standard_normal¶

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

Returns a Tensor filled with random values sampled from a standard normal distribution with mean 0 and standard deviation 1, with shape and dtype.

Parameters

• shape (tuple|list|Tensor) – Shape of the Tensor to be created. The data type is int32 or int64 . If shape is a list or tuple, each element of it should be integer or 0-D Tensor with shape []. If shape is an Tensor, it should be an 1-D Tensor which represents a list.

• dtype (str|np.dtype, optional) – The data type of the output Tensor. Supported data types: float32, float64. Default is None, use global default dtype (see get_default_dtype for details).

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

A Tensor filled with random values sampled from a standard normal distribution with mean 0 and standard deviation 1, with shape and dtype.

Return type

Tensor

Examples

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