matlab实现自注意力机制代码

以下是Matlab实现自注意力机制的代码：

function [output] = self_attention(input, num_heads)
% input: 输入的数据，大小为 [seq_len, embedding_dim]
% num_heads: 多头注意力的头数
% output: 输出的结果，大小为 [seq_len, embedding_dim]

seq_len = size(input, 1);
embedding_dim = size(input, 2);

% 计算 Q、K、V
Q = input;
K = input;
V = input;

% 按头数拆分 Q、K、V
Q = reshape(Q, [seq_len, embedding_dim/num_heads, num_heads]);
Q = permute(Q, [3, 1, 2]);
K = reshape(K, [seq_len, embedding_dim/num_heads, num_heads]);
K = permute(K, [3, 1, 2]);
V = reshape(V, [seq_len, embedding_dim/num_heads, num_heads]);
V = permute(V, [3, 1, 2]);

% 计算多头注意力
attention_scores = zeros(num_heads, seq_len, seq_len);
for i = 1:num_heads
    attention_scores(i, :, :) = Q(i, :, :) * K(i, :, :)' / sqrt(embedding_dim/num_heads);
end
attention_scores = softmax(attention_scores, 3);

% 计算输出
output = zeros(seq_len, embedding_dim);
for i = 1:num_heads
    output = output + attention_scores(i, :, :) * V(i, :, :);
end
output = reshape(output, [seq_len, embedding_dim]);
end

其中，`softmax`函数为softmax操作的实现，可以自行编写或调用Matlab内置的softmax函数。