transformer代码实现pytorch

PyTorch是一个开源深度学习框架，可以使用它来实现Transformer模型。以下是一个简单的Transformer代码实现：

import torch
import torch.nn as nn

class Transformer(nn.Module):
    def __init__(self, d_model, nhead, num_layers):
        super(Transformer, self).__init__()
        self.encoder = nn.TransformerEncoder(nn.TransformerEncoderLayer(d_model, nhead), num_layers)
        self.decoder = nn.TransformerDecoder(nn.TransformerDecoderLayer(d_model, nhead), num_layers)
        self.src_mask = None
        self.tgt_mask = None

    def forward(self, src, tgt):
        if self.src_mask is None or self.src_mask.size(0) != len(src):
            device = src.device
            mask = self._generate_square_subsequent_mask(len(src)).to(device)
            self.src_mask = mask

        if self.tgt_mask is None or self.tgt_mask.size(0) != len(tgt):
            device = tgt.device
            mask = self._generate_square_subsequent_mask(len(tgt)).to(device)
            self.tgt_mask = mask

        src = self.encoder(src, self.src_mask)
        tgt = self.decoder(tgt, src, self.tgt_mask)
        return tgt

    def _generate_square_subsequent_mask(self, sz):
        mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1)
        mask = mask.float().masked_fill(mask == 0, float('-inf')).masked_fill(mask == 1, float(0.0))
        return mask

这是一个简单的Transformer代码实现。其中d_model表示模型的维度，nhead表示多头注意力中的头数，num_layers表示Transformer中的层数。