Python chainer.functions 模块，maxout() 实例源码

def __call__(self, x):
        return functions.maxout(x, self.pool_size)

def check_forward(self, x_data):
        x = chainer.Variable(x_data)
        y = functions.maxout(x, self.pool_size, self.axis)
        self.assertEqual(y.data.dtype, self.dtype)
        gradient_check.assert_allclose(self.y, y.data)

def check_backward(self, x_data, y_grad):
        gradient_check.check_backward(
            lambda x: functions.maxout(x, self.pool_size, self.axis),
            x_data, y_grad, eps=0.125)

def test_invalid_shape_cpu(self):
        with self.assertRaises(self.error):
            functions.maxout(self.x, self.pool_size)

def test_invalid_shape_gpu(self):
        self.x.to_gpu()
        with self.assertRaises(self.error):
            functions.maxout(self.x, self.pool_size)

def __init__(self, pool_size, axis=1):
        self._function = "maxout"
        self.pool_size = pool_size
        self.axis = axis

def __call__(self, x):
        return F.maxout(x, self.pool_size, self.axis)

def __call__(self, x):
        return functions.maxout(x, self.pool_size)

def __init__(self, pool_size, axis=1):
        self._function = "maxout"
        self.pool_size = pool_size
        self.axis = axis

def __call__(self, x):
        return F.maxout(x, self.pool_size, self.axis)

def __init__(self, pool_size, axis=1):
        self._function = "maxout"
        self.pool_size = pool_size
        self.axis = axis

def __call__(self, x):
        return F.maxout(x, self.pool_size, self.axis)

def __init__(self, pool_size, axis=1):
        self._function = "maxout"
        self.pool_size = pool_size
        self.axis = axis

def __call__(self, x):
        return F.maxout(x, self.pool_size, self.axis)