from torch import nn
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class BasicNeuralNet(nn.Module):
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def __init__(self):
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super().__init__()
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# Inputs to hidden layer linear transformation
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self.hidden = nn.Linear(784, 256)
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# Output layer, 10 units
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self.output = nn.Linear(256, 10)
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# Define sigmoid activation and softmax output
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self.sigmoid = nn.Sigmoid()
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self.softmax = nn.Softmax(dim=1)
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def forward(self, x):
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# Pass the input tensor through each of the operations
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x = self.hidden(x)
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x = self.sigmoid(x)
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x = self.output(x)
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x = self.softmax(x)
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return x
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