randint_like¶
返回服从均匀分布的、范围在[low, high)的随机 Tensor，输出的形状与 x 的形状一致，当数据类型 dtype 为 None 时（默认），输出的数据类型与 x 的数据类型一致，当数据类型 dtype 不为 None 时，将输出用户指定的数据类型。当 high 为 None 时（默认），均匀采样的区间为[0, low)。
参数¶
x (Tensor) – 输入的多维 Tensor，数据类型可以是 bool，int32，int64，float16，float32，float64。输出 Tensor 的形状和
x相同。如果dtype为 None，则输出 Tensor 的数据类型与x相同。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)。dtype (str|np.dtype，可选) - 输出 Tensor 的数据类型，支持 bool，int32，int64，float16，float32，float64。当该参数值为 None 时，输出 Tensor 的数据类型与输入 Tensor 的数据类型一致。默认值为 None。
name (str，可选) - 具体用法请参见 Name，一般无需设置，默认值为 None。
返回¶
Tensor：从区间[
low，high)内均匀分布采样的随机 Tensor，形状为x.shape，数据类型为dtype。
代码示例¶
import paddle
# example 1:
# dtype is None and the dtype of x is float16
x = paddle.zeros((1,2)).astype("float16")
out1 = paddle.randint_like(x, low=-5, high=5)
print(out1)
print(out1.dtype)
# [[0, -3]] # random
# paddle.float16
# example 2:
# dtype is None and the dtype of x is float32
x = paddle.zeros((1,2)).astype("float32")
out2 = paddle.randint_like(x, low=-5, high=5)
print(out2)
print(out2.dtype)
# [[0, -3]] # random
# paddle.float32
# example 3:
# dtype is None and the dtype of x is float64
x = paddle.zeros((1,2)).astype("float64")
out3 = paddle.randint_like(x, low=-5, high=5)
print(out3)
print(out3.dtype)
# [[0, -3]] # random
# paddle.float64
# example 4:
# dtype is None and the dtype of x is int32
x = paddle.zeros((1,2)).astype("int32")
out4 = paddle.randint_like(x, low=-5, high=5)
print(out4)
print(out4.dtype)
# [[0, -3]] # random
# paddle.int32
# example 5:
# dtype is None and the dtype of x is int64
x = paddle.zeros((1,2)).astype("int64")
out5 = paddle.randint_like(x, low=-5, high=5)
print(out5)
print(out5.dtype)
# [[0, -3]] # random
# paddle.int64
# example 6:
# dtype is float64 and the dtype of x is float32
x = paddle.zeros((1,2)).astype("float32")
out6 = paddle.randint_like(x, low=-5, high=5, dtype="float64")
print(out6)
print(out6.dtype)
# [[0, -1]] # random
# paddle.float64
# example 7:
# dtype is bool and the dtype of x is float32
x = paddle.zeros((1,2)).astype("float32")
out7 = paddle.randint_like(x, low=-5, high=5, dtype="bool")
print(out7)
print(out7.dtype)
# [[0, -1]] # random
# paddle.bool
# example 8:
# dtype is int32 and the dtype of x is float32
x = paddle.zeros((1,2)).astype("float32")
out8 = paddle.randint_like(x, low=-5, high=5, dtype="int32")
print(out8)
print(out8.dtype)
# [[0, -1]] # random
# paddle.int32
# example 9:
# dtype is int64 and the dtype of x is float32
x = paddle.zeros((1,2)).astype("float32")
out9 = paddle.randint_like(x, low=-5, high=5, dtype="int64")
print(out9)
print(out9.dtype)
# [[0, -1]] # random
# paddle.int64
# example 10:
# dtype is int64 and the dtype of x is bool
x = paddle.zeros((1,2)).astype("bool")
out10 = paddle.randint_like(x, low=-5, high=5, dtype="int64")
print(out10)
print(out10.dtype)
# [[0, -1]] # random
# paddle.int64