I am running the following error when I try to optimize a LSTM using keras tuner in Python: AttributeError: module ‘keras.src.activations’ has no attribute ‘get’.

I am using the following versions: | Python version: 3.11.7 | Keras version: 3.4.1 | TensorFlow version: 2.16.2 | Keras Tuner version: 1.0.5

#LOADING REQUIRED PACKAGES
import pandas as pd
import math
import keras
import numpy as np
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.models import save_model
from tensorflow.keras.models import model_from_json
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import LSTM
from tensorflow.keras.layers import Dropout
from kerastuner.tuners import RandomSearch
from kerastuner.engine.hyperparameters import HyperParameters

#GENERATING SAMPLE DATA
# Creating x_train_data with 300 observations and 10 columns
x_train_data = pd.DataFrame(np.random.rand(300, 10))
# Creating y_train_data with 300 observations and 1 column
y_train_data = pd.DataFrame(np.random.rand(300, 1))
# Creating x_test_data with 10 observations and 10 columns
x_test_data = pd.DataFrame(np.random.rand(10, 10))
# Creating y_test_data with 10 observations and 1 column
y_test_data = pd.DataFrame(np.random.rand(10, 1))

#RESHAPING DATA
nrow_xtrain, ncol_xtrain = x_train_data.shape
x_train_data_lstm = x_train_data.reshape(1,nrow_xtrain, ncol_xtrain)
nrow_ytrain= y_train_data.shape[0]
y_train_data_lstm = y_train_data.reshape(1,nrow_ytrain,1)
nrow_ytest= y_test.shape[0]
y_test_data_lstm = y_test.reshape(1,nrow_ytest,1)
nrow_xtest, ncol_xtest = X_test.shape
x_test_data_lstm = X_test.reshape(1,nrow_xtest, ncol_xtest)

#BUILDING AND ESTIMATING MODEL
    def build_model(hp):
        model = Sequential()
        model.add(LSTM(hp.Int('input_unit',min_value=1,max_value=512,step=32),return_sequences=True, input_shape=(x_train_data_lstm.shape[1],x_train_data_lstm.shape[2])))
        for i in range(hp.Int('n_layers', 1, 4)):
            model.add(LSTM(hp.Int(f'lstm_{i}_units',min_value=1,max_value=512,step=32),return_sequences=True))
        model.add(LSTM(hp.Int('layer_2_neurons',min_value=1,max_value=512,step=32)))
        model.add(Dropout(hp.Float('Dropout_rate',min_value=0,max_value=0.5,step=0.1)))
        model.add(Dense(10, activation=hp.Choice('dense_activation',values=['relu', 'sigmoid',"linear"],default='relu')))
        model.compile(loss='mean_squared_error', optimizer='adam',metrics = ['mse'])
        return model
    
    tuner= RandomSearch(
            build_model,
            objective='mse',
            max_trials=2,
            executions_per_trial=1
            )
    
    tuner.search(
            x=X_train,
            y=Y_train,
            epochs=20,
            batch_size=128,
            validation_data=(x_test_data_lstm,y_test_data_lstm),
    )

Full Error Traceback:

C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskerassrclayersrnnrnn.py:204: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.
  super().__init__(**kwargs)

Traceback (most recent call last):

  Cell In[82], line 12
    tuner= RandomSearch(

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskeras_tunersrctunersrandomsearch.py:174 in __init__
    super().__init__(oracle, hypermodel, **kwargs)

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskeras_tunersrcenginetuner.py:122 in __init__
    super().__init__(

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskeras_tunersrcenginebase_tuner.py:132 in __init__
    self._populate_initial_space()

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskeras_tunersrcenginebase_tuner.py:192 in _populate_initial_space
    self._activate_all_conditions()

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskeras_tunersrcenginebase_tuner.py:149 in _activate_all_conditions
    self.hypermodel.build(hp)

  Cell In[82], line 8 in build_model
    model.add(Dense(10, activation=hp.Choice('dense_activation',values=['relu', 'sigmoid',"linear"],default='relu')))

  File C:WorkspacePython_RuntimeEnvsbbkLibsite-packageskerassrclayerscoredense.py:89 in __init__
    self.activation = activations.get(activation)

AttributeError: module 'keras.src.activations' has no attribute 'get'

UPDATE

After a restart of the kernel, suddenly the code worked and the error did not pop up anymore. However, in order to understand the error, I will still leave the question online.