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import torch.nn as nn | |
class NeuralNet(nn.Module): | |
def __init__(self): | |
super().__init__() | |
self.flatten = nn.Flatten() | |
self.layers = nn.Sequential( | |
nn.Linear(28*28, 512), | |
nn.ReLU(), | |
nn.Linear(512, 512), | |
nn.ReLU(), | |
nn.Linear(512, 10) | |
) | |
def forward(self, x): | |
x = self.flatten(x) | |
x = self.layers(x) | |
return x |