transformer代码c

transformer的代码大致如下所示：

class Transformer(nn.Module):
    def __init__(self, d_model=512, nhead=8, num_encoder_layers=6, num_decoder_layers=6, dim_feedforward=2048, dropout=0.1, activation="relu", normalize_before=False, return_intermediate_dec=False):
        super().__init__()
        
        # encode
        encoder_layer = TransformerEncoderLayer(d_model, nhead, dim_feedforward, dropout, activation, normalize_before)
        encoder_norm = nn.LayerNorm(d_model) if normalize_before else None
        self.encoder = TransformerEncoder(encoder_layer, num_encoder_layers, encoder_norm)
        
        # decode
        decoder_layer = TransformerDecoderLayer(d_model, nhead, dim_feedforward, dropout, activation, normalize_before)
        decoder_norm = nn.LayerNorm(d_model)
        self.decoder = TransformerDecoder(decoder_layer, num_decoder_layers, decoder_norm, return_intermediate=return_intermediate_dec)

以上是transformer模型的主要代码结构。它由一个encoder和一个decoder组成，其中encoder由多个encoder_layer堆叠而成，decoder由多个decoder_layer堆叠而成。每个encoder_layer包含self-attention和feed forward两个层，而每个decoder_layer包含mask self-attention、encoder-decoder attention和feed forward三个层。这些层的组合形成了transformer模型的总体结构。

你没有提供完整的代码，如果你需要更详细的解释，请提供完整的代码。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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