Bugs using keras.src.utils.split_dataset on tf.data.Dataset loaded using tf.data.experimental.make_csv_dataset on versions v3.4.0+

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Bug description:

We've noticed two bugs that appear when using split_dataset on tf datasets loaded using tf.data.experimental.make_csv_dataset for keras versions 3.4.0 onward. One of two things happens on attempting to call split_dataset on a dataset loaded using make_csv_dataset, either the split_dataset call hangs indefinitely or the output train and test data have their column names shuffled.

Tested keras versions: 3.5.0, 3.6.0. Tested tensorflow versions: 2.18.

Steps to reproduce:

`from keras.src.utils import split_dataset
import tensorflow as tf
import pandas as pd

data_dict = {
'a': [1.] * 10,
'b': [20.] * 10,
'c': [300.] * 10,
'd': [4000.] * 10
}

df = pd.DataFrame(data_dict)

valid_dataset = tf.data.Dataset.from_tensor_slices(dict(df))
print("Dataframe dataset sample: ", [e for e in valid_dataset.take(1)])
train, test = split_dataset(valid_dataset, left_size=0.5, seed=1)
print("Train dataset sample: ", [e for e in train.take(1)])

df.to_csv('bug_report_test_data.csv', index=False)

invalid_dataset = tf.data.experimental.make_csv_dataset('bug_report_test_data.csv', batch_size=1)
print("CSV dataset sample: ", [e for e in invalid_dataset.take(1)])
train, test = split_dataset(invalid_dataset, left_size=0.5, seed=1)
print("Train dataset sample: ", [e for e in train.take(1)])

`
In the first case, split_dataset works as expected. In the latter case, the split_dataset call will either hang indefinitely or the column names will get reassigned like ['d': [1], 'b':[300], 'c':[4000], 'a':[20]]

Reverting the function _restore_dataset_from_list in keras.src.utils.dataset_utils back to version 3.3.3 resolves the issue