openvino/docs/ops/generation/Range_4.md

Range

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Versioned name: Range-4

Category: Generation

Short description: Range operation generates a sequence of numbers according input values [start, stop) with a step.

Attributes:

• output_type

  • Description: the output tensor type
  • Range of values: any numeric type
  • Type: string
  • Required: yes

Inputs:

• 1: "start" - A scalar of type T1. Required.
• 2: "stop" - A scalar of type T2. Required.
• 3: "step" - A scalar of type T3. If step is equal to zero after casting to output_type, behavior is undefined. Required.

Outputs:

• 1: A tensor with type specified by attribute output_type.

Types

• T1, T2, T3: any numeric type.

Detailed description:

Range operation generates a sequence of numbers starting from the value in the first input (start) up to but not including the value in the second input (stop) with a step equal to the value in the third input, according to the following formula:

For a positive step:

.. math::

start<=val[i]<stop,

for a negative step:

.. math::

start>=val[i]>stop,

the i-th element is calculated by the following formula:

.. math::

val[i+1]=val[i]+step.

The calculations are done after casting all values to accumulate_type(output_type). accumulate_type is a type that have better or equal accuracy for accumulation than output_type on current hardware, e.g. fp64 for fp16. The number of elements is calculated in the floating-point type according to the following formula:

.. math::

max(ceil((end − start) / step), 0)

This is aligned with PyTorch's operation torch.arange, to align with tensorflow operation tf.range all inputs must be casted to output_type before calling Range. The rounding for casting values are done towards zero.

Examples

Example 1: positive step

.. code-block:: cpp

<layer ... type="Range">
    <data output_type="i32">
    <input>
        <port id="0">  < !-- start value: 2 -->
        </port>
        <port id="1">  < !-- stop value: 23 -->
        </port>
        <port id="2">  < !-- step value: 3 -->
        </port>
    </input>
    <output>
        <port id="3">
            <dim>7</dim> < !-- [ 2,  5,  8, 11, 14, 17, 20] -->
        </port>
    </output>
</layer>

Example 2: negative step

.. code-block:: cpp

<layer ... type="Range">
    <data output_type="i32">
    <input>
        <port id="0">  < !-- start value: 23 -->
        </port>
        <port id="1">  < !-- stop value: 2 -->
        </port>
        <port id="2">  < !-- step value: -3 -->
        </port>
    </input>
    <output>
        <port id="3">
            <dim>7</dim> < !-- [23, 20, 17, 14, 11, 8, 5] -->
        </port>
    </output>
</layer>

Example 3: floating-point

.. code-block:: cpp

<layer ... type="Range">
    <data output_type="f32">
    <input>
        <port id="0">  < !-- start value: 1 -->
        </port>
        <port id="1">  < !-- stop value: 2.5 -->
        </port>
        <port id="2">  < !-- step value: 0.5 -->
        </port>
    </input>
    <output>
        <port id="3">
            <dim>3</dim> < !-- [ 1.0,  1.5,  2.0] -->
        </port>
    </output>
</layer>

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