# Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.
import gc
from functools import partial

import torch
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.distributed.fsdp import MixedPrecision, ShardingStrategy
from torch.distributed.fsdp.wrap import lambda_auto_wrap_policy
from torch.distributed.utils import _free_storage


def shard_model(
    model,
    device_id,
    param_dtype=torch.bfloat16,
    reduce_dtype=torch.float32,
    buffer_dtype=torch.float32,
    process_group=None,
    sharding_strategy=ShardingStrategy.FULL_SHARD,
    sync_module_states=True,
    use_lora=False
):
    model = FSDP(
        module=model,
        process_group=process_group,
        sharding_strategy=sharding_strategy,
        auto_wrap_policy=partial(
            lambda_auto_wrap_policy, lambda_fn=lambda m: m in model.blocks),
        mixed_precision=MixedPrecision(
            param_dtype=param_dtype,
            reduce_dtype=reduce_dtype,
            buffer_dtype=buffer_dtype),
        device_id=device_id,
        sync_module_states=sync_module_states,
        use_orig_params=True if use_lora else False)
    return model


def free_model(model):
    for m in model.modules():
        if isinstance(m, FSDP):
            _free_storage(m._handle.flat_param.data)
    del model
    gc.collect()
    torch.cuda.empty_cache()
