code: def deserialize(config, custom_objects=None):
      """Instantiates a layer from a config dictionary.
  
      Args:
          config: dict of the form {'class_name': str, 'config': dict}
          custom_objects: dict mapping class names (or function names)
              of custom (non-Keras) objects to class/functions
  
      Returns:
          Layer instance (may be Model, Sequential, Network, Layer...)
      """
      populate_deserializable_objects()
      return generic_utils.deserialize_keras_object(
          config,
          module_objects=LOCAL.ALL_OBJECTS,
          custom_objects=custom_objects,
          printable_module_name="layer",
      )
  
file_path: tensorflow/tensorflow/python/keras/layers/serialization.py
imports: import threading
  from tensorflow.python import tf2
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.keras.engine import input_layer
  from tensorflow.python.keras.engine import input_spec
  from tensorflow.python.keras.layers import advanced_activations
  from tensorflow.python.keras.layers import convolutional
  from tensorflow.python.keras.layers import convolutional_recurrent
  from tensorflow.python.keras.layers import core
  from tensorflow.python.keras.layers import dense_attention
  from tensorflow.python.keras.layers import embeddings
  from tensorflow.python.keras.layers import merge
  from tensorflow.python.keras.layers import pooling
  from tensorflow.python.keras.layers import recurrent
  from tensorflow.python.keras.layers import rnn_cell_wrapper_v2
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import tf_inspect
label_desc: Use image node_id 3 for calling a global function with example usage: deserialize(config, custom_objects) and returns: generic_utils