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class Sigmoid(Function):
def forward(self, X):
return 1/(1 + np.exp(-X))
def backward(self, dY):
return dY * self.grad['X']
def local_grad(self, X):
s = 1/(1 + np.exp(-X))
grads = {'X': s * (1 - s)}
return grads
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