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4.4 Saving and Loading Models in PyTorch

In PyTorch, models are instantiated as objects of the torch.nn.Module class, which encapsulates all the layers, parameters, and computational logic of the neural network. This object-oriented approach allows for modular design and easy manipulation of model architectures. Upon completion of the training process, it's crucial to persist the model's state to disk for future use, whether for inference or continued training. PyTorch offers a versatile approach to model serialization, accommodating different use cases and deployment scenarios.

The framework provides two primary methods for saving models:

1. Saving the entire model: This approach preserves both the model's architecture and its learned parameters. ...