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

The solution in PyTorch 1.5 with the approach of two writers:

import os
from torch.utils.tensorboard import SummaryWriter

LOG_DIR = "experiment_dir"
train_writer = SummaryWriter(os.path.join(LOG_DIR, "train"))
val_writer = SummaryWriter(os.path.join(LOG_DIR, "val"))

# while in the training loop
for k, v in train_losses.items()
    train_writer.add_scalar(k, v, global_step)

# in the validation loop
for k, v in val_losses.items()
    val_writer.add_scalar(k, v, global_step)

# at the end
train_writer.close()
val_writer.close()

Keys in the train_losses dict have to match those in the val_losses to be grouped on the same graph.