May I use this with sequential(keras.utils.Sequence) data?

[asapsmc]

I'm using 3rd party working code that fits a TCN-based model with

model.fit(train_seq, steps_per_epoch=len(train_seq), epochs=20)

where train_seq is a keras.utils.Sequence implemented by the following code:

def cnn_pad(data, pad_frames):
    """Pad the data by repeating the first and last frame N times."""
    pad_start = np.repeat(data[:1], pad_frames, axis=0)
    pad_stop = np.repeat(data[-1:], pad_frames, axis=0)
    return np.concatenate((pad_start, data, pad_stop))
    
class DataSequence(Sequence):
    def __init__(self, x, y, fps=FPS, pad_frames=None):
        self.x = x
        y_proc = np.zeros(np.shape(x)[1])
        np.add.at(y_proc, y[0]*FPS, 1)
        self.y = [y_proc]
        self.pad_frames = pad_frames

    def __len__(self):
        return len(self.x)

    def __getitem__(self, idx):
        x = np.array(cnn_pad(self.x[idx], self.pad_frames))[np.newaxis, ..., np.newaxis]
        y = self.y[idx][np.newaxis, ..., np.newaxis]
        return x, y

x = [np.random.randn(1949, 81)]  # to emulate audio
y = [np.asarray([1, 2, 3, 4, 5])]  # to emulate annotations
train_seq = DataSequence(x[:1], y[:1], pad_frames=2)

How may I use LRFinder for this type of data? Ie, is it possible to "retrieve" valid x and y from the Sequence? To reproduce this issue (almost in entirety, with the exception of the keras h5 model), here is some dummy code: