An example of fine-tuning an auto-encoder for classification. The example demonstrates how arbitrary modules can easily be extended to fix the weights and/or biases after loading a model. Additionally it shows how weights and biases can manually be copied between models with a different structure.
Minimal example of defining a custom Torch module on a custom data structure. This example defines a simple data structure wrapping two Torch tensors and defines a linear
nn.Module to operate on this data structure. While the backward pass is not implemented, the example illustrates how Torch can be extended for deep learning on custom data structures.