Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________

self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>

    def test_make_tensor(self):  # type: () -> None
    

Current pytorch implementation ignores the argument split_f in the function train_batch_ch13 as shown below.

def train_batch_ch13(net, X, y, loss, trainer, devices):
    if isinstance(X, list):
        # Required for BERT Fine-tuning (to be covered later)
        X = [x.to(devices[0]) for x in X]
    else:
        X = X.to(devices[0])
...

Todo: Define the argument `

Adding types on the public API surface would allow us to do some runtime type checking later on and would allow user's IDE to have more info for static analysis.

The functions/signatures to type are the ones listed here https://github.com/keras-team/autokeras/blob/master/autokeras/__init__.py

For the context, see #856 where I add some type information on a ImageClassifier.

This issue can