tensorflow_tensorboard_scalar_logging_quickstart.py

1import tensorflow as tf
2import datetime
3
4# 1. Create a directory for logs
5log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
6
7# 2. Setup a summary writer
8summary_writer = tf.summary.create_file_writer(log_dir)
9
10# 3. Log some scalar data
11# If tensorboard-data-server is installed, TensorBoard will use it 
12# to read these files significantly faster during visualization.
13with summary_writer.as_default():
14    for step in range(100):
15        tf.summary.scalar('loss', 0.1 * (0.9 ** step), step=step)
16        tf.summary.scalar('accuracy', 1.0 - (0.1 * (0.9 ** step)), step=step)
17
18print(f"Data logged to {log_dir}. Run 'tensorboard --logdir logs' to view.")