Question

我在Colaboratory中建立了这个简单的神经网络。我想查看训练有素的参数的值，因此我使用了回调和ModelCheck。代码工作正常，但是当我下载文件（3.12M）时，我什么也没找到。我在做什么错了？

import keras
from keras.datasets import mnist

(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
from keras import models
from keras import layers

network = models.Sequential()
network.add(layers.Dense(512, activation='relu', input_shape=(28 * 28,)))
network.add(layers.Dense(10, activation='softmax'))
callbacks_list = [keras.callbacks.EarlyStopping(monitor='acc', patience=1,),keras.callbacks.ModelCheckpoint(filepath='my_model.hdf5',monitor='val_acc',save_best_only=True,)]
network.compile(optimizer='rmsprop',
            loss='categorical_crossentropy',
            metrics=['accuracy'])
train_images = train_images.reshape((60000, 28 * 28))
train_images = train_images.astype('float32') / 255

test_images = test_images.reshape((10000, 28 * 28))
test_images = test_images.astype('float32') / 255
from keras.utils import to_categorical

train_labels = to_categorical(train_labels)
test_labels = to_categorical(test_labels)
history=network.fit(train_images, train_labels, epochs=20, batch_size=128,callbacks=callbacks_list,validation_data=(train_images, train_labels))
network.evaluate(test_images, test_labels)

ps。我用hdfview打开了

Keras中的ModelCheckpoint存储了一个3.12M文件，但是当我用hdfview打开它时，似乎没有任何保存

0 个答案: