(l-onnx-doc-RandomUniform)=

# RandomUniform


(l-onnx-op-randomuniform-22)=

## RandomUniform - 22

### Version

- **name**: [RandomUniform (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#RandomUniform)
- **domain**: `main`
- **since_version**: `22`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 22**.

### Summary

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.

### Attributes

* **dtype - INT** (default is `'1'`):

  The data type for the elements of the output tensor. If not specified, default is TensorProto::FLOAT.

* **high - FLOAT** (default is `'1.0'`):

  Upper boundary of the output values.

* **low - FLOAT** (default is `'0.0'`):

  Lower boundary of the output values.

* **seed - FLOAT** :

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

* **shape - INTS** (required) :

  The shape of the output tensor.

### Outputs

- **output** (heterogeneous) - **T**:

  Output tensor of random values drawn from uniform distribution

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain output types to float tensors.

```{toctree}
text_diff_RandomUniform_1_22
```

(l-onnx-op-randomuniform-1)=

## RandomUniform - 1

### Version

- **name**: [RandomUniform (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#RandomUniform)
- **domain**: `main`
- **since_version**: `1`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 1**.

### Summary

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.

### Attributes

* **dtype - INT** (default is `'1'`):

  The data type for the elements of the output tensor. If not specified, default is TensorProto::FLOAT.

* **high - FLOAT** (default is `'1.0'`):

  Upper boundary of the output values.

* **low - FLOAT** (default is `'0.0'`):

  Lower boundary of the output values.

* **seed - FLOAT** :

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

* **shape - INTS** (required) :

  The shape of the output tensor.

### Outputs

- **output** (heterogeneous) - **T**:

  Output tensor of random values drawn from uniform distribution

### Type Constraints

* **T** in ( `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain output types to float tensors.