# Installa TensorFlow

import tensorflow as tf
mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
model = tf.keras.models.Sequential([
  tf.keras.layers.Flatten(input_shape=(28, 28)),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(10, activation='softmax')
])

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

log_dir = os.path.join('logs', 'fit', datetime.datetime.now().strftime('%Y%m%d-%H%M%S'))
print(log_dir)

os.makedirs(log_dir, exist_ok=True)
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)

model.fit(x_train, y_train, validation_data=(x_test, y_test), epochs=5, callbacks=[tensorboard_callback])

model.evaluate(x_test,  y_test, verbose=2)
