from __future__ import absolute_import, division, print_function, unicode_literals

# TensorFlow and tf.keras
import tensorflow as tf
from tensorflow import keras

# Helper libraries
import numpy as np
import matplotlib.pyplot as plt


fashion_mnist = keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()

train_images, test_images = train_images/255.0, test_images/255.0

model = keras.Sequential([

    keras.layers.Flatten(input_shape=(28,28)),
    keras.layers.Dense(128, activation='relu'),
    keras.layers.Dense(10, activation='softmax')

])


model.compile(
optimizer = 'adam',
loss = 'sparse_categorical_crossentropy',
metrics = ['accuracy']
)

model.fit(train_images, train_labels, epochs=1)

test_loss, test_acc = model.evaluate(test_images, test_labels)
print('\nTest accuracy:', test_acc)
