import tensorflow as tf
from tensorflow import keras
fashion_mnist=keras.datasets.fashion_mnist
(train_images,train_labels),(test_images,test_labels)=fashion_mnist.load_data()
train_images=train_images/255.0
test_images=test_images/255.0
model=keras.Sequential(layers=[
keras.layers.Flatten(input_shape=(28,28)),
keras.layers.Dense(128,activation='relu'),
keras.layers.Dense(10)
])
model.compile(optimizer='adam',
loss=keras.losses.SparseCategoricalCrossentropy(
from_logits=True),
metrics=['accuracy'])
model.fit(train_images,train_labels,epochs=3,batch_size=64)
#测试
model.evaluate(test_images,test_labels)
predicted_model=keras.Sequential(layers=[model,keras.layers.Softmax()])
predicted=predicted_model.predict(train_images[:10])
print(predicted)
