parameters: (start, limit=None, delta=1, name="range")
return_statement: return gen_math_ops._range(start, limit, delta, name=name)
docstring: Creates a sequence of integers.
  
    Creates a sequence of integers that begins at `start` and extends by
    increments of `delta` up to but not including `limit`.
  
    Like the Python builtin `range`, `start` defaults to 0, so that
    `range(n) = range(0, n)`.
  
    For example:
  
    ```
    # 'start' is 3
    # 'limit' is 18
    # 'delta' is 3
    tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
  
    # 'limit' is 5
    tf.range(limit) ==> [0, 1, 2, 3, 4]
    ```
  
    Args:
      start: A 0-D (scalar) of type `int32`. First entry in sequence.
        Defaults to 0.
      limit: A 0-D (scalar) of type `int32`. Upper limit of sequence,
        exclusive.
      delta: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
        Number that increments `start`.
      name: A name for the operation (optional).
  
    Returns:
      An 1-D `int32` `Tensor`.
docstring_summary: Creates a sequence of integers.
docstring_tokens: Creates a sequence of integers .
function: def range(start, limit=None, delta=1, name="range"):
    """Creates a sequence of integers.
  
    Creates a sequence of integers that begins at `start` and extends by
    increments of `delta` up to but not including `limit`.
  
    Like the Python builtin `range`, `start` defaults to 0, so that
    `range(n) = range(0, n)`.
  
    For example:
  
    ```
    # 'start' is 3
    # 'limit' is 18
    # 'delta' is 3
    tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
  
    # 'limit' is 5
    tf.range(limit) ==> [0, 1, 2, 3, 4]
    ```
  
    Args:
      start: A 0-D (scalar) of type `int32`. First entry in sequence.
        Defaults to 0.
      limit: A 0-D (scalar) of type `int32`. Upper limit of sequence,
        exclusive.
      delta: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
        Number that increments `start`.
      name: A name for the operation (optional).
  
    Returns:
      An 1-D `int32` `Tensor`.
    """
    if limit is None:
      start, limit = 0, start
    return gen_math_ops._range(start, limit, delta, name=name)
function_tokens: def range ( start , limit = None , delta = 1 , name = "range" ) : if limit is None : start , limit = 0 , start return gen_math_ops . _range ( start , limit , delta , name = name )