TensorBoard - Plot training and validation losses on the same graph?

Question

Is there a way to plot both the training losses and validation losses on the same graph?

It\'s easy to have two separate scalar summaries for each of them i

Answer 1

Please let me contribute with some code sample in the answer given by @Lifu Huang. First download the loger.py from here and then:

from logger import Logger
def train_model(parameters...):
    N_EPOCHS = 15
    # Set the logger
    train_logger = Logger('./summaries/train_logs')
    test_logger = Logger('./summaries/test_logs')
    for epoch in range(N_EPOCHS):

        # Code to get train_loss and test_loss

        # ============ TensorBoard logging ============#
        # Log the scalar values
        train_info = {
            'loss': train_loss,
        }
        test_info = {
            'loss': test_loss,
        }

        for tag, value in train_info.items():
            train_logger.scalar_summary(tag, value, step=epoch)
        for tag, value in test_info.items():
            test_logger.scalar_summary(tag, value, step=epoch)

Finally you run tensorboard --logdir=summaries/ --port=6006and you get: