tensorflow/models · error · ValueError

The number of logical devices %d is not supported. Supported

Error message

The number of logical devices %d is not supported. Supported numbers are 1, 2, 4, 8, 16

What it means

Error "The number of logical devices %d is not supported. Supported numbers are 1, 2, 4, 8, 16" thrown in tensorflow/models.

Source

Thrown at official/vision/train_spatial_partitioning.py:61

  Returns:
    A list of integers specifying the computation shape.

  Raises:
    ValueError: If the number of logical devices is not supported.
  """
  num_logical_devices = np.prod(input_partition_dims)
  if num_logical_devices == 1:
    return [1, 1, 1, 1]
  elif num_logical_devices == 2:
    return [1, 1, 1, 2]
  elif num_logical_devices == 4:
    return [1, 2, 1, 2]
  elif num_logical_devices == 8:
    return [2, 2, 1, 2]
  elif num_logical_devices == 16:
    return [4, 2, 1, 2]
  else:
    raise ValueError(
        'The number of logical devices %d is not supported. Supported numbers '
        'are 1, 2, 4, 8, 16' % num_logical_devices)


def create_distribution_strategy(distribution_strategy,
                                 tpu_address,
                                 input_partition_dims=None,
                                 num_gpus=None):
  """Creates distribution strategy to use for computation."""

  if input_partition_dims is not None:
    if distribution_strategy != 'tpu':
      raise ValueError('Spatial partitioning is only supported '
                       'for TPUStrategy.')

    # When `input_partition_dims` is specified create custom TPUStrategy
    # instance with computation shape for model parallelism.
    resolver = tf.distribute.cluster_resolver.TPUClusterResolver(

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Set the number of logical devices to one of 1, 2, 4, 8, or 16.
2. Adjust the TPU topology or device partition config to a supported count.

When it happens

Trigger: Thrown at official/vision/train_spatial_partitioning.py:61 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/6a0187dd8aba874f. Report an issue: GitHub.