docstr: Generate examples as dicts.
docstr_tok: ["Generate","examples","as","dicts","."]
code: def _generate_examples(self, examples, num_examples):
      """Generate examples as dicts."""
      examples |= beam.Filter(lambda x: x[0] < num_examples)
      # Record metadata works for common PCollections
      self.info.metadata[f"id_mean_{num_examples}"] = _compute_mean(
          examples
      )
      self.info.metadata[f"label_sum_{num_examples}"] = _compute_sum(
          examples
      )
      return examples
  
imports: import pathlib
  from typing import Callable
  from unittest import mock
  import apache_beam
  from etils import epath
  import numpy
  import pytest
  import tensorflow
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import dataset_utils
  from tensorflow_datasets.core import download
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import utils
label_desc: Use image node_id 2 for calling the CommonPipelineDummyBeamDataset obj's underlying member method code with example usage: obj._generate_examples(examples, num_examples) and returns: examples