import glob
import os

from lightx2v.models.networks.wan.infer.audio.post_wan_audio_infer import WanAudioPostInfer
from lightx2v.models.networks.wan.infer.audio.pre_wan_audio_infer import WanAudioPreInfer
from lightx2v.models.networks.wan.model import WanModel
from lightx2v.models.networks.wan.weights.post_weights import WanPostWeights
from lightx2v.models.networks.wan.weights.pre_weights import WanPreWeights
from lightx2v.models.networks.wan.weights.transformer_weights import (
    WanTransformerWeights,
)


class WanAudioModel(WanModel):
    pre_weight_class = WanPreWeights
    post_weight_class = WanPostWeights
    transformer_weight_class = WanTransformerWeights

    def __init__(self, model_path, config, device, seq_p_group=None):
        super().__init__(model_path, config, device, seq_p_group)

    def _init_infer_class(self):
        super()._init_infer_class()
        self.pre_infer_class = WanAudioPreInfer
        self.post_infer_class = WanAudioPostInfer


class Wan22MoeAudioModel(WanAudioModel):
    def _load_ckpt(self, unified_dtype, sensitive_layer):
        safetensors_files = glob.glob(os.path.join(self.model_path, "*.safetensors"))
        weight_dict = {}
        for file_path in safetensors_files:
            file_weights = self._load_safetensor_to_dict(file_path, unified_dtype, sensitive_layer)
            weight_dict.update(file_weights)
        return weight_dict