code: def test_classification_models(arch_name, input_shape):
      batch_size = 8
      reco_model = classification.__dict__[arch_name](
          pretrained=True, input_shape=input_shape
      )
      assert isinstance(reco_model, tf.keras.Model)
      input_tensor = tf.random.uniform(
          shape=[batch_size, *input_shape], minval=0, maxval=1
      )
  
      out = reco_model(input_tensor)
      assert isinstance(out, tf.Tensor)
      assert out.shape.as_list() == [8, 4]
  
file_path: doctr/tests/tensorflow/test_models_classification_tf.py
imports: import os
  import tempfile
  import cv2
  import numpy
  import onnxruntime
  import psutil
  import pytest
  import tensorflow
  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_models(arch_name, input_shape) without return types