Uniform¶

class paddle.nn.initializer. Uniform ( low=- 1.0, high=1.0, name=None ) [source]

The uniform distribution initializer.

Parameters

• low (float, optional) – Lower boundary of the uniform distribution. Default is \(-1.0\).

• high (float, optional) – Upper boundary of the uniform distribution. Default is \(1.0\).

• name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.

Returns

A parameter initialized by uniform distribution.

Examples

>>> 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]]])