def check_objects_being_equally_in_main_init():
    """
    Check if a (TensorFlow or Flax) object is in the main __init__ iif its counterpart in PyTorch is.
    """
    attrs = dir(transformers)

    failures = []
    for attr in attrs:
        obj = getattr(transformers, attr)
        if not hasattr(obj, "__module__") or "models.deprecated" in obj.__module__:
            continue

        module_path = obj.__module__
        module_name = module_path.split(".")[-1]
        module_dir = ".".join(module_path.split(".")[:-1])
        if (
            module_name.startswith("modeling_")
            and not module_name.startswith("modeling_tf_")
            and not module_name.startswith("modeling_flax_")
        ):
            parent_module = sys.modules[module_dir]

            frameworks = []
            if is_tf_available():
                frameworks.append("TF")
            if is_flax_available():
                frameworks.append("Flax")

            for framework in frameworks:
                other_module_path = module_path.replace("modeling_", f"modeling_{framework.lower()}_")
                if os.path.isfile("src/" + other_module_path.replace(".", "/") + ".py"):
                    other_module_name = module_name.replace("modeling_", f"modeling_{framework.lower()}_")
                    other_module = getattr(parent_module, other_module_name)
                    if hasattr(other_module, f"{framework}{attr}"):
                        if not hasattr(transformers, f"{framework}{attr}"):
                            if f"{framework}{attr}" not in OBJECT_TO_SKIP_IN_MAIN_INIT_CHECK:
                                failures.append(f"{framework}{attr}")
                    if hasattr(other_module, f"{framework}_{attr}"):
                        if not hasattr(transformers, f"{framework}_{attr}"):
                            if f"{framework}_{attr}" not in OBJECT_TO_SKIP_IN_MAIN_INIT_CHECK:
                                failures.append(f"{framework}_{attr}")
    if len(failures) > 0:
        raise Exception(f"There were {len(failures)} failures:\n" + "\n".join(failures))

    Check if a (TensorFlow or Flax) object is in the main __init__ iif its counterpart in PyTorch is.
    
dpkd/transformers/utils/check_repo.py