怎么在keras中记录损失loss,并保存到文件中

使用回调函数callback

以下为简单例子:

class LossHistory(keras.callbacks.Callback):
    def on_train_begin(self, logs={}):
        self.losses = []

    def on_batch_end(self, batch, logs={}):
        self.losses.append(logs.get('loss'))
#定义损失历史类
model = Sequential()
model.add(Dense(10, input_dim=784, kernel_initializer='uniform'))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer='rmsprop')
#构建模型
history = LossHistory()
model.fit(x_train, y_train, batch_size=128, epochs=20, verbose=0, callbacks=[history])
#训练,使用callback保存loss
print(history.losses)
# 输出
'''
[0.66047596406559383, 0.3547245744908703, ..., 0.25953155204159617, 0.25901699725311789]

也可以使用一下命令将损失记录在log.txt文件中

with open(‘log.txt’,‘a’, encoding='utf-8') as f:

    f.write(history.losses)

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转载自blog.csdn.net/yang_daxia/article/details/84571658