rand¶
该OP返回符合均匀分布的,范围在[0, 1)的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: 符合均匀分布的范围为[0, 1)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.rand(shape=[2, 3])
# [[0.451152 , 0.55825245, 0.403311 ], # random
# [0.22550228, 0.22106001, 0.7877319 ]] # 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.rand(shape=[dim1, dim2, 2])
# [[[0.8879919 , 0.25788337], # random
# [0.28826773, 0.9712097 ], # random
# [0.26438272, 0.01796806]], # random
# [[0.33633623, 0.28654453], # random
# [0.79109055, 0.7305809 ], # random
# [0.870881 , 0.2984597 ]]] # 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.rand(shape_tensor)
# [[0.22920267, 0.841956 , 0.05981819], # random
# [0.4836288 , 0.24573246, 0.7516129 ]] # random