(l-onnx-doc-Range)=

# Range


(l-onnx-op-range-27)=

## Range - 27

### Version

- **name**: [Range (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Range)
- **domain**: `main`
- **since_version**: `27`
- **function**: `True`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 27**.

### Summary

Generate a tensor containing a sequence of numbers that begin at `start` and extends by increments of `delta`
up to `limit` (exclusive).

The number of elements in the output of range is computed as below:
```
number_of_elements = max( ceil( (limit - start) / delta ) , 0 )
```
The pseudocode determining the contents of the output is shown below:
```
for(int i=0; i<number_of_elements; ++i) {
  output[i] =  start + (i * delta);
}
```
Example 1:
```
Inputs: start = 3, limit = 9, delta = 3
Output: [3, 6]
```
Example 2:
```
Inputs: start = 10, limit = 4, delta = -2
Output: [10, 8, 6]
```

For `float16` and `bfloat16` inputs, the `stash_type` attribute controls the precision used for
intermediate accumulation. Setting `stash_type` to `1` (float) causes `start`, `limit`, and
`delta` to be cast to 32-bit float before the loop, with the output cast back to the original
type. This avoids precision loss for large ranges where successive additions in float16 or
bfloat16 would otherwise be inexact (e.g. `x + 1 == x` for large `x`).

### Attributes

* **stash_type - INT** (default is `1`):

  The data type used for intermediate computation when T is float16 or bfloat16. Defaults to 1 (float). Has no effect for other types.

### Inputs

- **start** (heterogeneous) - **T**:

  Scalar. First entry for the range of output values.
- **limit** (heterogeneous) - **T**:

  Scalar. Exclusive upper limit for the range of output values.
- **delta** (heterogeneous) - **T**:

  Scalar. Value to step by.

### Outputs

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

  A 1-D tensor with same type as the inputs containing generated range of values.

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)`, `tensor(int16)`, `tensor(int32)`, `tensor(int64)` ):

  Constrain input types to common numeric type tensors.

```{toctree}
text_diff_Range_11_27
```

(l-onnx-op-range-11)=

## Range - 11

### Version

- **name**: [Range (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Range)
- **domain**: `main`
- **since_version**: `11`
- **function**: `True`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 11**.

### Summary

Generate a tensor containing a sequence of numbers that begin at `start` and extends by increments of `delta`
up to `limit` (exclusive).

The number of elements in the output of range is computed as below:
```
number_of_elements = max( ceil( (limit - start) / delta ) , 0 )
```
The pseudocode determining the contents of the output is shown below:
```
for(int i=0; i<number_of_elements; ++i) {
  output[i] =  start + (i * delta);
}
```
Example 1:
```
Inputs: start = 3, limit = 9, delta = 3
Output: [3, 6]
```
Example 2:
```
Inputs: start = 10, limit = 4, delta = -2
Output: [10, 8, 6]
```

#### Function Body

The function definition for this operator.

```
<
  domain: "",
  opset_import: ["" : 11]
>
Range (start, limit, delta) => (output)
{
   sub_result = Sub (limit, start)
   sub_result_casted = Cast <to: int = 1> (sub_result)
   delta_casted = Cast <to: int = 1> (delta)
   div_result = Div (sub_result_casted, delta_casted)
   ceil_result = Ceil (div_result)
   ceil_result_relu = Relu (ceil_result)
   ceil_result_relu_int = Cast <to: int = 7> (ceil_result_relu)
   ceil_result_relu_bool = Cast <to: int = 9> (ceil_result_relu)
   variadic_output, output = Loop (ceil_result_relu_int, ceil_result_relu_bool, start) <body: graph = loop_body_attribute (int64 i, bool cond,  prev) => ( cond_out,  current,  range) {
      cond_out = Identity (cond)
      current = Add (prev, delta)
      range = Identity (prev)
   }>
}
```

### Inputs

- **start** (heterogeneous) - **T**:

  Scalar. First entry for the range of output values.
- **limit** (heterogeneous) - **T**:

  Scalar. Exclusive upper limit for the range of output values.
- **delta** (heterogeneous) - **T**:

  Scalar. Value to step by.

### Outputs

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

  A 1-D tensor with same type as the inputs containing generated range of values.

### Type Constraints

* **T** in ( `tensor(double)`, `tensor(float)`, `tensor(int16)`, `tensor(int32)`, `tensor(int64)` ):

  Constrain input types to common numeric type tensors.