When using jupyter notebook, and try to using
tf.summary.scalar('loss', loss)
merged = tf.summary.merge_all()
with tf.Session() as sess:
train_writer = tf.summary.FileWriter('./train', sess.graph)
sess.run(tf.global_variables_initializer())
for step in range(200):
summ, _ = sess.run([merged, train], feed_dict={x: x_data, y:y_data})
train_writer.add_summary(summ, step)
prediction_value = sess.run(predict, feed_dict={x:x_data})
plt.figure()
plt.scatter(x_data, y_data)
plt.plot(x_data, prediction_value, 'r-')
plt.show()
This will success when the first time you open a notebook and run the code. But will fail, when you want to run the same cell again
But same exactly code, will pass and generated correact report when directly running the code.
