code: def _setup_strategy(
      self,
  ) -> Tuple[
      "tf.distribute.Strategy",
      "tf.distribute.cluster_resolver.TPUClusterResolver",
  ]:
      if self.is_tpu:
          tf.config.experimental_connect_to_cluster(self._setup_tpu)
          tf.tpu.experimental.initialize_tpu_system(self._setup_tpu)
  
          strategy = tf.distribute.TPUStrategy(self._setup_tpu)
      else:
          # currently no multi gpu is allowed
          if self.is_gpu:
              # TODO: Currently only single GPU is supported
              tf.config.set_visible_devices(
                  self.gpu_list[self.device_idx], "GPU"
              )
              strategy = tf.distribute.OneDeviceStrategy(
                  device=f"/gpu:{self.device_idx}"
              )
          else:
              tf.config.set_visible_devices([], "GPU")  # disable GPU
              strategy = tf.distribute.OneDeviceStrategy(
                  device=f"/cpu:{self.device_idx}"
              )
  
      return strategy
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/benchmark/benchmark_args_tf.py
imports: from dataclasses import dataclass, field
  from typing import Tuple
  from ..utils import cached_property, is_tf_available, logging, tf_required
  from .benchmark_args_utils import BenchmarkArguments
label_desc: Use image node_id 3 for calling the TensorFlowBenchmarkArguments obj's underlying member method code with example usage: obj._setup_strategy() and returns: strategy