因果注意力（or 掩码注意力）代码实现

import torch
import torch.nn as nn
import math
import numpy as np


class CausalSelfAttention(nn.Module):
    def __init__(self, hidden_dim, n_heads, dropout=0.0):
        super().__init__()
        self.hidden_dim = hidden_dim
        self.n_heads = n_heads
        self.head_dim = hidden_dim // n_heads
        assert hidden_dim % n_heads == 0, "hidden_dim 必须能被 n_heads 整除"
        self.query = nn.Linear(hidden_dim, hidden_dim)
        self.key = nn.Linear(hidden_dim, hidden_dim)
        self.value = nn.Linear(hidden_dim, hidden_dim)
        self.output = nn.Linear(hidden_dim, hidden_dim)
        self.dropout = nn.Dropout(p=dropout)
    

    def forward(self, x, mask=None):
        q = self.query(x)
        k = self.key(x)
        v = self.value(x)
        return self.get_attention_scores(q, k, v, mask=mask)

    def get_attention_scores(self, q, k, v, mask=None):