📅  最后修改于: 2022-03-11 14:55:52.547000             🧑  作者: Mango
import keras
import numpy as np
inp = keras.layers.Input(shape=(10,))
dense = keras.layers.Dense(10, activation='relu')(inp)
out = keras.layers.Dense(1, activation='sigmoid')(dense)
model = keras.models.Model(inp, out)
model.compile(optimizer="adam", loss="binary_crossentropy",)
# Just a noise data for fast working example
X = np.random.normal(0, 1, (1000, 10))
y = np.random.randint(0, 2, 1000)
# create and use callback:
saver = CustomSaver()
model.fit(X, y, callbacks=[saver], epochs=5)