微信公众号搜"智元新知"关注
微信扫一扫可直接关注哦!

ValueError:太多值无法用 RNN 分类器解包预期为 2

如何解决ValueError:太多值无法用 RNN 分类器解包预期为 2

您好,我在尝试使用 pytorch 训练 RNN 分类器时遇到此错误。 我希望有人能帮我解决它或解释原因。

train_loader2=embeddings_train

train_loader2=torch.from_numpy(embeddings_train)
train_loader2 = DataLoader(dataset=train_dataset,batch_size=batch_size,shuffle=True)
y_train=np.array(y_train)
targets2= torch.from_numpy(y_train)

# Initialize network
model = BRNN(input_size,hidden_size,num_layers,num_classes).to(device)

# Loss and optimizer
criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(model.parameters(),lr=learning_rate)

# Train Network
for epoch in range(num_epochs):
    for i,(dataf,targets2) in enumerate(train_loader2):
        # Get data to cuda if possible
        dataf = dataf.to(device=device).squeeze(1)
        targets2 = targets2.to(device=device)

        # forward
        scores = model(dataf)
        loss = criterion(scores,targets2)

        # backward
        optimizer.zero_grad()
        loss.backward()

        # gradient descent or adam step
        optimizer.step()

这是它发生的错误

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-42-d435f4563f2e> in <module>
     15 # Train Network
     16 for epoch in range(num_epochs):
---> 17     for i,targets2) in enumerate(train_loader2):
     18         # Get data to cuda if possible
     19         dataf = dataf.to(device=device).squeeze(1)

ValueError: too many values to unpack (expected 2)

版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 dio@foxmail.com 举报,一经查实,本站将立刻删除。