Collection of snippets of tensorboard usage with pytorch using the tensorboardX library.

Requirements

pip install torch
pip install tensorflow
pip install tensorboard

Run tensorboard

tensorboard --logdir runs

Open up the webapp in your browser, usually at http://localhost:6006.

Training script

import numpy as np
from torch.utils.tensorboard import SummaryWriter

## clean run folder
import shutil
import time
shutil.rmtree('runs', ignore_errors=True)


## run 1
writer = SummaryWriter(flush_secs=1)
for x in range(100):
    noise = np.random.normal(scale=1)
    y = (x/20)**2 + noise
    writer.add_scalar('noisy_parabola', y, x)
    time.sleep(0.1)
writer.close()


## run 2
writer = SummaryWriter(flush_secs=1)
for x in range(100):
    noise = np.random.normal(scale=6)
    y = (x/20)**2 + noise
    writer.add_scalar('noisy_parabola', y, x)
    time.sleep(0.1)
writer.close()

The tensorboard plot will be updated in real time. The final output will be something similar to this:

tensorboard