根据这个链接，我尝试使用自己的数据进行情感分析。但是我遇到了以下错误：

---------------------------------------------------------------------------RuntimeError                              Traceback (most recent call last)<timed exec> in <module><ipython-input-41-5f2f35b7976e> in train_epoch(model, data_loader, optimizer, device, scheduler, n_examples)      7       8     for d in data_loader:----> 9         input_ids = d["input_ids"].reshape(4,64).to(device)     10         attention_mask = d["attention_mask"].to(device)     11         targets = d["targets"].to(device)RuntimeError: shape '[4, 64]' is invalid for input of size 64

当我尝试运行以下代码时

history = defaultdict(list)best_accuracy = 0for epoch in range(EPOCHS):    print(f'Epoch {epoch + 1}/{EPOCHS}')    print('-' * 10)    train_acc, train_loss = train_epoch(        model,        train_data_loader,             optimizer,         device,         scheduler,         len(df_train)    )    print(f'Train loss {train_loss} Train accuracy {train_acc}')    val_acc, val_loss = eval_model(        model,        val_data_loader,         device,         len(df_val)    )    print(f'Val loss {val_loss} Val accuracy {val_acc}')    print()    history['train_acc'].append(train_acc)    history['train_loss'].append(train_loss)    history['val_acc'].append(val_acc)    history['val_loss'].append(val_loss)

我知道这个错误与我的数据形状有关，但我不知道如何找到正确的reshape参数来使其正常工作。

回答：

你示例中的形状[4,64]实际上是[批量大小, 最大序列长度]

所以你可以考虑用你的值来替换它们…