tensorflow/models · error · ValueError

Groundtruth matting map must have only 1 layer, but got {} l

Error message

Groundtruth matting map must have only 1 layer, but got {} layers.

What it means

Error "Groundtruth matting map must have only 1 layer, but got {} layers." thrown in tensorflow/models.

Source

Thrown at official/vision/losses/segmentation_losses.py:89

    Returns:
       A 0-D float which stores the overall loss of the batch.
    """
    _, height, width, num_classes = logits.get_shape().as_list()
    output_dtype = logits.dtype
    num_layers = labels.get_shape().as_list()[-1]
    if not self._use_binary_cross_entropy:
      if num_layers > 1:
        raise ValueError(
            'Groundtruth mask must have only 1 layer if using categorical'
            'cross entropy, but got {} layers.'.format(num_layers))
    if self._gt_is_matting_map:
      if num_classes != 2:
        raise ValueError(
            'Groundtruth matting map only supports 2 classes, but got {} '
            'classes.'.format(num_classes))
      if num_layers > 1:
        raise ValueError(
            'Groundtruth matting map must have only 1 layer, but got {} '
            'layers.'.format(num_layers))

    class_weights = (
        self._class_weights if self._class_weights else [1] * num_classes)
    if num_classes != len(class_weights):
      raise ValueError(
          'Length of class_weights should be {}'.format(num_classes))
    class_weights = tf.constant(class_weights, dtype=output_dtype)

    if not self._gt_is_matting_map:
      labels = tf.cast(labels, tf.int32)
    if self._use_groundtruth_dimension:
      # TODO(arashwan): Test using align corners to match deeplab alignment.
      logits = tf.image.resize(
          logits, tf.shape(labels)[1:3], method=tf.image.ResizeMethod.BILINEAR)
    else:
      labels = tf.image.resize(

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/vision/losses/segmentation_losses.py:89 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/b5711a9085cf1d80. Report an issue: GitHub.