class_docstr: Benchmarks for `tf.data.experimental.parallel_interleave()`.
class_docstr_tok: ["Benchmarks","for","`","tf.data.experimental.parallel_interleave","(",")","`","."]
code: def _benchmark(
      self,
      interleave_version,
      num_elements,
      benchmark_id,
      benchmark_label,
      initial_delay_us=0,
      remainder_delay_us=0,
      cycle_length=10,
      iters=100,
      num_parallel_calls=None,
      name=None,
  ):
      dataset = self.make_dataset(
          interleave_version=interleave_version,
          initial_delay=initial_delay_us,
          remainder_delay=remainder_delay_us,
          cycle_length=cycle_length,
          num_parallel_calls=num_parallel_calls,
      )
  
      self.run_and_report_benchmark(
          dataset=dataset,
          num_elements=num_elements,
          iters=iters,
          warmup=True,
          extras={
              "model_name": "interleave.benchmark.%s.%d"
              % (benchmark_label, benchmark_id),
              "parameters": "%d.%d.%d.%s"
              % (
                  num_elements,
                  cycle_length,
                  iters,
                  str(num_parallel_calls),
              ),
          },
          name=name,
      )
  
file_path: tensorflow/tensorflow/python/data/benchmarks/interleave_benchmark.py
imports: from tensorflow.python.data.benchmarks import benchmark_base
  from tensorflow.python.data.experimental.ops import interleave_ops
  from tensorflow.python.data.experimental.ops import testing
  from tensorflow.python.data.ops import dataset_ops
label_desc: Use image node_id 3 for calling the ParallelInterleaveBenchmark obj's underlying member method code with example usage: obj._benchmark(interleave_version, num_elements, benchmark_id, benchmark_label, initial_delay_us, remainder_delay_us, cycle_length, iters, num_parallel_calls, name) without return types