Explain the necessary process of pytorch training model

The necessary process of PyTorch training model includes data preparation, building model, setting hyperparameters, training model and evaluating model. The data preparation stage can involve data cleaning, data enhancement, etc.; the model building stage can involve selecting an optimizer, loss function, etc.; the hyperparameter setting stage can involve learning rate, gradient clipping, etc.; the training model stage can involve model training, model verification, etc.; finally, the evaluation model stage can involve model reasoning, model adversarial testing, etc.