tensorflow/models · error · ValueError

batch_size cannot be None for panoptic segmentation model.

Error message

batch_size cannot be None for panoptic segmentation model.

What it means

Error "batch_size cannot be None for panoptic segmentation model." thrown in tensorflow/models.

Source

Thrown at official/projects/panoptic/serving/panoptic_maskrcnn.py:39

from official.core import config_definitions as cfg
from official.projects.panoptic.modeling import panoptic_maskrcnn_model
from official.vision.serving import detection


class PanopticSegmentationModule(detection.DetectionModule):
  """Panoptic Segmentation Module."""

  def __init__(self,
               params: cfg.ExperimentConfig,
               *,
               model: tf_keras.Model,
               batch_size: int,
               input_image_size: List[int],
               num_channels: int = 3):
    """Initializes panoptic segmentation module for export."""

    if batch_size is None:
      raise ValueError('batch_size cannot be None for panoptic segmentation '
                       'model.')
    if not isinstance(model, panoptic_maskrcnn_model.PanopticMaskRCNNModel):
      raise ValueError('PanopticSegmentationModule module not implemented for '
                       '{} model.'.format(type(model)))

    super().__init__(
        params=params,
        model=model,
        batch_size=batch_size,
        input_image_size=input_image_size,
        num_channels=num_channels)

  def serve(self, images: tf.Tensor):
    """Casts image to float and run inference.

    Args:
      images: uint8 Tensor of shape [batch_size, None, None, 3]
    Returns:

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/panoptic/serving/panoptic_maskrcnn.py:39 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/ac57b1a8155830cf. Report an issue: GitHub.