randint_like

paddle. randint_like ( x, low=0, high=None, dtype=None, name=None ) [source]

This OP returns a Tensor filled with random integers from a discrete uniform distribution in the range [low, high), with the same shape as x. (use dtype if dtype is not None) If high is None (the default), the range is [0, low).

Parameters
  • x (Tensor) – The input tensor which specifies shape. The dtype of x can be bool, int32, int64, float16, float32, float64.

  • low (int) – The lower bound on the range of random values to generate. The low is included in the range. If high is None, the range is [0, low). Default is 0.

  • high (int, optional) – The upper bound on the range of random values to generate, the high is excluded in the range. Default is None (see above for behavior if high = None). Default is None.

  • dtype (str|np.dtype, optional) – The data type of the output tensor. Supported data types: bool, int32, int64, float16, float32, float64. If dytpe is None, the data type is the same as x’s data type. Default is None.

  • name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name.

Returns

A Tensor filled with random integers from a discrete uniform distribution in the range [low, high), with shape and dtype.

Return type

Tensor

Examples

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