# 示例：Tensor Fusion Network的核心计算单元
class TensorFusion(nn.Module):
    def __init__(self, input_dims, hidden_dim):
        super().__init__()
        self.fusion_weights = nn.Parameter(torch.rand(sum(input_dims)))

    def forward(self, text, audio, video):
        # 动态权重分配
        weights = F.softmax(self.fusion_weights, dim=0)
        # 张量融合计算
        fused = torch.einsum('b d, b t -> b t d', weights, 
                            torch.cat([text, audio, video], dim=1))
        return fused

# 文化敏感度自适应模块
class CultureAdapter(nn.Module):
    def __init__(self, culture_profiles):
        self.profiles = culture_profiles

    def adapt(self, emotion_vector, context):
        # 根据上下文提取文化特征
        cultural_context = self._extract_cultural_context(context)
        # 动态调整情感映射
        adjusted = torch.matmul(emotion_vector, 
                               self.profiles[cultural_context])
        return adjusted

# 混合符号推理与神经网络的框架
class NeuroSymbolicSystem:
    def __init__(self, neural_model, knowledge_base):
        self.neural = neural_model
        self.knowledge = knowledge_base

    def reason(self, input_data):
        raw_emotion = self.neural.predict(input_data)
        # 符号推理校正
        corrected = self.knowledge.correct(raw_emotion)
        return corrected