code: def create_examples(num_examples, input_mean):
      """Create ExampleProto's containing data."""
      ids = np.arange(num_examples).reshape([num_examples, 1])
      inputs = np.random.randn(num_examples, 1) + input_mean
      target = inputs - input_mean
      examples = []
      for row in range(num_examples):
          ex = example_pb2.Example()
          ex.features.feature["id"].bytes_list.value.append(
              bytes(ids[row, 0])
          )
          ex.features.feature["target"].float_list.value.append(
              target[row, 0]
          )
          ex.features.feature["inputs"].float_list.value.append(
              inputs[row, 0]
          )
          examples.append(ex)
      return examples
  
file_path: tensorflow-upstream/tensorflow/tools/gcs_test/python/gcs_smoke.py
imports: import random
  import sys
  import time
  import numpy
  import tensorflow
  from tensorflow.core.example import example_pb2
  from tensorflow.python.lib.io import file_io
label_desc: Use image node_id 1 for calling a global function with example usage: create_examples(num_examples, input_mean) and returns: examples