Hi all,
I’m looking at the Learning PyTorch with Examples page (see example code below).
https://pytorch.org/tutorials/beginner/pytorch_with_examples.html#pytorch-custom-nn-modules
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!
Callum
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