Tensor's shape is not compatible with supplied shape, Error in Keras Tuner

I am using Keras tuner. For the simple following code:

import keras_tuner as kt
from tensorflow.keras.regularizers import l1, l2
from tensorflow.keras.models import Sequential

# x: 100 x 20
# y: 1 x 100

tuner = kt.Hyperband(
            self.build_auto_encoder_model,
            objective='val_loss',
            max_epochs=30,
            hyperband_iterations=20)

tuner.search(x[0:80], y[0:80], epochs=30, validation_data=(x[80:], y[80:]))
best_model = tuner.get_best_models(1)[0]

def build_auto_encoder_model(hp):
    model = Sequential()
    regulizer_rate = hp.Choice("regulizer_rate", [1e-1, 1e-2, 1e-3, 1e-4, 1e-5])

    model.add(Dense(18, input_dim=20, activation='relu', kernel_regularizer=l1(regulizer_rate)))
    model.add(Dense(12, activation='relu', kernel_regularizer=l1(regulizer_rate)))
    model.add(Dense(10, activation='relu', kernel_regularizer=l1(regulizer_rate)))

    model.compile(optimizer=Adam(1e-2), loss='mse')

I have already tried for the different number of Dense layers, I am getting the following error:

Tensor's shape (20, 18) is not compatible with supplied shape (20, 15)

However, when totally, created a new project, it works. What was the reason?

Solution

The reason is because of some previous errors in the function code, an object has been created and loaded for any future trials, due to overwrite variable of the turner is False by default. Also, in the last version of the created object, the first layer was 15 that has been changed to 18 in your example.

A simple solution to resolve the problem (instead of creating a new project) is to make the overwrite variable to True to prevent reloading previously incompatible object with new changes, like the following:

# ...
tuner = kt.Hyperband(
            self.build_auto_encoder_model,
            objective='val_loss',
            max_epochs=30,
            hyperband_iterations=20,
            overwrite = True) # here
# ...