Normal¶

class paddle.nn.initializer. Normal ( mean=0.0, std=1.0, name=None ) [source]

The Random Normal (Gaussian) distribution initializer.

Parameters

• mean (float, optional) – mean of the normal distribution. Default is 0.0.

• std (float, optional) – standard deviation of the normal distribution. Default is 1.0.

• name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name. Default: None.

Returns

A parameter initialized by Random Normal (Gaussian) distribution.

Examples

>>> import paddle

>>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')
>>> weight_attr = paddle.framework.ParamAttr(
...     name="linear_weight",
...     initializer=paddle.nn.initializer.Normal(mean=0.0, std=2.0))
>>> bias_attr = paddle.framework.ParamAttr(
...     name="linear_bias",
...     initializer=paddle.nn.initializer.Normal(mean=0.0, std=2.0))
>>> 
>>> linear = paddle.nn.Linear(2, 2, weight_attr=weight_attr, bias_attr=bias_attr)
>>> print(linear.weight)
Parameter containing:
Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=False,
[[ 2.1973135 -2.2697184],
 [-1.9104223 -1.0541488]])
>>> print(linear.bias)
Parameter containing:
Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=False,
[ 0.7885926  -0.74719954])
>>> res = linear(data)
>>> print(res)
Tensor(shape=[3, 1, 2], dtype=float32, place=Place(cpu), stop_gradient=False,
[[[ 1.0754838 -4.071067 ]],
 [[ 1.0754838 -4.071067 ]],
 [[ 1.0754838 -4.071067 ]]])