randn¶
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