Uniform¶
均匀分布初始化方法。
参数¶
low (float，可选) - 均匀分布的下界，默认值为 \(-1.0\)。
high (float，可选) - 均匀分布的上界，默认值为 \(1.0\)。
name (str，可选) - 具体用法请参见 Name，一般无需设置，默认值为 None。
返回¶
由均匀分布初始化的参数。
代码示例¶
>>> import paddle
>>> paddle.seed(1)
>>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')
>>> weight_attr = paddle.framework.ParamAttr(
... name="linear_weight",
... initializer=paddle.nn.initializer.Uniform(low=-0.5, high=0.5))
>>> bias_attr = paddle.framework.ParamAttr(
... name="linear_bias",
... initializer=paddle.nn.initializer.Uniform(low=-0.5, high=0.5))
>>> 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,
[[-0.48212373, 0.26492310],
[ 0.17605734, -0.45379421]])
>>> print(linear.bias)
Parameter containing:
Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=False,
[-0.11236754, 0.46462214])
>>> res = linear(data)
>>> print(res)
Tensor(shape=[3, 1, 2], dtype=float32, place=Place(cpu), stop_gradient=False,
[[[-0.41843393, 0.27575102]],
[[-0.41843393, 0.27575102]],
[[-0.41843393, 0.27575102]]])