docstr: Returns a tf.data.Dataset with dynamic embedding as input.
docstr_tok: ["Returns","a","tf.data.Dataset","with","dynamic","embedding","as","input","."]
code: def _create_dataset(self):
      """Returns a tf.data.Dataset with dynamic embedding as input."""
      dataset = tf.data.Dataset.range(100)
      dataset = dataset.batch(batch_size=4, drop_remainder=True)
  
      def _parse(example):
          string_ids = tf.strings.as_string(example)
          input_embed = de_ops.dynamic_embedding_lookup(
              string_ids,
              self._config,
              "input_embed",
              service_address=self._kbs_address,
              skip_gradient_update=True,
          )
          return input_embed
  
      dataset = dataset.map(_parse, num_parallel_calls=2)
      return dataset
  
imports: import itertools
  from absl.testing import parameterized
  from research.carls import context
  from research.carls import dynamic_embedding_ops
  from research.carls.testing import test_util
  import numpy
  import tensorflow
label_desc: Use image node_id 9 for calling the DynamicEmbeddingOpsTest obj's underlying member method code with example usage: obj._create_dataset() and returns: dataset, input_embed