When using Keras Tuner, there doesn't seem to be a way to allow the skipping of a problematic combination of hyperparams. For example, the number of filters in
I trained my network several times and I already got some results. Then I found out about the Keras tuner and wanted to find the best hyperparameters with it. b
My goal is to tune over possible network architectures that meet the following criteria: Layer 1 can have any number of hidden units from this list: [32, 64, 12
I'm trying to reload or access the Keras-Tuner Trials after the Tuner's search has completed for inspecting the results. I'm not able to find any documentation
I am trying out Keras (2.8.0) autotuner for a regression problem. Here is my code: import pandas as pd from tensorflow import keras from keras import layers, lo