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Regarding two questions regarding the exercises. Please see the two comments:
initialise weights to zero: check out this code -> zero_() method call on paramters (the underscore tell you that is changing the state as far as I know)
if you make your custom module, it has the attributes you give it (and some methods it inherits). So a nn.Linear instance has attributes weight and bias, not your custom class bases on nn.Module
class LinearRegression(nn.Module):
def __init__(self):
"""Everything stateful which you need to use your model goes here."""
super().__init__() # needs to be here for API reasons -> call nn.Module.__init__
self.linear_reg = nn.Linear(1, 1)
def forward(self, x): # now with input
return self.linear_reg(x)
lin_reg = LinearRegression()
lin_reg.linear_reg.weight # access weight of underlying nn.Linear instance
The text was updated successfully, but these errors were encountered:
Regarding two questions regarding the exercises. Please see the two comments:
initialise weights to zero: check out this code ->
zero_()
method call on paramters (the underscore tell you that is changing the state as far as I know)if you make your custom module, it has the attributes you give it (and some methods it inherits). So a
nn.Linear
instance has attributesweight
andbias
, not your custom class bases onnn.Module
The text was updated successfully, but these errors were encountered: