Simple integration of keras-tuner (hyperparameter tuning) and tensorboard dashboard (interactive visualization).
Project description
Keras-tuner Tensorboard logger
keras-tuner logger for streaming search report to Tensorboard plugins Hparams, beautiful interactive visualization tool.
Requirements
- Python 3.6+
- keras-tuner 1.0.0+
- Tensorboard 2.1+
Example
simple and incomplete code is introduced.
See details about how to use keras-tuner in here.
Add only one argument in tuner class and search it, then you can go to see search report in Tensorboard.
# import this
from kerastuner_tensorboard_logger import TensorBoardLogger
tuner = Hyperband(
build_model,
objective="val_acc",
max_epochs=5,
directory="logs/tuner",
project_name="tf_test",
logger=TensorBoardLogger(
metrics=["val_acc"], logdir="logs/hparams"
), # add only this argument
)
tuner.search(x, y, epochs=5, validation_data=(val_x, val_y))
Tensorboard
$ tensorboard --logdir ./logs/hparams
Go to http://127.0.0.1:6006.
You will see the interactive visualization (provided by Tensorboard).
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