tensorboard的使用

import tensorflow as tf
import datetime

datapath  = r'D:datamlmnist.npz'
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data(datapath)

x_train = tf.keras.utils.normalize(x_train, axis=1)
x_test = tf.keras.utils.normalize(x_test, axis=1)

model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
model.add(tf.keras.layers.Dense(10, activation=tf.nn.softmax))

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

log_dir = 'D:/data/log/' + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)

model.fit(x=x_train,
          y=y_train,
          epochs=3,
          validation_data=(x_test, y_test),
          callbacks=[tensorboard_callback])
print(log_dir)

执行  tensorboard --logdir D:/data/log/20191018-162001 查看