Skip to main content

Simple integration of keras-tuner (hyperparameter tuning) and tensorboard dashboard (interactive visualization).

Project description

Keras-tuner Tensorboard logger

PyPI version

keras-tuner logger for streaming search report to Tensorboard plugins Hparams, beautiful interactive visualization tool.


  • Python 3.6+
  • keras-tuner 1.0.0+
  • Tensorboard 2.1+


$ pip install kerastuner-tensorboard-logger


here is simple (and incomplete) code.

See details about how to use keras-tuner here.

Add only one argument in tuner class and search it, then you can go to see search report in Tensorboard.

Optionally, you can call setup_tb to be more accurate TensorBoard visualization. It convert keras-tuner hyperparameter information and do Tensorboard experimental setup.

# import this
from kerastuner_tensorboard_logger import (
    setup_tb  # Optional

tuner = Hyperband(
        metrics=["val_acc"], logdir="logs/hparams"
    ),  # add only this argument

setup_tb(tuner)  # (Optional) For more accurate visualization., y, epochs=5, validation_data=(val_x, val_y))


$ tensorboard --logdir ./logs/hparams

Go to

You will see the interactive visualization (provided by Tensorboard).

Table View

Parallel Coordinates View

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kerastuner-tensorboard-logger-0.2.3.tar.gz (4.9 kB view hashes)

Uploaded source

Built Distribution

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page