updates.py 文件源码

def setUp(self):
    self.initial = np.array([0.1, 0.1], dtype='float32')
    x = theano.shared(self.initial)

    self.params = [x]

    left_bound = T.fscalar('left bound')
    right_bound = T.fscalar('right bound')

    self.inputs = [left_bound, right_bound]

    y = T.sum(x)
    loss = -T.log(y - left_bound) - T.log(right_bound - y) + 1.0e-3 * T.sum(x ** 2)

    self.loss = loss
    x0 = (0.01 + 0.011 + 2.0 + 2.1) / 4.0
    self.approx_solution = np.array([x0 / 2, x0 / 2], dtype='float32')

    self.get_inputs = lambda : [
        np.float32(np.random.uniform(0.01, 0.011)),
        np.float32(np.random.uniform(2.0, 2.1)),
      ]

    x_sub = T.fvector('x sub')
    self.get_loss = theano.function([x_sub] + self.inputs, self.loss, givens=[(self.params[0], x_sub)])