no_grad¶

class paddle. no_grad [源代码] ¶

创建一个上下文来禁用动态图梯度计算。在此模式下，每次计算的结果都将具有 stop_gradient=True。

也可以用作一个装饰器（需要创建实例对象作为装饰器）。

代码示例¶

          >>> import numpy as np
>>> import paddle

>>> # use as generator

>>> data = np.array([[2, 3], [4, 5]]).astype('float32')
>>> l0 = paddle.nn.Linear(2, 2)  # l0.weight.gradient() is None
>>> l1 = paddle.nn.Linear(2, 2)
>>> with paddle.no_grad():
...     # l1.weight.stop_gradient is False
...     tmp = l1.weight * 2  # tmp.stop_gradient is True
>>> x = paddle.to_tensor(data)
>>> y = l0(x) + tmp
>>> o = l1(y)
>>> o.backward()
>>> print(tmp.gradient() is None)
True
>>> print(l0.weight.gradient() is None)
False

>>> # use as decorator

>>> @paddle.no_grad()
>>> def test_layer():
...     inp = np.ones([3, 1024], dtype='float32')
...     t = paddle.to_tensor(inp)
...     linear1 = paddle.nn.Linear(1024, 4, bias_attr=False)
...     linear2 = paddle.nn.Linear(4, 4)
...     ret = linear1(t)
...     dy_ret = linear2(ret)
...
>>> test_layer()

         