tensorflow/models · error · ValueError

Unrecognized Distribution Strategy: %r

Error message

Unrecognized Distribution Strategy: %r

What it means

Error "Unrecognized Distribution Strategy: %r" thrown in tensorflow/models.

Source

Thrown at official/common/distribute_utils.py:203

    if num_gpus > 1:
      raise ValueError("`OneDeviceStrategy` can not be used for more than "
                       "one device.")
    return tf.distribute.OneDeviceStrategy("device:GPU:0")

  if distribution_strategy == "mirrored":
    if num_gpus == 0:
      devices = ["device:CPU:0"]
    else:
      devices = ["device:GPU:%d" % i for i in range(num_gpus)]
    return tf.distribute.MirroredStrategy(
        devices=devices,
        cross_device_ops=_mirrored_cross_device_ops(all_reduce_alg, num_packs))

  if distribution_strategy == "parameter_server":
    cluster_resolver = tf.distribute.cluster_resolver.TFConfigClusterResolver()
    return tf.distribute.experimental.ParameterServerStrategy(cluster_resolver)

  raise ValueError("Unrecognized Distribution Strategy: %r" %
                   distribution_strategy)


def configure_cluster(worker_hosts=None, task_index=-1):
  """Set multi-worker cluster spec in TF_CONFIG environment variable.

  Args:
    worker_hosts: comma-separated list of worker ip:port pairs.
    task_index: index of the worker.

  Returns:
    Number of workers in the cluster.
  """
  tf_config = json.loads(os.environ.get("TF_CONFIG", "{}"))
  if tf_config:
    num_workers = (
        len(tf_config["cluster"].get("chief", [])) +
        len(tf_config["cluster"].get("worker", [])))

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/common/distribute_utils.py:203 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/16f180f270d11aa3. Report an issue: GitHub.