randint¶
该OP返回服从均匀分布的、范围在[low
, high
)的随机Tensor,形状为 shape
,数据类型为 dtype
。当 high
为None时(默认),均匀采样的区间为[0, low
)。
参数¶
low (int) - 要生成的随机值范围的下限,
low
包含在范围中。当high
为None时,均匀采样的区间为[0,low
)。默认值为0。high (int, 可选) - 要生成的随机值范围的上限,
high
不包含在范围中。默认值为None,此时范围是[0,low
)。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。。默认值为[1]。dtype (str|np.dtype|core.VarDesc.VarType, 可选) - 输出Tensor的数据类型,支持int32、int64。当该参数值为None时, 输出Tensor的数据类型为int64。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:从区间[
low
,high
)内均匀分布采样的随机Tensor,形状为shape
,数据类型为dtype
。
代码示例¶
import paddle
# example 1:
# attr shape is a list which doesn't contain Tensor.
out1 = paddle.randint(low=-5, high=5, shape=[3])
# [0, -3, 2] # 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.randint(low=-5, high=5, shape=[dim1, dim2])
# [[0, -1, -3], # random
# [4, -2, 0]] # random
# example 3:
# attr shape is a Tensor
shape_tensor = paddle.to_tensor(3)
out3 = paddle.randint(low=-5, high=5, shape=shape_tensor)
# [-2, 2, 3] # random
# example 4:
# data type is int32
out4 = paddle.randint(low=-5, high=5, shape=[3], dtype='int32')
# [-5, 4, -4] # random
# example 5:
# Input only one parameter
# low=0, high=10, shape=[1], dtype='int64'
out5 = paddle.randint(10)
# [7] # random