def pad_batch_equal(batch, padding_values: AxesParams=0, ratio: AxesParams=0.5):
    '\n    Pad each element of ``batch`` to obtain a correctly shaped array.\n\n    References\n    ----------\n    `pad_to_shape`\n    '
    max_shapes = np.max(lmap(np.shape, batch), axis=0)
    if (max_shapes.size != 0):
        batch = [pad_to_shape(x, max_shapes, padding_values=padding_values, ratio=ratio) for x in batch]
    return np.array(batch)
Pad each element of ``batch`` to obtain a correctly shaped array.

References
----------
`pad_to_shape`
def pad_batch_equal(batch, padding_values: AxesParams=0, ratio: AxesParams=0.5):
    '\n    Pad each element of ``batch`` to obtain a correctly shaped array.\n\n    References\n    ----------\n    `pad_to_shape`\n    '
    max_shapes = np.max(lmap(np.shape, batch), axis=0)
    if (max_shapes.size != 0):
        batch = [pad_to_shape(x, max_shapes, padding_values=padding_values, ratio=ratio) for x in batch]
    return np.array(batch)