.. _op_ai_onnx_RandomNormal:

RandomNormal
============

- **Domain**: ``ai.onnx``
- **Since version**: 22

Generate a tensor with random values drawn from a normal distribution. The shape
of the tensor is specified by the ``shape`` argument and the parameter of the normal distribution
specified by ``mean`` and ``scale``.

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 normal distribution

**Attributes**

- **dtype** (*int*): The data type for the elements of the output tensor. Default is TensorProto::FLOAT.
- **mean** (*float*): The mean of the normal distribution.
- **scale** (*float*): The standard deviation of the normal distribution.
- **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_randomnormal**

.. code-block:: text

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

.. code-block:: text

    Inputs:

    Outputs:
      y: shape=(2, 3), dtype=float32
        [[ 0.04646347,  1.3829458 ,  0.1371488 ],
         [-1.691909  ,  0.6007101 ,  0.24345492]]

**test_cc_randomnormal_double**

.. code-block:: text

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

.. code-block:: text

    Inputs:

    Outputs:
      y: shape=(2, 3), dtype=float64
        [[ 0.04646347,  1.38294577,  0.1371488 ],
         [-1.69190901,  0.60071012,  0.24345492]]

**test_cc_randomnormal_seeded**

.. code-block:: text

    Node:
      RandomNormal() -> (y)
      Attributes:
        mean = 1.0
        scale = 2.0
        seed = 42.0
        shape = [2, 3]

.. code-block:: text

    Inputs:

    Outputs:
      y: shape=(2, 3), dtype=float32
        [[-7.8826690e-01,  6.6930413e-02,  4.1850791e+00],
         [-2.7278478e+00,  2.0848513e-03,  4.0150185e+00]]

Differences with previous version (1)
-------------------------------------

**SchemaDiff**: ``RandomNormal`` (domain ``'ai.onnx'``)

* old version: 1
* new version: 22
* breaking: no

**Type constraints:**

* changed 'T': added types: ['tensor(bfloat16)']

Version History
---------------

- :doc:`Version 1 <RandomNormal-1>`