Fill in the blanks : Solve above blanks only one number D Question 1 11 10 12

Fill in the blanks : Solve above blanks only one number

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D Question 1 11 10 12 13 nn.Linear( 8 9 1 class SoftMaxRegression (nn.Module): 2 def_init_(self): 3 4 6 5 super()._init_(0) # define layers self.flatten = nn.Flatten() self.linear = nn. Linear(784, 10) def forward (self, x): # Now it only takes a call to the layer to make predictions y = self. flatten(x) y = self.linear(y) return y Suppose you have a set of color images of dimension (3 x 32 x 20 x 20) that belong to 11 different classes. You want to re-use the above simple model in order to work with such images. Give the two updated arguments for the definition of nn.Linear. (Please write only one number for each blank) 4 pts D Question 1 11 10 12 13 nn.Linear( 8 9 1 class SoftMaxRegression (nn.Module): 2 def_init_(self): 3 4 6 5 super()._init_(0) # define layers self.flatten = nn.Flatten() self.linear = nn. Linear(784, 10) def forward (self, x): # Now it only takes a call to the layer to make predictions y = self. flatten(x) y = self.linear(y) return y Suppose you have a set of color images of dimension (3 x 32 x 20 x 20) that belong to 11 different classes. You want to re-use the above simple model in order to work with such images. Give the two updated arguments for the definition of nn.Linear. (Please write only one number for each blank) 4 pts