be sure to call model.eval() method before inferencing to set the dropout and batch normalization layers to evaluation mode. Failing to do this will yield inconsistent inference results.

您的第一个问题是关于 PyTorch 模型推理时需要调用 model.eval() 方法的说明。这是非常重要的步骤，因为它可以确保在推理时，模型中的 dropout 和 batch normalization 层处于评估模式，从而避免因此产生的不一致的推理结果。如果您在推理时没有调用 model.eval() 方法，那么您得到的推理结果可能会与您预期的不一致。因此，在进行模型推理之前，一定要确保调用 model.eval() 方法。

相关问题

model.eval()

The `model.eval()` method is used to set the model in evaluation mode. In this mode, the model is used for inference or prediction, rather than training.

When the model is in evaluation mode, certain layers or functions may behave differently than during training, such as dropout layers being turned off or batch normalization layers using precomputed statistics instead of computing them on the fly.

It is important to set the model to evaluation mode before using it for prediction, as using the model in training mode can result in incorrect predictions or unexpected behavior.