PaddlePaddle

 paddle / randn


randn

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

该OP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|core.VarDesc.VarType, 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) - 输出的名字。一般无需设置,默认值为None。该参数供开发人员打印调试信息时使用,具体用法请参见 Name

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.randn(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.randn(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.randn(shape_tensor)
# [[-2.878077 ,  0.17099959,  0.05111201]  # random
#  [-0.3761474, -1.044801  ,  1.1870178 ]]  # random

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