TensorBoard

Using VESSL's Python SDK, you can view and interact with metrics and media logged to TensorBoard directly on VESSL. We currently support scalars, images, and audio.

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VESSL supports TensorBoard with TensorFlow, PyTorch (TensorBoard > 1.14), and TensorBoardX.

You can integrate TensorBoard by simply adding vessl.init(tensorboard=True)to your code.

Note that this should be called before creating the file writer. This is because VESSL auto-detects the TensorBoard logdir upon writer creation but cannot do so if the writer has already been created.

TensorFlow

import tensorflow as tf
import vessl

vessl.init(tensorboard=True) # Must be called before tf.summary.create_file_writer

w = tf.summary.create_file_writer("./logdir")
...

PyTorch

from torch.utils.tensorboard import SummaryWriter
import vessl

vessl.init(tensorboard=True) # Must be called before SummaryWriter

writer = SummaryWriter("newdir")
...

TensorBoardX

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