code: def CounterV2(start=0, step=1, dtype=dtypes.int64):
      """Creates a `Dataset` that counts from `start` in steps of size `step`.
  
      Unlike `tf.data.Dataset.range` which will stop at some ending number,
      `Counter` will produce elements indefinitely.
  
      >>> dataset = tf.data.experimental.Counter().take(5)
      >>> list(dataset.as_numpy_iterator())
      [0, 1, 2, 3, 4]
      >>> dataset.element_spec
      TensorSpec(shape=(), dtype=tf.int64, name=None)
      >>> dataset = tf.data.experimental.Counter(dtype=tf.int32)
      >>> dataset.element_spec
      TensorSpec(shape=(), dtype=tf.int32, name=None)
      >>> dataset = tf.data.experimental.Counter(start=2).take(5)
      >>> list(dataset.as_numpy_iterator())
      [2, 3, 4, 5, 6]
      >>> dataset = tf.data.experimental.Counter(start=2, step=5).take(5)
      >>> list(dataset.as_numpy_iterator())
      [2, 7, 12, 17, 22]
      >>> dataset = tf.data.experimental.Counter(start=10, step=-1).take(5)
      >>> list(dataset.as_numpy_iterator())
      [10, 9, 8, 7, 6]
  
      Args:
        start: (Optional.) The starting value for the counter. Defaults to 0.
        step: (Optional.) The step size for the counter. Defaults to 1.
        dtype: (Optional.) The data type for counter elements. Defaults to
          `tf.int64`.
  
      Returns:
        A `Dataset` of scalar `dtype` elements.
      """
      return dataset_ops.Dataset.counter(start, step, dtype)
  
file_path: tensorflow/tensorflow/python/data/experimental/ops/counter.py
imports: from tensorflow.python import tf2
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import dtypes
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: CounterV2(start, step, dtype) and returns: dataset_ops