transformer中selfattention简单实现

AI大模型学习

在当前技术环境下，AI大模型学习不仅要求研究者具备深厚的数学基础和编程能力，还需要对特定领域的业务场景有深入的了解。通过不断优化模型结构和算法，AI大模型学习能够不断提升模型的准确性和效率，为人类生活和工作带来更多便利。

import torch
import torch.nn.functional as F


class SelfAttention(torch.nn.Module):
    def __init__(self, embed_size, heads):
        super(SelfAttention, self).__init__()
        self.embed_size = embed_size
        self.heads = heads
        self.head_dim = embed_size // heads

        assert (
                self.head_dim * heads == embed_size
        ), "Embedding size needs to be divisible by heads"

        self.values = torch.nn.Linear(self.head_dim, self.head_dim, bias=False)
        self.keys = torch.nn.Linear(self.head_dim, self.head_dim, bias=False)
        self.queries = torch.nn.Linear(self.head_dim, self.head_dim, bias=False)
        self.fc_out = torch.nn.Linear(heads * self.head_di