code: def test_classification_architectures(
      arch_name, input_shape, output_size
  ):
      # Model
      model = classification.__dict__[arch_name](pretrained=True).eval()
      _test_classification(model, input_shape, output_size)
      # Check that you can pretrained everything up until the last layer
      classification.__dict__[arch_name](
          pretrained=True, num_classes=10
      )
  
file_path: doctr/tests/pytorch/test_models_classification_pt.py
imports: import os
  import tempfile
  import cv2
  import numpy
  import onnxruntime
  import pytest
  import torch
  from doctr.models import classification
  from doctr.models.classification.predictor import CropOrientationPredictor
  from doctr.models.utils import export_model_to_onnx
label_desc: Use image node_id 2 for calling a global function with example usage: test_classification_architectures(arch_name, input_shape, output_size) without return types