standard_normal

paddle. standard_normal ( shape, dtype=None, name=None ) [源代码]

返回符合标准正态分布(均值为 0,标准差为 1 的正态随机分布)的随机 Tensor,形状为 shape,数据类型为 dtype

参数

  • shape (list|tuple|Tensor) - 生成的随机 Tensor 的形状。如果 shape 是 list、tuple,则其中的元素可以是 int,或者是形状为[1]且数据类型为 int32、int64 的 Tensor。如果 shape 是 Tensor,则是数据类型为 int32、int64 的 1-D Tensor。

  • dtype (str|np.dtype,可选) - 输出 Tensor 的数据类型,支持 float32、float64。当该参数值为 None 时,输出 Tensor 的数据类型为 float32。默认值为 None。

  • 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

Tensor:符合标准正态分布的随机 Tensor,形状为 shape,数据类型为 dtype

示例代码

import paddle

# example 1: attr shape is a list which doesn't contain Tensor.
out1 = paddle.standard_normal(shape=[2, 3])
# [[-2.923464  ,  0.11934398, -0.51249987],  # random
#  [ 0.39632758,  0.08177969,  0.2692008 ]]  # random

# example 2: attr shape is a list which contains Tensor.
dim1 = paddle.to_tensor([2], 'int64')
dim2 = paddle.to_tensor([3], 'int32')
out2 = paddle.standard_normal(shape=[dim1, dim2, 2])
# [[[-2.8852394 , -0.25898588],  # random
#   [-0.47420555,  0.17683524],  # random
#   [-0.7989969 ,  0.00754541]],  # random
#  [[ 0.85201347,  0.32320443],  # random
#   [ 1.1399018 ,  0.48336947],  # random
#   [ 0.8086993 ,  0.6868893 ]]]  # random

# example 3: attr shape is a Tensor, the data type must be int64 or int32.
shape_tensor = paddle.to_tensor([2, 3])
out3 = paddle.standard_normal(shape_tensor)
# [[-2.878077 ,  0.17099959,  0.05111201]  # random
#  [-0.3761474, -1.044801  ,  1.1870178 ]]  # random