code: def resnet50(
      im_width=224, im_height=224, num_classes=1000, include_top=True
  ):
      return _resnet(
          Bottleneck,
          [3, 4, 6, 3],
          im_width,
          im_height,
          num_classes,
          include_top,
      )
  
file_path: deep-learning-for-image-processing/tensorflow_classification/Test5_resnet/model.py
imports: from tensorflow.keras import layers, Model, Sequential
label_desc: Use image node_id 4 for calling a global function with example usage: resnet50(im_width, im_height, num_classes, include_top) and returns: _resnet