class_docstr: Describes backbone information and provides utility functions.
      
class_docstr_tok: ["Describes","backbone","information","and","provides","utility","functions","."]
docstr: Downloads ImageNet weights and returns path to weights file.
          
docstr_tok: ["Downloads","ImageNet","weights","and","returns","path","to","weights","file","."]
code: def download_imagenet(self):
      """Downloads ImageNet weights and returns path to weights file."""
      from efficientnet.weights import IMAGENET_WEIGHTS_PATH
      from efficientnet.weights import IMAGENET_WEIGHTS_HASHES
  
      model_name = "efficientnet-b" + self.backbone[-1]
      file_name = (
          model_name
          + "_weights_tf_dim_ordering_tf_kernels_autoaugment_notop.h5"
      )
      file_hash = IMAGENET_WEIGHTS_HASHES[model_name][1]
      weights_path = keras.utils.get_file(
          file_name,
          IMAGENET_WEIGHTS_PATH + file_name,
          cache_subdir="models",
          file_hash=file_hash,
      )
      return weights_path
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/models/effnet.py
imports: from tensorflow import keras
  from .None import retinanet
  from .None import Backbone
  import efficientnet.keras
label_desc: Use image node_id 3 for calling the EfficientNetBackbone obj's underlying member method code with example usage: obj.download_imagenet() and returns: weights_path