tensorflow/models · error · ValueError

Wrong validation dataset size {!r}

Error message

Wrong validation dataset size {!r}

What it means

Error "Wrong validation dataset size {!r}" thrown in tensorflow/models.

Source

Thrown at official/vision/configs/video_classification.py:183

  init_checkpoint_modules: str = 'all'  # all or backbone
  freeze_backbone: bool = False
  # Spatial Partitioning fields.
  train_input_partition_dims: Optional[Tuple[int, ...]] = None
  eval_input_partition_dims: Optional[Tuple[int, ...]] = None


def add_trainer(experiment: cfg.ExperimentConfig,
                train_batch_size: int,
                eval_batch_size: int,
                learning_rate: float = 1.6,
                train_epochs: int = 44,
                warmup_epochs: int = 5):
  """Add and config a trainer to the experiment config."""
  if experiment.task.train_data.num_examples <= 0:
    raise ValueError('Wrong train dataset size {!r}'.format(
        experiment.task.train_data))
  if experiment.task.validation_data.num_examples <= 0:
    raise ValueError('Wrong validation dataset size {!r}'.format(
        experiment.task.validation_data))
  experiment.task.train_data.global_batch_size = train_batch_size
  experiment.task.validation_data.global_batch_size = eval_batch_size
  steps_per_epoch = experiment.task.train_data.num_examples // train_batch_size
  experiment.trainer = cfg.TrainerConfig(
      steps_per_loop=steps_per_epoch,
      summary_interval=steps_per_epoch,
      checkpoint_interval=steps_per_epoch,
      train_steps=train_epochs * steps_per_epoch,
      validation_steps=experiment.task.validation_data.num_examples //
      eval_batch_size,
      validation_interval=steps_per_epoch,
      optimizer_config=optimization.OptimizationConfig({
          'optimizer': {
              'type': 'sgd',
              'sgd': {
                  'momentum': 0.9,
                  'nesterov': True,

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/vision/configs/video_classification.py:183 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/52abe1a13d4b7a94. Report an issue: GitHub.