import torch
import accelerate

def get_op_by_name(module, op_name):
    # get the op by its name relative to the module
    for name, m in module.named_modules():
        if name == op_name:
            return m
    raise ValueError(f"Cannot find op {op_name} in module {module}")


def set_op_by_name(layer, name, new_module):
    levels = name.split(".")
    if len(levels) > 1:
        mod_ = layer
        for l_idx in range(len(levels) - 1):
            if levels[l_idx].isdigit():
                mod_ = mod_[int(levels[l_idx])]
            else:
                mod_ = getattr(mod_, levels[l_idx])
        setattr(mod_, levels[-1], new_module)
    else:
        setattr(layer, name, new_module)


def get_op_name(module, op):
    # get the name of the op relative to the module
    for name, m in module.named_modules():
        if m is op:
            return name
    raise ValueError(f"Cannot find op {op} in module {module}")


def append_str_prefix(x, prefix):
    if isinstance(x, str):
        return prefix + x
    elif isinstance(x, tuple):
        return tuple([append_str_prefix(y, prefix) for y in x])
    elif isinstance(x, list):
        return [append_str_prefix(y, prefix) for y in x]
    else:
        return x



def get_module_by_name_suffix(model, module_name: str):
    for name, module in model.named_modules():
        if name.endswith(module_name):
            return module


def simple_dispatch_model(model, device_map):
    from accelerate.hooks import add_hook_to_module, AlignDevicesHook

    if "" in device_map:
        d = device_map[""]
        model = model.to(torch.device(d))
        model.hf_device_map = device_map
        return model

    tied_params = accelerate.utils.modeling.find_tied_parameters(model)
    if set(device_map.values()) == {"cpu"} or set(device_map.values()) == {
        "cpu",
        "disk",
    }:
        main_device = "cpu"
    else:
        main_device = [d for d in device_map.values() if d not in ["cpu", "disk"]][0]

    cpu_offload_group = [(n, d) for n, d in device_map.items() if d == "cpu"]
    prev_hook = None
    for idx, (n, d) in enumerate(cpu_offload_group):
        m = get_module_by_name_suffix(model, n)
        _, prev_hook = accelerate.cpu_offload_with_hook(
            m, execution_device=main_device, prev_module_hook=prev_hook
        )
    # set first cpu offload module's prev_module_hook to the last cpu offload module's hook
    if len(cpu_offload_group) > 1:
        get_module_by_name_suffix(
            model, cpu_offload_group[0][0]
        )._hf_hook.prev_module_hook = prev_hook

    for n, d in device_map.items():
        m = get_module_by_name_suffix(model, n)
        if d != "cpu":
            d = torch.device(d)
            hook = AlignDevicesHook(d, io_same_device=True, place_submodules=True)
            add_hook_to_module(m, hook)
    accelerate.utils.modeling.retie_parameters(model, tied_params)
    model.hf_device_map = device_map

    return model