tensorflow-single-node(Python)

import tensorflow as tf

from tensorflow.keras import models, layers, datasets

import datetime, uuid

# Verify that we're using TensorFlow 2.x or 1.15

assert tf.__version__.startswith("2.") or tf.__version__.startswith("1.15")

(x_train, y_train), (x_test, y_test) = datasets.mnist.load_data()

x_train, x_test = x_train / 255.0, x_test / 255.0

model = models.Sequential([

  layers.Flatten(input_shape=(28, 28)),

  layers.Dense(10, activation='softmax')

])

model.compile(optimizer=tf.keras.optimizers.SGD(learning_rate=0.5),

              loss=tf.keras.losses.sparse_categorical_crossentropy,

              metrics=['accuracy'])

# Define a user unique directory in DBFS

try:

  username = dbutils.notebook.entry_point.getDbutils().notebook().getContext().tags().apply('user')

except:

  username = str(uuid.uuid1()).replace("-", "")

experiment_log_dir = "/dbfs/user/{}/tensorboard_log_dir/".format(username)

%load_ext tensorboard

%tensorboard --logdir $experiment_log_dir

run_log_dir = experiment_log_dir + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")

tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=run_log_dir, histogram_freq=1)

​

model.fit(x_train, y_train, epochs=5, batch_size=64, callbacks=[tensorboard_callback])

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