tensorflow/models · error · ValueError

TpuBatchNormalization does not support fused=True.

Error message

TpuBatchNormalization does not support fused=True.

What it means

Error "TpuBatchNormalization does not support fused=True." thrown in tensorflow/models.

Source

Thrown at official/projects/edgetpu/vision/modeling/common_modules.py:34

from typing import Optional, Tuple
import numpy as np
import tensorflow as tf, tf_keras
import tensorflow.compat.v1 as tf1

from tensorflow.python.tpu import tpu_function  # pylint: disable=g-direct-tensorflow-import


MEAN_RGB = (0.5 * 255, 0.5 * 255, 0.5 * 255)
STDDEV_RGB = (0.5 * 255, 0.5 * 255, 0.5 * 255)


@tf_keras.utils.register_keras_serializable(package='Vision')
class TpuBatchNormalization(tf_keras.layers.BatchNormalization):
  """Cross replica batch normalization."""

  def __init__(self, fused: Optional[bool] = False, **kwargs):
    if fused in (True, None):
      raise ValueError('TpuBatchNormalization does not support fused=True.')
    super(TpuBatchNormalization, self).__init__(fused=fused, **kwargs)

  def _cross_replica_average(self, t: tf.Tensor, num_shards_per_group: int):
    """Calculates the average value of input tensor across TPU replicas."""
    num_shards = tpu_function.get_tpu_context().number_of_shards
    group_assignment = None
    if num_shards_per_group > 1:
      if num_shards % num_shards_per_group != 0:
        raise ValueError(
            'num_shards: %d mod shards_per_group: %d, should be 0' %
            (num_shards, num_shards_per_group))
      num_groups = num_shards // num_shards_per_group
      group_assignment = [[
          x for x in range(num_shards) if x // num_shards_per_group == y
      ] for y in range(num_groups)]
    return tf1.tpu.cross_replica_sum(t, group_assignment) / tf.cast(
        num_shards_per_group, t.dtype)

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/edgetpu/vision/modeling/common_modules.py:34 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/26e3bfc9ac84f6cd. Report an issue: GitHub.