tensorflow/models · error · ConfigError

{field_name} must be one of {list(allowed_values)}, got {val

Error message

{field_name} must be one of {list(allowed_values)}, got {value!r}.

What it means

Error "{field_name} must be one of {list(allowed_values)}, got {value!r}." thrown in tensorflow/models.

Source

Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/config_loader.py:370

  Each folder-name knob has exactly one allowed value declared in
  ``_ALLOWED_FOLDER_NAMES``. Any other value is rejected with a message
  listing the allowed set.

  Args:
      value: The value to validate.
      field_name: The top-level YAML field name (also the key into
        ``_ALLOWED_FOLDER_NAMES``).

  Returns:
      The validated string.

  Raises:
      ConfigError: If the value is not in the allowed set for that field.
  """
  allowed_values = _ALLOWED_FOLDER_NAMES[field_name]
  if value not in allowed_values:
    raise ConfigError(
        f"{field_name} must be one of {list(allowed_values)}, "
        f"got {value!r}."
    )
  return value


def _validate_crop_size(
    raw_crop_size: Any, prompt_name: str
) -> tuple[int, int]:
  """Validates and normalizes a crop_size entry into a tuple.

  Args:
      raw_crop_size: The value read from YAML; expected to be a two-element
        sequence of positive integers.
      prompt_name: Prompt name used in the error message.

  Returns:
      The crop size as a ``(height, width)`` tuple of ints.

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/config_loader.py:370 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/e39bdd08f289d8af. Report an issue: GitHub.