalization()
    self.dropout1 = keras.layers.Dropout(0.1)

    self.conv2 = keras.layers.Conv2D(64, 3, activation='relu')
    self.pool2 = keras.layers.MaxPool2D((3, 3))
    self.batch_norm2 = keras.layers.BatchNormalization()
    self.dropout2 = keras.layers.Dropout(0.2)

    self.conv3 = keras.layers.Conv2D(128, 3, activation='relu')
    self.pool3 = keras.layers.MaxPool2D((3, 3))
    self.batch_norm3 = keras.layers.BatchNormalization()
    self.dropout3 = keras.layers.Dropout(0.3)

    self.flatten = keras.layers.Flatten()
    self.dense1 = keras.layers.Dense(128, activation='relu')
    self.dense2 = keras.layers.Dense(10)

    def call(self, x):
      x = self.conv1(x)
      x = self.pool1(x)
      x = …