TensorBoard.dev TensorBoard TensorFlow


TensorBoard.dev has been shut down as of January 1, 2024.
Thank you for being part of the TensorBoard.dev journey.


What can I use instead of TensorBoard.dev?

You can continue to use TensorBoard as a local tool via the open source project, which is unaffected by this shutdown, with the exception of the removal of the `tensorboard dev` subcommand in our command line tool. For a refresher, please see our documentation.

For sharing TensorBoard results, we recommend the TensorBoard integration with Google Colab. TensorBoard log files that are generated or downloaded by code in the Colab notebook can be directly visualized by running TensorBoard within the notebook.

What format is the data export produced by `tensorboard dev export`?

Note: It is no longer possible export data from TensorBoard.dev because it has been shut down. If you previously exported data, see below for documentation of the export format.

The export command produces one subfolder per experiment. Each subfolder contains several newline-delimited JSON files:

  • metadata.json: experiment-level metadata such as title and description
  • scalars.json: full data points for scalars (shown on the Scalars dashboard)
  • tensors.json: data point metadata for tensor-type data (shown on the Histograms, Distributions, Text, and Hparams dashboard)
  • blob_sequences.json: data point metadata for blob-type data (shown on the Graphs dashboard)

The data point values for tensors and blob sequences are written separately as individual files. Tensor values are written to a "tensors" subfolder as Numpy zip files (.npz), and blob values are written to a "blobs" subfolder as binary files (.bin). For the Graphs plugin, the binary file format will be a serialized GraphDef protocol buffer.

There is a Python script available to convert the JSON-based export format described above into event files that can be viewed directly in open source TensorBoard. Download and run via Python to see usage instructions: convert_tbdev_export.py

What if I have a problem not addressed here?

For problems that cannot be addressed by this FAQ, please reach out to tensorboard.dev-support@google.com.