def tanh(x: Variable) -> Variable:
data = np.tanh(x.data)
w = 1 - data**2
return x.unary_op(data, w)
def relu(x: Variable) -> Variable:
data = x.data.copy()
np.maximum(data, 0, data)
w = data.copy()
w[w > 0] = 1
return x.unary_op(data, w)
def sigmoid(x: Variable) -> Variable:
data = (np.exp(-x.data) + 1)**(-1)
w = -data + 1
w[:] *= data[:]
return x.unary_op(data, w)
