class_docstr: GoogLeNet model.
  
  The following is a list of string that can be specified to ``use_up_to`` option in ``__call__`` method;
  
  * ``'classifier'`` (default): The output of the final affine layer for classification.
  * ``'pool'``: The output of the final global average pooling.
  * ``'prepool'``: The input of the final global average pooling, i.e. the output of the final inception block.
  
  References:
      * `Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich: Going Deeper with Convolutions.
        <https://arxiv.org/pdf/1409.4842.pdf>`_
code: def __init__(self):
      # Load nnp
      self._load_nnp("GoogLeNet.nnp", "GoogLeNet/GoogLeNet.nnp")
  
file_path: nnabla/python/src/nnabla/models/imagenet/googlenet.py
imports: from __future__ import absolute_import
  from nnabla.utils.nnp_graph import NnpNetworkPass
  from .base import ImageNetBase
label_desc: Use image node_id 1 to create a new GoogLeNet object from inherited base classes: ImageNetBase with example: obj = GoogLeNet()