class_docstr: Generator of fake examples randomly and deterministically generated.
class_docstr_tok: ["Generator","of","fake","examples","randomly","and","deterministically","generated","."]
docstr: Yields all fake examples deterministically.
docstr_tok: ["Yields","all","fake","examples","deterministically","."]
code: def __iter__(self):
      """Yields all fake examples deterministically."""
      rng = np.random.default_rng(self._seed)
      for _ in range(self._num_examples):
          yield self._generate_example(rng)
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import contextlib
  import enum
  import functools
  import os
  from typing import Any, Callable, Iterator, Optional
  from unittest import mock
  from absl import logging
  from etils import epath
  import numpy
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import decode
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import file_adapters
  from tensorflow_datasets.core import read_only_builder
  from tensorflow_datasets.core import reader
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core.data_sources import array_record
  from tensorflow_datasets.core.utils import dtype_utils
  from tensorflow_datasets.core.utils import tree_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.testing import test_utils
label_desc: Use image node_id 5 for calling the RandomFakeGenerator obj's underlying member method code with example usage: obj.__iter__() without return types