In this part, you are asked to program with PyTorch, NOT NumPy.
Define a deep neural network module (class) named Linear_Model.
It has the following architecture:
2 layers: 1 hidden layer and 1 output layer.
No activation function. That is, the connection between two consecutive layers is only an affine transformation.
### WRITE YOUR SOLUTION HERE ###
class Linear_Model(nn.Module):
def __init__(self, in_features, hidden_features, out_features):
super().__init__()
self.in_features = in_features
self.hidden_features = hidden_features
self.out_features = out_features
self.linear0 = nn.Linear(in_features, hidden_features)
self.linear1 = nn.Linear(hidden_features, out_features)
def forward(self, x):
x = self.linear0(x)
x = self.linear1(x)
return x
""" END OF THIS PART """