from torch.utils.tensorboard import SummaryWriter logdir = "logs" writer = SummaryWriter(logdir)
# Log a scalar value iteration = 0 loss = 3.14 writer.add_scalar("train/loss", loss, iteration)
writer.close()This will ensure that all the data is written to disk and the logging process is safely stopped. In summary, the `torch.utils.tensorboard.SummaryWriter` is a useful class in the PyTorch package library that allows convenient logging of data to TensorBoard from within PyTorch code. With this tool, we can quickly visualize and analyze large amounts of data, accelerating the development of machine learning models.