PyTorch Forward Function Implementation: A Detailed Explanation

This is a forward function for a model.

The input 'x' is multiplied by weights 'w1' and added to a bias 'w0'. The result is stored in 'lr_out'.

The 'crossLayer' function is then applied to 'x', which returns a tensor of the same shape as 'x'. This output is added to 'lr_out', and the result is passed through a sigmoid function to obtain the final logits.

The logits represent the model's prediction for the given input 'x'.