Range

Range - 11

Version

  • name: Range (GitHub)

  • 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.