tensorflow/models · error · ValueError

Attribute {head.name} not found in model outputs.

Error message

Attribute {head.name} not found in model outputs.

What it means

Error "Attribute {head.name} not found in model outputs." thrown in tensorflow/models.

Source

Thrown at official/vision/tasks/retinanet.py:176

                           box_sample_weight: tf.Tensor) -> float:
    """Computes attribute loss.

    Args:
      attribute_heads: a list of attribute head configs.
      outputs: RetinaNet model outputs.
      labels: RetinaNet labels.
      box_sample_weight: normalized bounding box sample weights.

    Returns:
      Attribute loss of all attribute heads.
    """
    params = self.task_config
    attribute_loss = 0.0
    for head in attribute_heads:
      if head.name not in labels['attribute_targets']:
        raise ValueError(f'Attribute {head.name} not found in label targets.')
      if head.name not in outputs['attribute_outputs']:
        raise ValueError(f'Attribute {head.name} not found in model outputs.')

      if head.type == 'regression':
        y_true_att = loss_utils.multi_level_flatten(
            labels['attribute_targets'][head.name], last_dim=head.size
        )
        y_pred_att = loss_utils.multi_level_flatten(
            outputs['attribute_outputs'][head.name], last_dim=head.size
        )
        att_loss_fn = tf_keras.losses.Huber(
            1.0, reduction=tf_keras.losses.Reduction.SUM)
        att_loss = att_loss_fn(
            y_true=y_true_att,
            y_pred=y_pred_att,
            sample_weight=box_sample_weight)
      elif head.type == 'classification':
        y_true_att = loss_utils.multi_level_flatten(
            labels['attribute_targets'][head.name], last_dim=None
        )

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Ensure the model outputs contain the attribute head's outputs keyed by head.name.
2. Add the missing attribute head to the model or fix the head name in the config.

When it happens

Trigger: Thrown at official/vision/tasks/retinanet.py:176 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/101c854ac84af493. Report an issue: GitHub.