Bug: StructuredDataClassifier ignores loss parameter

[DF-Damm]

Bug Description

The StructuredDataClassifier trains with default loss and ignores any user input. Even setting the loss to some random string like loss='this is not a loss' does not change the behavior (or result in an error).

Bug Reproduction

import tensorflow as tf
import autokeras as ak

TRAIN_DATA_URL = "https://storage.googleapis.com/tf-datasets/titanic/train.csv"
TEST_DATA_URL = "https://storage.googleapis.com/tf-datasets/titanic/eval.csv"

train_file_path = tf.keras.utils.get_file("train.csv", TRAIN_DATA_URL)
test_file_path = tf.keras.utils.get_file("eval.csv", TEST_DATA_URL)

# Initialize the structured data classifier.
clf = ak.StructuredDataClassifier(
    overwrite=True, max_trials=3, loss='mse'
) 
# Feed the structured data classifier with training data.
clf.fit(
    # The path to the train.csv file.
    train_file_path,
    # The name of the label column.
    "survived",
    epochs=10,
)
# Print loss function used during training
model = clf.export_model()
print('loss function:', model.loss)

Expected Behavior

The model is supposed to be trained using the mean squared error, but it is actually being trained using <keras.losses.BinaryCrossentropy>.

Setup Details

• OS: Windows
• Python: 3
• autokeras: 1.0.20
• keras-tuner: 1.1.3
• scikit-learn: 1.0.2
• numpy: 1.21.5
• pandas: 1.5.1
• tensorflow: 2.9.1

Additional context

Upon examining the code, it appears that the user input is being overwritten at this point.

#1608 raises a similar issue as a feature request.