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出现raise NotImplementedError报错

news 2025/8/4 1:41:49

在学习《动手学深度学习》时，实现下面代码时，报出raise NotImplementedError错误。

import collections
import torch
from d2l import torch as d2l
import math
from torch import nnclass Seq2SeqEncoder(d2l.Encoder):def __init__(self,vocab_size,embed_size,num_hiddens,num_layers,dropout=0,**kwargs):super(Seq2SeqEncoder,self).__init__(**kwargs)self.embedding = nn.Embedding(vocab_size,embed_size)self.rnn = nn.GRU(embed_size,num_hiddens,num_layers,dropout=dropout)def forward(self, X, *args):X = self.embedding(X)X = X.permute(1,0,2)output,state = self.rnn(X)return output,stateencoder = Seq2SeqEncoder(10,8,16,2)
encoder.eval()
X = torch.zeros((4,7),dtype=torch.long)
output,state = encoder(X)
print(output.shape)class Seq2SeqDecoder(d2l.Decoder):def __init__(self,vocab_size,embed_size,num_hiddens,num_layers,dropout=0,**kwargs):super(Seq2SeqDecoder,self).__init__(**kwargs)self.embedding = nn.Embedding(vocab_size,embed_size)self.rnn = nn.GRU(embed_size+num_hiddens,num_hiddens,num_layers,dropout=dropout)self.dense = nn.Linear(num_hiddens,vocab_size)def init_state(self, enc_outputs, *args):return enc_outputs[1]def farward(self,X,state):X = self.embedding(X).permute(1,0,2)context = state[-1].repeat(X.shape[0],1,1)X_and_context = torch.cat((X,context),2)output,state = self.rnn(X_and_context,state)output = self.dense(output).permute(1,0,2)return output,statedecoder = Seq2SeqDecoder(10,8,16,2)
print(decoder.eval())
state = decoder.init_state(encoder(X))
output,state = decoder(X,state)
print(output.shape)