code: def EfficientNetB6(
      include_top=True,
      weights="imagenet",
      input_tensor=None,
      input_shape=None,
      pooling=None,
      classes=1000,
      **kwargs,
  ):
      return EfficientNet(
          1.8,
          2.6,
          528,
          0.5,
          model_name="efficientnet-b6",
          include_top=include_top,
          weights=weights,
          input_tensor=input_tensor,
          input_shape=input_shape,
          pooling=pooling,
          classes=classes,
          **kwargs,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import math
  import string
  import collections
  from six.moves import xrange
  from keras_applications.imagenet_utils import _obtain_input_shape
  from keras_applications.imagenet_utils import preprocess_input
  from .None import get_submodules_from_kwargs
  from .weights import IMAGENET_WEIGHTS_PATH, IMAGENET_WEIGHTS_HASHES, NS_WEIGHTS_HASHES, NS_WEIGHTS_PATH
label_desc: Use image node_id 14 for calling a global function with example usage: EfficientNetB6(include_top, weights, input_tensor, input_shape, pooling, classes) and returns: EfficientNet