code: def get_swish(**kwargs):
      backend, layers, models, keras_utils = get_submodules_from_kwargs(
          kwargs
      )
  
      def swish(x):
          """Swish activation function: x * sigmoid(x).
          Reference: [Searching for Activation Functions](https://arxiv.org/abs/1710.05941)
          """
  
          if backend.backend() == "tensorflow":
              try:
                  # The native TF implementation has a more
                  # memory-efficient gradient implementation
                  return backend.tf.nn.swish(x)
              except AttributeError:
                  pass
  
          return x * backend.sigmoid(x)
  
      return swish
  
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 2 for calling a global function with example usage: get_swish() and returns: swish, unknown, backend