set_global_initializer¶

paddle.nn.initializer. set_global_initializer ( weight_init, bias_init=None ) [源代码] ¶

该 API 用于设置 Paddle 框架中全局的参数初始化方法。该 API 只对位于其后的代码生效。

模型参数为模型中的 weight 和 bias 统称，在框架中对应 paddle.ParamAttr 类，继承自 paddle.Tensor，是一种可持久化的 variable。该 API 的设置仅对模型参数生效，对通过 create_global_var 、 cn_api_paddle_Tensor_create_tensor 等 API 创建的变量不会生效。

如果创建网络层时还通过 param_attr 、 bias_attr 设置了初始化方式，这里的全局设置将不会生效，因为其优先级更低。

参数¶

weight_init (Initializer) - 设置框架的全局的 weight 参数初始化方法。

bias_init (Initializer，可选) - 设置框架的全局的 bias 参数初始化方法。默认：None。

返回¶

无

代码示例¶

          >>> import paddle
>>> import paddle.nn as nn

>>> nn.initializer.set_global_initializer(nn.initializer.Uniform(), nn.initializer.Constant())
>>> x_var = paddle.uniform((2, 4, 8, 8), dtype='float32', min=-1., max=1.)

>>> # The weight of conv1 is initialized by Uniform
>>> # The bias of conv1 is initialized by Constant
>>> conv1 = nn.Conv2D(4, 6, (3, 3))
>>> y_var1 = conv1(x_var)

>>> # If set param_attr/bias_attr too, global initializer will not take effect
>>> # The weight of conv2 is initialized by Xavier
>>> # The bias of conv2 is initialized by Normal
>>> conv2 = nn.Conv2D(4, 6, (3, 3),
...     weight_attr=nn.initializer.XavierUniform(),
...     bias_attr=nn.initializer.Normal())
>>> y_var2 = conv2(x_var)

>>> # Cancel the global initializer in framework, it will takes effect in subsequent code
>>> nn.initializer.set_global_initializer(None)

         