class_docstr: Base class for ONNX exportable model describing metadata on how to export the model through the ONNX format.
docstr: The default batch size to use if no other indication
  
  Returns:
      Integer > 0
docstr_tok: ["The","default","batch","size","to","use","if","no","other","indication","Returns",":","Integer",">","0"]
code: def default_batch_size(self) -> int:
      """
      The default batch size to use if no other indication
  
      Returns:
          Integer > 0
      """
      # Using 2 avoid ONNX making assumption about single sample batch
      return OnnxConfig.default_fixed_batch
  
imports: import copy
  import dataclasses
  import warnings
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Mapping, Optional, Tuple, Union
  import numpy
  from packaging import version
  from ..utils import TensorType, is_torch_available, is_vision_available, logging
  from .utils import ParameterFormat, compute_effective_axis_dimension, compute_serialized_parameters_size
label_desc: Use image node_id 6 for calling the OnnxConfig obj's underlying member method code with example usage: obj.default_batch_size() and returns: OnnxConfig