code: def __init__(self, input_size=256, pretrained=False) -> None:
      super().__init__()
      if pretrained:
          self.img_model = _get_cnn(feature_extraction=True)
      else:
          self.img_model = TinyCnn(feature_extraction=True)
  
      self.misc_model = nn.Sequential(
          nn.Linear(input_size, 12), nn.ReLU()
      )
      self.fc = nn.Linear(12 * 2, 10)
  
imports: import unittest
  from typing import Callable, List, Union
  import torch
  import torch.nn
  from captum.insights import AttributionVisualizer, Batch
  from captum.insights.attr_vis.app import FilterConfig
  from captum.insights.attr_vis.features import BaseFeature, FeatureOutput, ImageFeature
  from tests.helpers.basic import BaseTest
label_desc: Use image node_id 1 to create a new TinyMultiModal object from inherited base classes: nn with example: obj = TinyMultiModal(input_size, pretrained)