code: def test_intermediate_layer_getter():
      backbone = ResNet50(include_top=False, weights=None, pooling=None)
      feat_extractor = IntermediateLayerGetter(
          backbone, ["conv2_block3_out", "conv3_block4_out"]
      )
      # Check num of output features
      input_tensor = tf.random.uniform(
          shape=[1, 224, 224, 3], minval=0, maxval=1
      )
      assert len(feat_extractor(input_tensor)) == 2
  
      # Repr
      assert repr(feat_extractor) == "IntermediateLayerGetter()"
  
file_path: doctr/tests/tensorflow/test_models_utils_tf.py
imports: import os
  import pytest
  import tensorflow
  from tensorflow.keras import Sequential, layers
  from tensorflow.keras.applications import ResNet50
  from doctr.models.utils import IntermediateLayerGetter, _bf16_to_float32, _copy_tensor, conv_sequence, load_pretrained_params
label_desc: Use image node_id 5 for calling a global function with example usage: test_intermediate_layer_getter() without return types