code: def random_genenerator():
      generator: tf.random.Generator = tf.random.Generator.from_seed(42)
      for unused_i in range(10):
          r = {
              "input1": generator.uniform(
                  shape=(2, 1), minval=0.0, maxval=1.0
              ),
              "input2": generator.uniform(
                  shape=(2, 1), minval=0.0, maxval=1.0
              ),
              "input3": tf.constant(
                  [[b"a"], [b"b"]], shape=(2, 1), dtype=tf.string
              ),
          }
          yield r
  
imports: import itertools
  import os
  import tempfile
  from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import model_eval_lib
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.extractors import features_extractor
  from tensorflow_model_analysis.extractors import tflite_predict_extractor
  from tensorflow_model_analysis.proto import config_pb2
  from tfx_bsl.tfxio import test_util
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: random_genenerator() without return types