请帮助我进行以下操作。我似乎无法保存模型。如您所见,我确实引用了Sequential()
方法的实例
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.InputLayer(input_shape=[timePortion,1 ]))
model.add(tf.keras.layers.Conv1D(kernel_size=timePortion,
filters=1000,
strides=1,
use_bias=False,
activation="relu",
kernel_initializer=tf.keras.initializers.VarianceScaling))
model.summary()
model.add(tf.keras.layers.Dropout(rate=0.2))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(32,
activation='relu',
kernel_initializer=tf.keras.initializers.VarianceScaling))
model.add(tf.keras.layers.Dense(8,
activation='relu',
kernel_initializer=tf.keras.initializers.VarianceScaling))
model.add(tf.keras.layers.Dense(1,
kernel_initializer=tf.keras.initializers.VarianceScaling))
model.summary()
model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
loss="mean_squared_error",
metrics=["accuracy","mae"])
filepath = "model.h5"
model.fit(inputs,
labels,
steps_per_epoch=1,
epochs=2,
shuffle=False,
verbose=1)
tf.keras.models.save_model(model,
filepath,
overwrite=True,
include_optimizer=True)
我在将模型保存到Jupyter笔记本电脑时遇到问题。该文件实际上已创建,但随后出现此错误。这很奇怪,因为我正在引用模型实例。
TypeError: get_config() missing 1 required positional argument: 'self'
答案 0 :(得分:1)
问题在于内核初始化程序无法序列化,因为您尚未实例化它。要实例化它,请添加圆括号()
:
kernel_initializer=tf.keras.initializers.VarianceScaling()