def compute_module_persistent_sizes(
    model: nn.Module,
    dtype: Optional[Union[str, torch.device]] = None,
    special_dtypes: Optional[Dict[str, Union[str, torch.device]]] = None,
):
    """
    Compute the size of each submodule of a given model (parameters + persistent buffers).
    """
    if dtype is not None:
        dtype = _get_proper_dtype(dtype)
        dtype_size = dtype_byte_size(dtype)
    if special_dtypes is not None:
        special_dtypes = {key: _get_proper_dtype(dtyp) for key, dtyp in special_dtypes.items()}
        special_dtypes_size = {key: dtype_byte_size(dtyp) for key, dtyp in special_dtypes.items()}
    module_sizes = defaultdict(int)

    module_list = []

    module_list = named_persistent_module_tensors(model, recurse=True)

    for name, tensor in module_list:
        if special_dtypes is not None and name in special_dtypes:
            size = tensor.numel() * special_dtypes_size[name]
        elif dtype is None:
            size = tensor.numel() * dtype_byte_size(tensor.dtype)
        elif str(tensor.dtype).startswith(("torch.uint", "torch.int", "torch.bool")):
            # According to the code in set_module_tensor_to_device, these types won't be converted
            # so use their original size here
            size = tensor.numel() * dtype_byte_size(tensor.dtype)
        else:
            size = tensor.numel() * min(dtype_size, dtype_byte_size(tensor.dtype))
        name_parts = name.split(".")
        for idx in range(len(name_parts) + 1):
            module_sizes[".".join(name_parts[:idx])] += size

    return module_sizes

    Compute the size of each submodule of a given model (parameters + persistent buffers).
    
tests/models/test_modeling_common.py