code: def set_model_input_shape_attr(model, dataset=None, input_shape=None):
      """Sets an attribute named 'input_shape' within the model instance, specifying the expected input shape
  
      Args:
            model (nn.Module): Model instance
            dataset (str): Name of dataset from which to infer input shape
            input_shape (tuple): Tuple of integers representing the input shape. Can also be a tuple of tuples, allowing
              arbitrarily complex collections of tensors. Used only if 'dataset' is None
      """
      if not hasattr(model, "input_shape"):
          model.input_shape = _validate_input_shape(
              dataset, input_shape
          )
  
imports: import argparse
  from collections import OrderedDict
  from copy import deepcopy
  import logging
  import operator
  import random
  import numpy
  import torch
  import torch.nn
  import torch.backends.cudnn
  import yaml
  import inspect
label_desc: Use image node_id 42 for calling a global function with example usage: set_model_input_shape_attr(model, dataset, input_shape) without return types