RandomUniform#

  • Domain: ai.onnx

  • Since version: 22

Generate a tensor with random values drawn from a uniform distribution. The shape of the tensor is specified by the shape argument and the range by low and high.

The data type is specified by the ‘dtype’ argument. The ‘dtype’ argument must be one of the data types specified in the ‘DataType’ enum field in the TensorProto message.

Outputs

  • output (T): Output tensor of random values drawn from uniform distribution

Attributes

  • dtype (int): The data type for the elements of the output tensor. If not specified, default is TensorProto::FLOAT.

  • high (float): Upper boundary of the output values.

  • low (float): Lower boundary of the output values.

  • seed (float): (Optional) Seed to the random generator, if not specified we will auto generate one.

  • shape (int[]): The shape of the output tensor.

Type Constraints

  • T: Constrain output types to float tensors. Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16).

Examples#

test_cc_randomuniform

Node:
  RandomUniform() -> (y)
  Attributes:
    shape = [2, 3]

Inputs:

Outputs:
  y: shape=(2, 3), dtype=float32
    [[0.8833108 , 0.431528  , 0.02643377],
     [0.970882  , 0.10634669, 0.32732576]]

test_cc_randomuniform_double

Node:
  RandomUniform() -> (y)
  Attributes:
    dtype = 11
    shape = [2, 3]

Inputs:

Outputs:
  y: shape=(2, 3), dtype=float64
    [[0.88331081, 0.431528  , 0.02643377],
     [0.97088198, 0.10634669, 0.32732576]]

test_cc_randomuniform_seeded

Node:
  RandomUniform() -> (y)
  Attributes:
    low = -1.0
    high = 3.0
    seed = 42.0
    shape = [2, 3]

Inputs:

Outputs:
  y: shape=(2, 3), dtype=float32
    [[ 1.9662595 , -0.36035842,  0.11440456],
     [ 0.37676287, -0.8478793 ,  2.4729123 ]]

Differences with previous version (1)#

SchemaDiff: RandomUniform (domain 'ai.onnx')

  • old version: 1

  • new version: 22

  • breaking: no

Type constraints:

  • changed ‘T’: added types: [‘tensor(bfloat16)’]

Version History#