Method _ensure_safe

tensorflow/lite/python/interpreter.py:258–272

Makes sure no numpy arrays pointing to internal buffers are active. This should be called from any function that will call a function on _interpreter that may reallocate memory e.g. invoke(), ... Raises: RuntimeError: If there exist numpy objects pointing to internal memory

(self)

    return sys.getrefcount(self._interpreter) == 2

  def _ensure_safe(self):
    """Makes sure no numpy arrays pointing to internal buffers are active.

    This should be called from any function that will call a function on
    _interpreter that may reallocate memory e.g. invoke(), ...

    Raises:
      RuntimeError: If there exist numpy objects pointing to internal memory
        then we throw.
    """
    if not self._safe_to_run():
      raise RuntimeError("""There is at least 1 reference to internal data
      in the interpreter in the form of a numpy array or slice. Be sure to
      only hold the function returned from tensor() if you are using raw
      data access.""")

  def _get_tensor_details(self, tensor_index):
    """Gets tensor details.