I’m looking at the Learning PyTorch with Examples page (see example code below).
I’m a little confused about where to go from here in terms of testing my model now. It is unclear to me how I apply my new model/linear relationship to “forecasting” to hindcasting on my data.
I also am not sure how to extract the relevant weights for each input layer.
Any help would be appreciated. Thanks!
class TwoLayerNet(torch.nn.Module): def __init__(self, D_in, H, D_out): """ In the constructor we instantiate two nn.Linear modules and assign them as member variables. """ super(TwoLayerNet, self).__init__() self.linear1 = torch.nn.Linear(D_in, H) self.linear2 = torch.nn.Linear(H, D_out) def forward(self, x): """ In the forward function we accept a Tensor of input data and we must return a Tensor of output data. We can use Modules defined in the constructor as well as arbitrary operators on Tensors. """ h_relu = self.linear1(x).clamp(min=0) y_pred = self.linear2(h_relu) return y_pred